MRI classification system (MRICS) for children with cerebral palsy: development, reliability, and recommendations.

PubMed

Himmelmann, Kate; Horber, Veronka; De La Cruz, Javier; Horridge, Karen; Mejaski-Bosnjak, Vlatka; Hollody, Katalin; Krägeloh-Mann, Ingeborg

2017-01-01

To develop and evaluate a classification system for magnetic resonance imaging (MRI) findings of children with cerebral palsy (CP) that can be used in CP registers. The classification system was based on pathogenic patterns occurring in different periods of brain development. The MRI classification system (MRICS) consists of five main groups: maldevelopments, predominant white matter injury, predominant grey matter injury, miscellaneous, and normal findings. A detailed manual for the descriptions of these patterns was developed, including test cases (www.scpenetwork.eu/en/my-scpe/rtm/neuroimaging/cp-neuroimaging/). A literature review was performed and MRICS was compared with other classification systems. An exercise was carried out to check applicability and interrater reliability. Professionals working with children with CP or in CP registers were invited to participate in the exercise and chose to classify either 18 MRIs or MRI reports of children with CP. Classification systems in the literature were compatible with MRICS and harmonization possible. Interrater reliability was found to be good overall (k=0.69; 0.54-0.82) among the 41 participants and very good (k=0.81; 0.74-0.92) using the classification based on imaging reports. Surveillance of Cerebral Palsy in Europe (SCPE) proposes the MRICS as a reliable tool. Together with its manual it is simple to apply for CP registers. © 2016 Mac Keith Press.

A Review of Major Nursing Vocabularies and the Extent to Which They Have the Characteristics Required for Implementation in Computer-based Systems

PubMed Central

Henry, Suzanne Bakken; Warren, Judith J.; Lange, Linda; Button, Patricia

1998-01-01

Building on the work of previous authors, the Computer-based Patient Record Institute (CPRI) Work Group on Codes and Structures has described features of a classification scheme for implementation within a computer-based patient record. The authors of the current study reviewed the evaluation literature related to six major nursing vocabularies (the North American Nursing Diagnosis Association Taxonomy 1, the Nursing Interventions Classification, the Nursing Outcomes Classification, the Home Health Care Classification, the Omaha System, and the International Classification for Nursing Practice) to determine the extent to which the vocabularies include the CPRI features. None of the vocabularies met all criteria. The Omaha System, Home Health Care Classification, and International Classification for Nursing Practice each included five features. Criteria not fully met by any systems were clear and non-redundant representation of concepts, administrative cross-references, syntax and grammar, synonyms, uncertainty, context-free identifiers, and language independence. PMID:9670127

Classification and grading of muscle injuries: a narrative review

PubMed Central

Hamilton, Bruce; Valle, Xavier; Rodas, Gil; Til, Luis; Grive, Ricard Pruna; Rincon, Josep Antoni Gutierrez; Tol, Johannes L

2015-01-01

A limitation to the accurate study of muscle injuries and their management has been the lack of a uniform approach to the categorisation and grading of muscle injuries. The goal of this narrative review was to provide a framework from which to understand the historical progression of the classification and grading of muscle injuries. We reviewed the classification and grading of muscle injuries in the literature to critically illustrate the strengths, weaknesses, contradictions or controversies. A retrospective, citation-based methodology was applied to search for English language literature which evaluated or utilised a novel muscle classification or grading system. While there is an abundance of literature classifying and grading muscle injuries, it is predominantly expert opinion, and there remains little evidence relating any of the clinical or radiological features to an established pathology or clinical outcome. While the categorical grading of injury severity may have been a reasonable solution to a clinical challenge identified in the middle of the 20th century, it is time to recognise the complexity of the injury, cease trying to oversimplify it and to develop appropriately powered research projects to answer important questions. PMID:25394420

Localized contourlet features in vehicle make and model recognition

NASA Astrophysics Data System (ADS)

Zafar, I.; Edirisinghe, E. A.; Acar, B. S.

2009-02-01

Automatic vehicle Make and Model Recognition (MMR) systems provide useful performance enhancements to vehicle recognitions systems that are solely based on Automatic Number Plate Recognition (ANPR) systems. Several vehicle MMR systems have been proposed in literature. In parallel to this, the usefulness of multi-resolution based feature analysis techniques leading to efficient object classification algorithms have received close attention from the research community. To this effect, Contourlet transforms that can provide an efficient directional multi-resolution image representation has recently been introduced. Already an attempt has been made in literature to use Curvelet/Contourlet transforms in vehicle MMR. In this paper we propose a novel localized feature detection method in Contourlet transform domain that is capable of increasing the classification rates up to 4%, as compared to the previously proposed Contourlet based vehicle MMR approach in which the features are non-localized and thus results in sub-optimal classification. Further we show that the proposed algorithm can achieve the increased classification accuracy of 96% at significantly lower computational complexity due to the use of Two Dimensional Linear Discriminant Analysis (2DLDA) for dimensionality reduction by preserving the features with high between-class variance and low inter-class variance.

BeeSpace Navigator: exploratory analysis of gene function using semantic indexing of biological literature.

PubMed

Sen Sarma, Moushumi; Arcoleo, David; Khetani, Radhika S; Chee, Brant; Ling, Xu; He, Xin; Jiang, Jing; Mei, Qiaozhu; Zhai, ChengXiang; Schatz, Bruce

2011-07-01

With the rapid decrease in cost of genome sequencing, the classification of gene function is becoming a primary problem. Such classification has been performed by human curators who read biological literature to extract evidence. BeeSpace Navigator is a prototype software for exploratory analysis of gene function using biological literature. The software supports an automatic analogue of the curator process to extract functions, with a simple interface intended for all biologists. Since extraction is done on selected collections that are semantically indexed into conceptual spaces, the curation can be task specific. Biological literature containing references to gene lists from expression experiments can be analyzed to extract concepts that are computational equivalents of a classification such as Gene Ontology, yielding discriminating concepts that differentiate gene mentions from other mentions. The functions of individual genes can be summarized from sentences in biological literature, to produce results resembling a model organism database entry that is automatically computed. Statistical frequency analysis based on literature phrase extraction generates offline semantic indexes to support these gene function services. The website with BeeSpace Navigator is free and open to all; there is no login requirement at www.beespace.illinois.edu for version 4. Materials from the 2010 BeeSpace Software Training Workshop are available at www.beespace.illinois.edu/bstwmaterials.php.

Ototoxicity (cochleotoxicity) classifications: A review.

PubMed

Crundwell, Gemma; Gomersall, Phil; Baguley, David M

2016-01-01

Drug-mediated ototoxicity, specifically cochleotoxicity, is a concern for patients receiving medications for the treatment of serious illness. A number of classification schemes exist, most of which are based on pure-tone audiometry, in order to assist non-audiological/non-otological specialists in the identification and monitoring of iatrogenic hearing loss. This review identifies the primary classification systems used in cochleototoxicity monitoring. By bringing together classifications published in discipline-specific literature, the paper aims to increase awareness of their relative strengths and limitations in the assessment and monitoring of ototoxic hearing loss and to indicate how future classification systems may improve upon the status-quo. Literature review. PubMed identified 4878 articles containing the search term ototox*. A systematic search identified 13 key classification systems. Cochleotoxicity classification systems can be divided into those which focus on hearing change from a baseline audiogram and those that focus on the functional impact of the hearing loss. Common weaknesses of these grading scales included a lack of sensitivity to small adverse changes in hearing thresholds, a lack of high-frequency audiometry (>8 kHz), and lack of indication of which changes are likely to be clinically significant for communication and quality of life.

Classification of maxillectomy defects: a systematic review and criteria necessary for a universal description.

PubMed

Bidra, Avinash S; Jacob, Rhonda F; Taylor, Thomas D

2012-04-01

Maxillectomy defects are complex and involve a number of anatomic structures. Several maxillectomy defect classifications have been proposed with no universal acceptance among surgeons and prosthodontists. Established criteria for describing the maxillectomy defect are lacking. This systematic review aimed to evaluate classification systems in the available literature, to provide a critical appraisal, and to identify the criteria necessary for a universal description of maxillectomy and midfacial defects. An electronic search of the English language literature between the periods of 1974 and June 2011 was performed by using PubMed, Scopus, and Cochrane databases with predetermined inclusion criteria. Key terms included in the search were maxillectomy classification, maxillary resection classification, maxillary removal classification, maxillary reconstruction classification, midfacial defect classification, and midfacial reconstruction classification. This was supplemented by a manual search of selected journals. After application of predetermined exclusion criteria, the final list of articles was reviewed in-depth to provide a critical appraisal and identify criteria for a universal description of a maxillectomy defect. The electronic database search yielded 261 titles. Systematic application of inclusion and exclusion criteria resulted in identification of 14 maxillectomy and midfacial defect classification systems. From these articles, 6 different criteria were identified as necessary for a universal description of a maxillectomy defect. Multiple deficiencies were noted in each classification system. Though most articles described the superior-inferior extent of the defect, only a small number of articles described the anterior-posterior and medial-lateral extent of the defect. Few articles listed dental status and soft palate involvement when describing maxillectomy defects. No classification system has accurately described the maxillectomy defect, based on criteria that satisfy both surgical and prosthodontic needs. The 6 criteria identified in this systematic review for a universal description of a maxillectomy defect are: 1) dental status; 2) oroantral/nasal communication status; 3) soft palate and other contiguous structure involvement; 4) superior-inferior extent; 5) anterior-posterior extent; and 6) medial-lateral extent of the defect. A criteria-based description appears more objective and amenable for universal use than a classification-based description. Copyright © 2012 The Editorial Council of the Journal of Prosthetic Dentistry. Published by Mosby, Inc. All rights reserved.

The rationale behind Pierre Duhem's natural classification.

PubMed

Bhakthavatsalam, Sindhuja

2015-06-01

The central concern of this paper is the interpretation of Duhem's attitude towards physical theory. Based on his view that the classification of experimental laws yielded by theory progressively approaches a natural classification-a classification reflecting that of underlying realities-Duhem has been construed as a realist of sorts in recent literature. Here I argue that his positive attitude towards the theoretic classification of laws had rather to do with the pragmatic rationality of the physicist. Duhem's idea of natural classification was an intuitive idea in the mind of the physicist that had to be affirmed in order to justify the physicist's pursuit of theory. Copyright © 2015 Elsevier Ltd. All rights reserved.

Visual brain activity patterns classification with simultaneous EEG-fMRI: A multimodal approach.

PubMed

Ahmad, Rana Fayyaz; Malik, Aamir Saeed; Kamel, Nidal; Reza, Faruque; Amin, Hafeez Ullah; Hussain, Muhammad

2017-01-01

Classification of the visual information from the brain activity data is a challenging task. Many studies reported in the literature are based on the brain activity patterns using either fMRI or EEG/MEG only. EEG and fMRI considered as two complementary neuroimaging modalities in terms of their temporal and spatial resolution to map the brain activity. For getting a high spatial and temporal resolution of the brain at the same time, simultaneous EEG-fMRI seems to be fruitful. In this article, we propose a new method based on simultaneous EEG-fMRI data and machine learning approach to classify the visual brain activity patterns. We acquired EEG-fMRI data simultaneously on the ten healthy human participants by showing them visual stimuli. Data fusion approach is used to merge EEG and fMRI data. Machine learning classifier is used for the classification purposes. Results showed that superior classification performance has been achieved with simultaneous EEG-fMRI data as compared to the EEG and fMRI data standalone. This shows that multimodal approach improved the classification accuracy results as compared with other approaches reported in the literature. The proposed simultaneous EEG-fMRI approach for classifying the brain activity patterns can be helpful to predict or fully decode the brain activity patterns.

A systematic review of definitions and classification systems of adjacent segment pathology.

PubMed

Kraemer, Paul; Fehlings, Michael G; Hashimoto, Robin; Lee, Michael J; Anderson, Paul A; Chapman, Jens R; Raich, Annie; Norvell, Daniel C

2012-10-15

Systematic review. To undertake a systematic review to determine how "adjacent segment degeneration," "adjacent segment disease," or clinical pathological processes that serve as surrogates for adjacent segment pathology are classified and defined in the peer-reviewed literature. Adjacent segment degeneration and adjacent segment disease are terms referring to degenerative changes known to occur after reconstructive spine surgery, most commonly at an immediately adjacent functional spinal unit. These can include disc degeneration, instability, spinal stenosis, facet degeneration, and deformity. The true incidence and clinical impact of degenerative changes at the adjacent segment is unclear because there is lack of a universally accepted classification system that rigorously addresses clinical and radiological issues. A systematic review of the English language literature was undertaken and articles were classified using the Grades of Recommendation Assessment, Development, and Evaluation criteria. RESULTS.: Seven classification systems of spinal degeneration, including degeneration at the adjacent segment, were identified. None have been evaluated for reliability or validity specific to patients with degeneration at the adjacent segment. The ways in which terms related to adjacent segment "degeneration" or "disease" are defined in the peer-reviewed literature are highly variable. On the basis of the systematic review presented in this article, no formal classification system for either cervical or thoracolumbar adjacent segment disorders currently exists. No recommendations regarding the use of current classification of degeneration at any segments can be made based on the available literature. A new comprehensive definition for adjacent segment pathology (ASP, the now preferred terminology) has been proposed in this Focus Issue, which reflects the diverse pathology observed at functional spinal units adjacent to previous spinal reconstruction and balances detailed stratification with clinical utility. A comprehensive classification system is being developed through expert opinion and will require validation as well as peer review. Strength of Statement: Strong.

An application to pulmonary emphysema classification based on model of texton learning by sparse representation

NASA Astrophysics Data System (ADS)

Zhang, Min; Zhou, Xiangrong; Goshima, Satoshi; Chen, Huayue; Muramatsu, Chisako; Hara, Takeshi; Yokoyama, Ryojiro; Kanematsu, Masayuki; Fujita, Hiroshi

2012-03-01

We aim at using a new texton based texture classification method in the classification of pulmonary emphysema in computed tomography (CT) images of the lungs. Different from conventional computer-aided diagnosis (CAD) pulmonary emphysema classification methods, in this paper, firstly, the dictionary of texton is learned via applying sparse representation(SR) to image patches in the training dataset. Then the SR coefficients of the test images over the dictionary are used to construct the histograms for texture presentations. Finally, classification is performed by using a nearest neighbor classifier with a histogram dissimilarity measure as distance. The proposed approach is tested on 3840 annotated regions of interest consisting of normal tissue and mild, moderate and severe pulmonary emphysema of three subtypes. The performance of the proposed system, with an accuracy of about 88%, is comparably higher than state of the art method based on the basic rotation invariant local binary pattern histograms and the texture classification method based on texton learning by k-means, which performs almost the best among other approaches in the literature.

[Evaluation of traditional pathological classification at molecular classification era for gastric cancer].

PubMed

Yu, Yingyan

2014-01-01

Histopathological classification is in a pivotal position in both basic research and clinical diagnosis and treatment of gastric cancer. Currently, there are different classification systems in basic science and clinical application. In medical literatures, different classifications are used including Lauren and WHO systems, which have confused many researchers. Lauren classification has been proposed for half a century, but is still used worldwide. It shows many advantages of simple, easy handling with prognostic significance. The WHO classification scheme is better than Lauren classification in that it is continuously being revised according to the progress of gastric cancer, and is always used in the clinical and pathological diagnosis of common scenarios. Along with the progression of genomics, transcriptomics, proteomics, metabolomics researches, molecular classification of gastric cancer becomes the current hot topics. The traditional therapeutic approach based on phenotypic characteristics of gastric cancer will most likely be replaced with a gene variation mode. The gene-targeted therapy against the same molecular variation seems more reasonable than traditional chemical treatment based on the same morphological change.

Using classification models for the generation of disease-specific medications from biomedical literature and clinical data repository.

PubMed

Wang, Liqin; Haug, Peter J; Del Fiol, Guilherme

2017-05-01

Mining disease-specific associations from existing knowledge resources can be useful for building disease-specific ontologies and supporting knowledge-based applications. Many association mining techniques have been exploited. However, the challenge remains when those extracted associations contained much noise. It is unreliable to determine the relevance of the association by simply setting up arbitrary cut-off points on multiple scores of relevance; and it would be expensive to ask human experts to manually review a large number of associations. We propose that machine-learning-based classification can be used to separate the signal from the noise, and to provide a feasible approach to create and maintain disease-specific vocabularies. We initially focused on disease-medication associations for the purpose of simplicity. For a disease of interest, we extracted potentially treatment-related drug concepts from biomedical literature citations and from a local clinical data repository. Each concept was associated with multiple measures of relevance (i.e., features) such as frequency of occurrence. For the machine purpose of learning, we formed nine datasets for three diseases with each disease having two single-source datasets and one from the combination of previous two datasets. All the datasets were labeled using existing reference standards. Thereafter, we conducted two experiments: (1) to test if adding features from the clinical data repository would improve the performance of classification achieved using features from the biomedical literature only, and (2) to determine if classifier(s) trained with known medication-disease data sets would be generalizable to new disease(s). Simple logistic regression and LogitBoost were two classifiers identified as the preferred models separately for the biomedical-literature datasets and combined datasets. The performance of the classification using combined features provided significant improvement beyond that using biomedical-literature features alone (p-value<0.001). The performance of the classifier built from known diseases to predict associated concepts for new diseases showed no significant difference from the performance of the classifier built and tested using the new disease's dataset. It is feasible to use classification approaches to automatically predict the relevance of a concept to a disease of interest. It is useful to combine features from disparate sources for the task of classification. Classifiers built from known diseases were generalizable to new diseases. Copyright © 2017 Elsevier Inc. All rights reserved.

Recent development of feature extraction and classification multispectral/hyperspectral images: a systematic literature review

NASA Astrophysics Data System (ADS)

Setiyoko, A.; Dharma, I. G. W. S.; Haryanto, T.

2017-01-01

Multispectral data and hyperspectral data acquired from satellite sensor have the ability in detecting various objects on the earth ranging from low scale to high scale modeling. These data are increasingly being used to produce geospatial information for rapid analysis by running feature extraction or classification process. Applying the most suited model for this data mining is still challenging because there are issues regarding accuracy and computational cost. This research aim is to develop a better understanding regarding object feature extraction and classification applied for satellite image by systematically reviewing related recent research projects. A method used in this research is based on PRISMA statement. After deriving important points from trusted sources, pixel based and texture-based feature extraction techniques are promising technique to be analyzed more in recent development of feature extraction and classification.

Toward a Reasoned Classification of Diseases Using Physico-Chemical Based Phenotypes

PubMed Central

Schwartz, Laurent; Lafitte, Olivier; da Veiga Moreira, Jorgelindo

2018-01-01

Background: Diseases and health conditions have been classified according to anatomical site, etiological, and clinical criteria. Physico-chemical mechanisms underlying the biology of diseases, such as the flow of energy through cells and tissues, have been often overlooked in classification systems. Objective: We propose a conceptual framework toward the development of an energy-oriented classification of diseases, based on the principles of physical chemistry. Methods: A review of literature on the physical chemistry of biological interactions in a number of diseases is traced from the point of view of the fluid and solid mechanics, electricity, and chemistry. Results: We found consistent evidence in literature of decreased and/or increased physical and chemical forces intertwined with biological processes of numerous diseases, which allowed the identification of mechanical, electric and chemical phenotypes of diseases. Discussion: Biological mechanisms of diseases need to be evaluated and integrated into more comprehensive theories that should account with principles of physics and chemistry. A hypothetical model is proposed relating the natural history of diseases to mechanical stress, electric field, and chemical equilibria (ATP) changes. The present perspective toward an innovative disease classification may improve drug-repurposing strategies in the future. PMID:29541031

A simple working classification proposed for the latrogenic lesions of teeth and associated structures in the oral cavity.

PubMed

Shamim, Thorakkal

2013-09-01

Iatrogenic lesions can affect both hard and soft tissues in the oral cavity, induced by the dentist's activity, manner or therapy. There is no approved simple working classification for the iatrogenic lesions of teeth and associated structures in the oral cavity in the literature. A simple working classification is proposed here for iatrogenic lesions of teeth and associated structures in the oral cavity based on its relation with dental specialities. The dental specialities considered in this classification are conservative dentistry and endodontics, orthodontics, oral and maxillofacial surgery and prosthodontics. This classification will be useful for the dental clinician who is dealing with diseases of oral cavity.

Intra- and interobserver reliability of the Eaton classification for trapeziometacarpal arthritis: a systematic review.

PubMed

Berger, Aaron J; Momeni, Arash; Ladd, Amy L

2014-04-01

Trapeziometacarpal, or thumb carpometacarpal (CMC), arthritis is a common problem with a variety of treatment options. Although widely used, the Eaton radiographic staging system for CMC arthritis is of questionable clinical utility, as disease severity does not predictably correlate with symptoms or treatment recommendations. A possible reason for this is that the classification itself may not be reliable, but the literature on this has not, to our knowledge, been systematically reviewed. We therefore performed a systematic review to determine the intra- and interobserver reliability of the Eaton staging system. We systematically reviewed English-language studies published between 1973 and 2013 to assess the degree of intra- and interobserver reliability of the Eaton classification for determining the stage of trapeziometacarpal joint arthritis and pantrapezial arthritis based on plain radiographic imaging. Search engines included: PubMed, Scopus(®), and CINAHL. Four studies, which included a total of 163 patients, met our inclusion criteria and were evaluated. The level of evidence of the studies included in this analysis was determined using the Oxford Centre for Evidence Based Medicine Levels of Evidence Classification by two independent observers. A limited number of studies have been performed to assess intra- and interobserver reliability of the Eaton classification system. The four studies included were determined to be Level 3b. These studies collectively indicate that the Eaton classification demonstrates poor to fair interobserver reliability (kappa values: 0.11-0.56) and fair to moderate intraobserver reliability (kappa values: 0.54-0.657). Review of the literature demonstrates that radiographs assist in the assessment of CMC joint disease, but there is not a reliable system for classification of disease severity. Currently, diagnosis and treatment of thumb CMC arthritis are based on the surgeon's qualitative assessment combining history, physical examination, and radiographic evaluation. Inconsistent agreement using the current common radiographic classification system suggests a need for better radiographic tools to quantify disease severity.

Locality-preserving sparse representation-based classification in hyperspectral imagery

NASA Astrophysics Data System (ADS)

Gao, Lianru; Yu, Haoyang; Zhang, Bing; Li, Qingting

2016-10-01

This paper proposes to combine locality-preserving projections (LPP) and sparse representation (SR) for hyperspectral image classification. The LPP is first used to reduce the dimensionality of all the training and testing data by finding the optimal linear approximations to the eigenfunctions of the Laplace Beltrami operator on the manifold, where the high-dimensional data lies. Then, SR codes the projected testing pixels as sparse linear combinations of all the training samples to classify the testing pixels by evaluating which class leads to the minimum approximation error. The integration of LPP and SR represents an innovative contribution to the literature. The proposed approach, called locality-preserving SR-based classification, addresses the imbalance between high dimensionality of hyperspectral data and the limited number of training samples. Experimental results on three real hyperspectral data sets demonstrate that the proposed approach outperforms the original counterpart, i.e., SR-based classification.

Mandatory, Preferred, or Discretionary: How the Classification of Domestic Violence Warrantless Arrest Laws Impacts Their Estimated Effects on Intimate Partner Homicide

ERIC Educational Resources Information Center

Zeoli, April M.; Norris, Alexis; Brenner, Hannah

2011-01-01

Warrantless arrest laws for domestic violence (DV) are generally classified as discretionary, preferred, or mandatory, based on the level of power accorded to police in deciding whether to arrest. However, there is a lack of consensus in the literature regarding how each state's law should be categorized. Using three classification schemes, this…

Quantitative evaluation of variations in rule-based classifications of land cover in urban neighbourhoods using WorldView-2 imagery.

PubMed

Belgiu, Mariana; Dr Guţ, Lucian; Strobl, Josef

2014-01-01

The increasing availability of high resolution imagery has triggered the need for automated image analysis techniques, with reduced human intervention and reproducible analysis procedures. The knowledge gained in the past might be of use to achieving this goal, if systematically organized into libraries which would guide the image analysis procedure. In this study we aimed at evaluating the variability of digital classifications carried out by three experts who were all assigned the same interpretation task. Besides the three classifications performed by independent operators, we developed an additional rule-based classification that relied on the image classifications best practices found in the literature, and used it as a surrogate for libraries of object characteristics. The results showed statistically significant differences among all operators who classified the same reference imagery. The classifications carried out by the experts achieved satisfactory results when transferred to another area for extracting the same classes of interest, without modification of the developed rules.

Quantitative evaluation of variations in rule-based classifications of land cover in urban neighbourhoods using WorldView-2 imagery

PubMed Central

Belgiu, Mariana; Drǎguţ, Lucian; Strobl, Josef

2014-01-01

The increasing availability of high resolution imagery has triggered the need for automated image analysis techniques, with reduced human intervention and reproducible analysis procedures. The knowledge gained in the past might be of use to achieving this goal, if systematically organized into libraries which would guide the image analysis procedure. In this study we aimed at evaluating the variability of digital classifications carried out by three experts who were all assigned the same interpretation task. Besides the three classifications performed by independent operators, we developed an additional rule-based classification that relied on the image classifications best practices found in the literature, and used it as a surrogate for libraries of object characteristics. The results showed statistically significant differences among all operators who classified the same reference imagery. The classifications carried out by the experts achieved satisfactory results when transferred to another area for extracting the same classes of interest, without modification of the developed rules. PMID:24623959

Quantitative evaluation of variations in rule-based classifications of land cover in urban neighbourhoods using WorldView-2 imagery

NASA Astrophysics Data System (ADS)

Belgiu, Mariana; ǎguţ, Lucian, , Dr; Strobl, Josef

2014-01-01

The increasing availability of high resolution imagery has triggered the need for automated image analysis techniques, with reduced human intervention and reproducible analysis procedures. The knowledge gained in the past might be of use to achieving this goal, if systematically organized into libraries which would guide the image analysis procedure. In this study we aimed at evaluating the variability of digital classifications carried out by three experts who were all assigned the same interpretation task. Besides the three classifications performed by independent operators, we developed an additional rule-based classification that relied on the image classifications best practices found in the literature, and used it as a surrogate for libraries of object characteristics. The results showed statistically significant differences among all operators who classified the same reference imagery. The classifications carried out by the experts achieved satisfactory results when transferred to another area for extracting the same classes of interest, without modification of the developed rules.

Understanding the use of standardized nursing terminology and classification systems in published research: A case study using the International Classification for Nursing Practice(®).

PubMed

Strudwick, Gillian; Hardiker, Nicholas R

2016-10-01

In the era of evidenced based healthcare, nursing is required to demonstrate that care provided by nurses is associated with optimal patient outcomes, and a high degree of quality and safety. The use of standardized nursing terminologies and classification systems are a way that nursing documentation can be leveraged to generate evidence related to nursing practice. Several widely-reported nursing specific terminologies and classifications systems currently exist including the Clinical Care Classification System, International Classification for Nursing Practice(®), Nursing Intervention Classification, Nursing Outcome Classification, Omaha System, Perioperative Nursing Data Set and NANDA International. However, the influence of these systems on demonstrating the value of nursing and the professions' impact on quality, safety and patient outcomes in published research is relatively unknown. This paper seeks to understand the use of standardized nursing terminology and classification systems in published research, using the International Classification for Nursing Practice(®) as a case study. A systematic review of international published empirical studies on, or using, the International Classification for Nursing Practice(®) were completed using Medline and the Cumulative Index for Nursing and Allied Health Literature. Since 2006, 38 studies have been published on the International Classification for Nursing Practice(®). The main objectives of the published studies have been to validate the appropriateness of the classification system for particular care areas or populations, further develop the classification system, or utilize it to support the generation of new nursing knowledge. To date, most studies have focused on the classification system itself, and a lesser number of studies have used the system to generate information about the outcomes of nursing practice. Based on the published literature that features the International Classification for Nursing Practice, standardized nursing terminology and classification systems appear to be well developed for various populations, settings and to harmonize with other health-related terminology systems. However, the use of the systems to generate new nursing knowledge, and to validate nursing practice is still in its infancy. There is an opportunity now to utilize the well-developed systems in their current state to further what is know about nursing practice, and how best to demonstrate improvements in patient outcomes through nursing care. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Model-based classification of CPT data and automated lithostratigraphic mapping for high-resolution characterization of a heterogeneous sedimentary aquifer

PubMed Central

Mallants, Dirk; Batelaan, Okke; Gedeon, Matej; Huysmans, Marijke; Dassargues, Alain

2017-01-01

Cone penetration testing (CPT) is one of the most efficient and versatile methods currently available for geotechnical, lithostratigraphic and hydrogeological site characterization. Currently available methods for soil behaviour type classification (SBT) of CPT data however have severe limitations, often restricting their application to a local scale. For parameterization of regional groundwater flow or geotechnical models, and delineation of regional hydro- or lithostratigraphy, regional SBT classification would be very useful. This paper investigates the use of model-based clustering for SBT classification, and the influence of different clustering approaches on the properties and spatial distribution of the obtained soil classes. We additionally propose a methodology for automated lithostratigraphic mapping of regionally occurring sedimentary units using SBT classification. The methodology is applied to a large CPT dataset, covering a groundwater basin of ~60 km2 with predominantly unconsolidated sandy sediments in northern Belgium. Results show that the model-based approach is superior in detecting the true lithological classes when compared to more frequently applied unsupervised classification approaches or literature classification diagrams. We demonstrate that automated mapping of lithostratigraphic units using advanced SBT classification techniques can provide a large gain in efficiency, compared to more time-consuming manual approaches and yields at least equally accurate results. PMID:28467468

Model-based classification of CPT data and automated lithostratigraphic mapping for high-resolution characterization of a heterogeneous sedimentary aquifer.

PubMed

Rogiers, Bart; Mallants, Dirk; Batelaan, Okke; Gedeon, Matej; Huysmans, Marijke; Dassargues, Alain

2017-01-01

Cone penetration testing (CPT) is one of the most efficient and versatile methods currently available for geotechnical, lithostratigraphic and hydrogeological site characterization. Currently available methods for soil behaviour type classification (SBT) of CPT data however have severe limitations, often restricting their application to a local scale. For parameterization of regional groundwater flow or geotechnical models, and delineation of regional hydro- or lithostratigraphy, regional SBT classification would be very useful. This paper investigates the use of model-based clustering for SBT classification, and the influence of different clustering approaches on the properties and spatial distribution of the obtained soil classes. We additionally propose a methodology for automated lithostratigraphic mapping of regionally occurring sedimentary units using SBT classification. The methodology is applied to a large CPT dataset, covering a groundwater basin of ~60 km2 with predominantly unconsolidated sandy sediments in northern Belgium. Results show that the model-based approach is superior in detecting the true lithological classes when compared to more frequently applied unsupervised classification approaches or literature classification diagrams. We demonstrate that automated mapping of lithostratigraphic units using advanced SBT classification techniques can provide a large gain in efficiency, compared to more time-consuming manual approaches and yields at least equally accurate results.

The Influence of Hindu Epistemology on Ranganathan's Colon Classification.

ERIC Educational Resources Information Center

Maurer, Bradley Gerald

This study attempted to determine the influence of Hindu epistemology on Ranganathan's Colon Classification. Only the epistemological schools of Hindu philosophy and the Idea Plane element of Colon Classification were included. A literature search revealed that, although there is significant literature on each side of the problem, no bridges exist…

Intrinsic Remediation Engineering Evaluation/Cost Analysis for Car Care Center at Bolling Air Force Base, Washington, DC

DTIC Science & Technology

1997-01-01

supplemented using established literature values for similar aquifer materials . The groundwater sampling activities and analytical results from both...subsurface materials recovered. Observed soil classification types compared very favorably to the soil classifications determined by the CPT tests. 0 2.1.5...other similar substances were handled in a manner consistent with accepted safety procedures and standard operating practices. Well completion materials

Nasal Septal Deviations: A Systematic Review of Classification Systems.

PubMed

Teixeira, Jeffrey; Certal, Victor; Chang, Edward T; Camacho, Macario

2016-01-01

Objective. To systematically review the international literature for internal nasal septal deviation classification systems and summarize them for clinical and research purposes. Data Sources. Four databases (including PubMed/MEDLINE) were systematically searched through December 16, 2015. Methods. Systematic review, adhering to PRISMA. Results. After removal of duplicates, this study screened 952 articles for relevance. A final comprehensive review of 50 articles identified that 15 of these articles met the eligibility criteria. The classification systems defined in these articles included C-shaped, S-shaped, reverse C-shaped, and reverse S-shaped descriptions of the septal deviation in both the cephalocaudal and anteroposterior dimensions. Additional studies reported use of computed tomography and categorized deviation based on predefined locations. Three studies graded the severity of septal deviations based on the amount of deflection. The systems defined in the literature also included an evaluation of nasal septal spurs and perforations. Conclusion. This systematic review ascertained that the majority of the currently published classification systems for internal nasal septal deviations can be summarized by C-shaped or reverse C-shaped, as well as S-shaped or reverse S-shaped deviations in the anteroposterior and cephalocaudal dimensions. For imaging studies, predefined points have been defined along the septum. Common terminology can facilitate future research.

Proposal of a new radiological classification system for spinal meningiomas as a descriptive tool and surgical guide.

PubMed

Bayoumi, Ahmed B; Laviv, Yosef; Yokus, Burhan; Efe, Ibrahim E; Toktas, Zafer Orkun; Kilic, Turker; Demir, Mustafa K; Konya, Deniz; Kasper, Ekkehard M

2017-11-01

1) To provide neurosurgeons and radiologists with a new quantitative and anatomical method to describe spinal meningiomas (SM) consistently. 2) To provide a guide to the surgical approach needed and amount of bony resection required based on the proposed classification. 3) To report the distribution of our 58 cases of SM over different Stages and Subtypes in correlation to the surgical treatment needed for each case. 4) To briefly review the literature on the rare non-conventional surgical corridors to resect SM. We reviewed the literature to report on previously published cohorts and classifications used to describe the location of the tumor inside the spinal canal. We reviewed the cases that were published prior showing non-conventional surgical approaches to resect spinal meningiomas. We proposed our classification system composed of Staging based on maximal cross-sectional surface area of tumor inside canal, Typing based on number of quadrants occupied by tumor and Subtyping based on location of the tumor bulk to spinal cord. Extradural and extra-spinal growth were also covered by our classification. We then applied it retrospectively on our 58 cases. 12 articles were published illustrating overlapping terms to describe spinal meningiomas. Another 7 articles were published reporting on 23 cases of anteriorly located spinal meningiomas treated with approaches other than laminectomies/laminoplasties. 4 Types, 9 Subtypes and 4 Stages were described in our Classification System. In our series of 58 patients, no midline anterior type was represented. Therefore, all our cases were treated by laminectomies or laminoplasties (with/without facetectomies) except a case with a paraspinal component where a costotransversectomy was needed. Spinal meningiomas can be radiologically described in a precise fashion. Selection of surgical corridor depends mainly on location of tumor bulk inside canal. Copyright © 2017 Elsevier B.V. All rights reserved.

Speech emotion recognition methods: A literature review

NASA Astrophysics Data System (ADS)

Basharirad, Babak; Moradhaseli, Mohammadreza

2017-10-01

Recently, attention of the emotional speech signals research has been boosted in human machine interfaces due to availability of high computation capability. There are many systems proposed in the literature to identify the emotional state through speech. Selection of suitable feature sets, design of a proper classifications methods and prepare an appropriate dataset are the main key issues of speech emotion recognition systems. This paper critically analyzed the current available approaches of speech emotion recognition methods based on the three evaluating parameters (feature set, classification of features, accurately usage). In addition, this paper also evaluates the performance and limitations of available methods. Furthermore, it highlights the current promising direction for improvement of speech emotion recognition systems.

A hybrid clustering and classification approach for predicting crash injury severity on rural roads.

PubMed

Hasheminejad, Seyed Hessam-Allah; Zahedi, Mohsen; Hasheminejad, Seyed Mohammad Hossein

2018-03-01

As a threat for transportation system, traffic crashes have a wide range of social consequences for governments. Traffic crashes are increasing in developing countries and Iran as a developing country is not immune from this risk. There are several researches in the literature to predict traffic crash severity based on artificial neural networks (ANNs), support vector machines and decision trees. This paper attempts to investigate the crash injury severity of rural roads by using a hybrid clustering and classification approach to compare the performance of classification algorithms before and after applying the clustering. In this paper, a novel rule-based genetic algorithm (GA) is proposed to predict crash injury severity, which is evaluated by performance criteria in comparison with classification algorithms like ANN. The results obtained from analysis of 13,673 crashes (5600 property damage, 778 fatal crashes, 4690 slight injuries and 2605 severe injuries) on rural roads in Tehran Province of Iran during 2011-2013 revealed that the proposed GA method outperforms other classification algorithms based on classification metrics like precision (86%), recall (88%) and accuracy (87%). Moreover, the proposed GA method has the highest level of interpretation, is easy to understand and provides feedback to analysts.

Evaluation of a Machine-Learning Classifier for Keratoconus Detection Based on Scheimpflug Tomography.

PubMed

Ruiz Hidalgo, Irene; Rodriguez, Pablo; Rozema, Jos J; Ní Dhubhghaill, Sorcha; Zakaria, Nadia; Tassignon, Marie-José; Koppen, Carina

2016-06-01

To evaluate the performance of a support vector machine algorithm that automatically and objectively identifies corneal patterns based on a combination of 22 parameters obtained from Pentacam measurements and to compare this method with other known keratoconus (KC) classification methods. Pentacam data from 860 eyes were included in the study and divided into 5 groups: 454 KC, 67 forme fruste (FF), 28 astigmatic, 117 after refractive surgery (PR), and 194 normal eyes (N). Twenty-two parameters were used for classification using a support vector machine algorithm developed in Weka, a machine-learning computer software. The cross-validation accuracy for 3 different classification tasks (KC vs. N, FF vs. N and all 5 groups) was calculated and compared with other known classification methods. The accuracy achieved in the KC versus N discrimination task was 98.9%, with 99.1% sensitivity and 98.5% specificity for KC detection. The accuracy in the FF versus N task was 93.1%, with 79.1% sensitivity and 97.9% specificity for the FF discrimination. Finally, for the 5-groups classification, the accuracy was 88.8%, with a weighted average sensitivity of 89.0% and specificity of 95.2%. Despite using the strictest definition for FF KC, the present study obtained comparable or better results than the single-parameter methods and indices reported in the literature. In some cases, direct comparisons with the literature were not possible because of differences in the compositions and definitions of the study groups, especially the FF KC.

The addition of entropy-based regularity parameters improves sleep stage classification based on heart rate variability.

PubMed

Aktaruzzaman, M; Migliorini, M; Tenhunen, M; Himanen, S L; Bianchi, A M; Sassi, R

2015-05-01

The work considers automatic sleep stage classification, based on heart rate variability (HRV) analysis, with a focus on the distinction of wakefulness (WAKE) from sleep and rapid eye movement (REM) from non-REM (NREM) sleep. A set of 20 automatically annotated one-night polysomnographic recordings was considered, and artificial neural networks were selected for classification. For each inter-heartbeat (RR) series, beside features previously presented in literature, we introduced a set of four parameters related to signal regularity. RR series of three different lengths were considered (corresponding to 2, 6, and 10 successive epochs, 30 s each, in the same sleep stage). Two sets of only four features captured 99 % of the data variance in each classification problem, and both of them contained one of the new regularity features proposed. The accuracy of classification for REM versus NREM (68.4 %, 2 epochs; 83.8 %, 10 epochs) was higher than when distinguishing WAKE versus SLEEP (67.6 %, 2 epochs; 71.3 %, 10 epochs). Also, the reliability parameter (Cohens's Kappa) was higher (0.68 and 0.45, respectively). Sleep staging classification based on HRV was still less precise than other staging methods, employing a larger variety of signals collected during polysomnographic studies. However, cheap and unobtrusive HRV-only sleep classification proved sufficiently precise for a wide range of applications.

Four Levels of Moral Conflict in ISD

NASA Astrophysics Data System (ADS)

Vartiainen, Tero

This study introduces a literature-based classification of moral conflicts in information systems development (ISD). The classification describes what moral conflicts an IS professional confronts in ISD as a whole and includes intentional, functional, managerial, and societal levels. The internal structure of moral conflicts is exemplified by means of a philosophical and a business ethics theory. The limitations of the study are considered and practical implications for the teaching of computer ethics are discussed.

The fallopian canal: a comprehensive review and proposal of a new classification.

PubMed

Mortazavi, M M; Latif, B; Verma, K; Adeeb, N; Deep, A; Griessenauer, C J; Tubbs, R S; Fukushima, T

2014-03-01

The facial nerve follows a complex course through the skull base. Understanding its anatomy is crucial during standard skull base approaches and resection of certain skull base tumors closely related to the nerve, especially, tumors at the cerebellopontine angle. Herein, we review the fallopian canal and its implications in surgical approaches to the skull base. Furthermore, we suggest a new classification. Based on the anatomy and literature, we propose that the meatal segment of the facial nerve be included as a component of the fallopian canal. A comprehensive knowledge of the course of the facial nerve is important to those who treat patients with pathology of or near this cranial nerve.

A probabilistic approach to segmentation and classification of neoplasia in uterine cervix images using color and geometric features

NASA Astrophysics Data System (ADS)

Srinivasan, Yeshwanth; Hernes, Dana; Tulpule, Bhakti; Yang, Shuyu; Guo, Jiangling; Mitra, Sunanda; Yagneswaran, Sriraja; Nutter, Brian; Jeronimo, Jose; Phillips, Benny; Long, Rodney; Ferris, Daron

2005-04-01

Automated segmentation and classification of diagnostic markers in medical imagery are challenging tasks. Numerous algorithms for segmentation and classification based on statistical approaches of varying complexity are found in the literature. However, the design of an efficient and automated algorithm for precise classification of desired diagnostic markers is extremely image-specific. The National Library of Medicine (NLM), in collaboration with the National Cancer Institute (NCI), is creating an archive of 60,000 digitized color images of the uterine cervix. NLM is developing tools for the analysis and dissemination of these images over the Web for the study of visual features correlated with precancerous neoplasia and cancer. To enable indexing of images of the cervix, it is essential to develop algorithms for the segmentation of regions of interest, such as acetowhitened regions, and automatic identification and classification of regions exhibiting mosaicism and punctation. Success of such algorithms depends, primarily, on the selection of relevant features representing the region of interest. We present color and geometric features based statistical classification and segmentation algorithms yielding excellent identification of the regions of interest. The distinct classification of the mosaic regions from the non-mosaic ones has been obtained by clustering multiple geometric and color features of the segmented sections using various morphological and statistical approaches. Such automated classification methodologies will facilitate content-based image retrieval from the digital archive of uterine cervix and have the potential of developing an image based screening tool for cervical cancer.

Extraction of Pharmacokinetic Evidence of Drug–Drug Interactions from the Literature

PubMed Central

Kolchinsky, Artemy; Lourenço, Anália; Wu, Heng-Yi; Li, Lang; Rocha, Luis M.

2015-01-01

Drug-drug interaction (DDI) is a major cause of morbidity and mortality and a subject of intense scientific interest. Biomedical literature mining can aid DDI research by extracting evidence for large numbers of potential interactions from published literature and clinical databases. Though DDI is investigated in domains ranging in scale from intracellular biochemistry to human populations, literature mining has not been used to extract specific types of experimental evidence, which are reported differently for distinct experimental goals. We focus on pharmacokinetic evidence for DDI, essential for identifying causal mechanisms of putative interactions and as input for further pharmacological and pharmacoepidemiology investigations. We used manually curated corpora of PubMed abstracts and annotated sentences to evaluate the efficacy of literature mining on two tasks: first, identifying PubMed abstracts containing pharmacokinetic evidence of DDIs; second, extracting sentences containing such evidence from abstracts. We implemented a text mining pipeline and evaluated it using several linear classifiers and a variety of feature transforms. The most important textual features in the abstract and sentence classification tasks were analyzed. We also investigated the performance benefits of using features derived from PubMed metadata fields, various publicly available named entity recognizers, and pharmacokinetic dictionaries. Several classifiers performed very well in distinguishing relevant and irrelevant abstracts (reaching F1≈0.93, MCC≈0.74, iAUC≈0.99) and sentences (F1≈0.76, MCC≈0.65, iAUC≈0.83). We found that word bigram features were important for achieving optimal classifier performance and that features derived from Medical Subject Headings (MeSH) terms significantly improved abstract classification. We also found that some drug-related named entity recognition tools and dictionaries led to slight but significant improvements, especially in classification of evidence sentences. Based on our thorough analysis of classifiers and feature transforms and the high classification performance achieved, we demonstrate that literature mining can aid DDI discovery by supporting automatic extraction of specific types of experimental evidence. PMID:25961290

True aneurysm in autologous hemodialysis fistulae: definitions, classification and indications for treatment.

PubMed

Balaz, Peter; Björck, Martin

2015-01-01

Definition, etiology, classification and indication for treatment of the arteriovenous access (AVA) aneurysm are poorly described in medical literature. The objectives of the paper are to complete this information gap according to the extensive review of the literature. A literature search was performed of the articles published between April 1, 1967, and March 1, 2014. The databases searched included Medline and the Cochrane Database of Systematic Reviews. The eligibility criteria in this review studies the need to assess the association of aneurysms and pseudoaneurysms with autologous AVA. Aneurysms and pseudoaneurysms involving prosthetic AVA were not included in this literature review. From a total of 327 papers, 54 non-English papers, 40 case reports and 167 papers which did not meet the eligibility criteria were removed. The remaining 66 papers were reviewed. Based on the literature the indication for the treatment of an AVA aneurysm is its clinical presentation related to the patient's discomfort, bleeding prevention and inadequate access flow. A new classification system of AVA aneurysm, which divides it into the four types, was also suggested. AVA aneurysm is characterized by an enlargement of all three vessel layers with a diameter of more than 18 mm and can be presented in four types according to the presence of stenosis and/or thrombosis. The management of an AVA aneurysm depends on several factors including skin condition, clinical symptoms, ease of cannulation and access flow. The diameter of the AVA aneurysm as a solo parameter is not an indication for the treatment.

Particle Swarm Optimization approach to defect detection in armour ceramics.

PubMed

Kesharaju, Manasa; Nagarajah, Romesh

2017-03-01

In this research, various extracted features were used in the development of an automated ultrasonic sensor based inspection system that enables defect classification in each ceramic component prior to despatch to the field. Classification is an important task and large number of irrelevant, redundant features commonly introduced to a dataset reduces the classifiers performance. Feature selection aims to reduce the dimensionality of the dataset while improving the performance of a classification system. In the context of a multi-criteria optimization problem (i.e. to minimize classification error rate and reduce number of features) such as one discussed in this research, the literature suggests that evolutionary algorithms offer good results. Besides, it is noted that Particle Swarm Optimization (PSO) has not been explored especially in the field of classification of high frequency ultrasonic signals. Hence, a binary coded Particle Swarm Optimization (BPSO) technique is investigated in the implementation of feature subset selection and to optimize the classification error rate. In the proposed method, the population data is used as input to an Artificial Neural Network (ANN) based classification system to obtain the error rate, as ANN serves as an evaluator of PSO fitness function. Copyright © 2016. Published by Elsevier B.V.

Cluster Analysis in Nursing Research: An Introduction, Historical Perspective, and Future Directions.

PubMed

Dunn, Heather; Quinn, Laurie; Corbridge, Susan J; Eldeirawi, Kamal; Kapella, Mary; Collins, Eileen G

2017-05-01

The use of cluster analysis in the nursing literature is limited to the creation of classifications of homogeneous groups and the discovery of new relationships. As such, it is important to provide clarity regarding its use and potential. The purpose of this article is to provide an introduction to distance-based, partitioning-based, and model-based cluster analysis methods commonly utilized in the nursing literature, provide a brief historical overview on the use of cluster analysis in nursing literature, and provide suggestions for future research. An electronic search included three bibliographic databases, PubMed, CINAHL and Web of Science. Key terms were cluster analysis and nursing. The use of cluster analysis in the nursing literature is increasing and expanding. The increased use of cluster analysis in the nursing literature is positioning this statistical method to result in insights that have the potential to change clinical practice.

Ecosystem Services Linking People to Coastal Habitats ...

EPA Pesticide Factsheets

Background/Question/Methods: There is a growing need to incorporate and prioritize ecosystem services/condition information into land-use decision making. While there are a number of place-based studies looking at how land-use decisions affect the availability and delivery of coastal services, many of these methods require data, funding and/or expertise that may be inaccessible to many coastal communities. Using existing classification standards for beneficiaries and coastal habitats, (i.e., Final Ecosystem Goods and Services Classification System (FEGS-CS) and Coastal and Marine Ecological Classification Standard (CMECS)), a comprehensive literature review was coupled with a “weight of evidence” approach to evaluate linkages between beneficiaries and coastal habitat features most relevant to community needs. An initial search of peer-reviewed journal articles was conducted using JSTOR and ScienceDirect repositories identifying sources that provide evidence for coastal beneficiary:habitat linkages. Potential sources were further refined based on a double-blind review of titles, abstracts, and full-texts, when needed. Articles in the final list were then scored based on habitat/beneficiary specificity and data quality (e.g., indirect evidence from literature reviews was scored lower than direct evidence from case studies with valuation results). Scores were then incorporated into a weight of evidence framework summarizing the support for each benefici

Muscle Injuries: A Brief Guide to Classification and Management

PubMed Central

Maffulli, Nicola; Del Buono, Angelo; Oliva, Francesco; Giai Via, Alessio; Frizziero, Antonio; Barazzuol, Michele; Brancaccio, Paola; Freschi, Marco; Galletti, Stefano; Lisitano, Gianfranco; Melegati, Gianluca; Nanni, Gianni; Pasta, Ghito; Ramponi, Carlo; Rizzo, Diego; Testa, Vittorino; Valent, Alessandro

2015-01-01

Muscle injuries are frequent in athletes. Despite their high incidence, advances in clinical diagnostic criteria and imaging, their optimal management and rehabilitation strategies are still debated in literature. Furthermore, reinjury rate is high after a muscle lesion, and an improper treatment or an early return to sports can increase the rate of reinjury and complications. Most muscle injuries are managed conservatively with excellent results, and surgery is normally advocated only for larger tears. This article reviews the current literature to provide physicians and rehabilitation specialists with the necessary basic tools to diagnose, classify and to treat muscle injuries. Based on anatomy, biomechanics, and imaging features of muscle injury, the use of a recently reported new classification system is also advocated. PMID:26535183

Analysis of DSN software anomalies

NASA Technical Reports Server (NTRS)

Galorath, D. D.; Hecht, H.; Hecht, M.; Reifer, D. J.

1981-01-01

A categorized data base of software errors which were discovered during the various stages of development and operational use of the Deep Space Network DSN/Mark 3 System was developed. A study team identified several existing error classification schemes (taxonomies), prepared a detailed annotated bibliography of the error taxonomy literature, and produced a new classification scheme which was tuned to the DSN anomaly reporting system and encapsulated the work of others. Based upon the DSN/RCI error taxonomy, error data on approximately 1000 reported DSN/Mark 3 anomalies were analyzed, interpreted and classified. Next, error data are summarized and histograms were produced highlighting key tendencies.

Accurate crop classification using hierarchical genetic fuzzy rule-based systems

NASA Astrophysics Data System (ADS)

Topaloglou, Charalampos A.; Mylonas, Stelios K.; Stavrakoudis, Dimitris G.; Mastorocostas, Paris A.; Theocharis, John B.

2014-10-01

This paper investigates the effectiveness of an advanced classification system for accurate crop classification using very high resolution (VHR) satellite imagery. Specifically, a recently proposed genetic fuzzy rule-based classification system (GFRBCS) is employed, namely, the Hierarchical Rule-based Linguistic Classifier (HiRLiC). HiRLiC's model comprises a small set of simple IF-THEN fuzzy rules, easily interpretable by humans. One of its most important attributes is that its learning algorithm requires minimum user interaction, since the most important learning parameters affecting the classification accuracy are determined by the learning algorithm automatically. HiRLiC is applied in a challenging crop classification task, using a SPOT5 satellite image over an intensively cultivated area in a lake-wetland ecosystem in northern Greece. A rich set of higher-order spectral and textural features is derived from the initial bands of the (pan-sharpened) image, resulting in an input space comprising 119 features. The experimental analysis proves that HiRLiC compares favorably to other interpretable classifiers of the literature, both in terms of structural complexity and classification accuracy. Its testing accuracy was very close to that obtained by complex state-of-the-art classification systems, such as the support vector machines (SVM) and random forest (RF) classifiers. Nevertheless, visual inspection of the derived classification maps shows that HiRLiC is characterized by higher generalization properties, providing more homogeneous classifications that the competitors. Moreover, the runtime requirements for producing the thematic map was orders of magnitude lower than the respective for the competitors.

Fractures of the cervical spine

PubMed Central

Marcon, Raphael Martus; Cristante, Alexandre Fogaça; Teixeira, William Jacobsen; Narasaki, Douglas Kenji; Oliveira, Reginaldo Perilo; de Barros Filho, Tarcísio Eloy Pessoa

2013-01-01

OBJECTIVES: The aim of this study was to review the literature on cervical spine fractures. METHODS: The literature on the diagnosis, classification, and treatment of lower and upper cervical fractures and dislocations was reviewed. RESULTS: Fractures of the cervical spine may be present in polytraumatized patients and should be suspected in patients complaining of neck pain. These fractures are more common in men approximately 30 years of age and are most often caused by automobile accidents. The cervical spine is divided into the upper cervical spine (occiput-C2) and the lower cervical spine (C3-C7), according to anatomical differences. Fractures in the upper cervical spine include fractures of the occipital condyle and the atlas, atlanto-axial dislocations, fractures of the odontoid process, and hangman's fractures in the C2 segment. These fractures are characterized based on specific classifications. In the lower cervical spine, fractures follow the same pattern as in other segments of the spine; currently, the most widely used classification is the SLIC (Subaxial Injury Classification), which predicts the prognosis of an injury based on morphology, the integrity of the disc-ligamentous complex, and the patient's neurological status. It is important to correctly classify the fracture to ensure appropriate treatment. Nerve or spinal cord injuries, pseudarthrosis or malunion, and postoperative infection are the main complications of cervical spine fractures. CONCLUSIONS: Fractures of the cervical spine are potentially serious and devastating if not properly treated. Achieving the correct diagnosis and classification of a lesion is the first step toward identifying the most appropriate treatment, which can be either surgical or conservative. PMID:24270959

A Novel Segment-Based Approach for Improving Classification Performance of Transport Mode Detection.

PubMed

Guvensan, M Amac; Dusun, Burak; Can, Baris; Turkmen, H Irem

2017-12-30

Transportation planning and solutions have an enormous impact on city life. To minimize the transport duration, urban planners should understand and elaborate the mobility of a city. Thus, researchers look toward monitoring people's daily activities including transportation types and duration by taking advantage of individual's smartphones. This paper introduces a novel segment-based transport mode detection architecture in order to improve the results of traditional classification algorithms in the literature. The proposed post-processing algorithm, namely the Healing algorithm, aims to correct the misclassification results of machine learning-based solutions. Our real-life test results show that the Healing algorithm could achieve up to 40% improvement of the classification results. As a result, the implemented mobile application could predict eight classes including stationary, walking, car, bus, tram, train, metro and ferry with a success rate of 95% thanks to the proposed multi-tier architecture and Healing algorithm.

Development of a definition, classification system, and model for cultural geology

NASA Astrophysics Data System (ADS)

Mitchell, Lloyd W., III

The concept for this study is based upon a personal interest by the author, an American Indian, in promoting cultural perspectives in undergraduate college teaching and learning environments. Most academicians recognize that merged fields can enhance undergraduate curricula. However, conflict may occur when instructors attempt to merge social science fields such as history or philosophy with geoscience fields such as mining and geomorphology. For example, ideologies of Earth structures derived from scientific methodologies may conflict with historical and spiritual understandings of Earth structures held by American Indians. Specifically, this study addresses the problem of how to combine cultural studies with the geosciences into a new merged academic discipline called cultural geology. This study further attempts to develop the merged field of cultural geology using an approach consisting of three research foci: a definition, a classification system, and a model. Literature reviews were conducted for all three foci. Additionally, to better understand merged fields, a literature review was conducted specifically for academic fields that merged social and physical sciences. Methodologies concentrated on the three research foci: definition, classification system, and model. The definition was derived via a two-step process. The first step, developing keyword hierarchical ranking structures, was followed by creating and analyzing semantic word meaning lists. The classification system was developed by reviewing 102 classification systems and incorporating selected components into a system framework. The cultural geology model was created also utilizing a two-step process. A literature review of scientific models was conducted. Then, the definition and classification system were incorporated into a model felt to reflect the realm of cultural geology. A course syllabus was then developed that incorporated the resulting definition, classification system, and model. This study concludes that cultural geology can be introduced as a merged discipline by using a three-foci framework consisting of a definition, classification system, and model. Additionally, this study reveals that cultural beliefs, attitudes, and behaviors, can be incorporated into a geology course during the curriculum development process, using an approach known as 'learner-centered'. This study further concludes that cultural beliefs, derived from class members, are an important source of curriculum materials.

Review of the literature on benzene exposure and leukemia subtypes.

PubMed

Schnatter, A Robert; Rosamilia, Kim; Wojcik, Nancy C

2005-05-30

The epidemiologic literature on benzene exposure and leukemia in the MEDLINE and TOXNET databases was examined through October 2004 using the keywords "benzene", "leukemia" and "adverse health effects". This search was complemented by reviewing the reference lists from extant literature reviews and criteria documents on benzene. Published studies were characterized according to the type of industry studied and design, exposure assessment, disease classification, and control for confounding variables. Study design consisted of either cohort studies or case-control studies, which were further categorized into population-based and nested case-control studies. Disease classification considered the source of diagnostic information, whether there was clinical confirmation from medical records or histopathological, morphological and/or cytogenetic reviews, and as to whether the International Classification of Diseases (ICD) or the French-American-British (FAB) schemes were used (no studies used the Revised European-American Lymphoma (REAL) classification scheme). Nine cohort and 13 case-control studies met inclusion criteria for this review. High and significant acute myeloid leukemia risks with positive dose response relationships were identified across study designs, particularly in the "well-conducted" cohort studies and especially in more highly exposed workers in rubber, shoe, and paint industries. Risks for chronic lymphocytic leukemia (CLL) tended to show elevations in nested case-control studies, with possible dose response relationships in at least two of the three studies. However, cohort studies on CLL show no such risks. Data for chronic myeloid leukemia and acute lymphocytic leukemia are sparse and inconclusive.

Classification of complex networks based on similarity of topological network features

NASA Astrophysics Data System (ADS)

Attar, Niousha; Aliakbary, Sadegh

2017-09-01

Over the past few decades, networks have been widely used to model real-world phenomena. Real-world networks exhibit nontrivial topological characteristics and therefore, many network models are proposed in the literature for generating graphs that are similar to real networks. Network models reproduce nontrivial properties such as long-tail degree distributions or high clustering coefficients. In this context, we encounter the problem of selecting the network model that best fits a given real-world network. The need for a model selection method reveals the network classification problem, in which a target-network is classified into one of the candidate network models. In this paper, we propose a novel network classification method which is independent of the network size and employs an alignment-free metric of network comparison. The proposed method is based on supervised machine learning algorithms and utilizes the topological similarities of networks for the classification task. The experiments show that the proposed method outperforms state-of-the-art methods with respect to classification accuracy, time efficiency, and robustness to noise.

Intelligent condition monitoring method for bearing faults from highly compressed measurements using sparse over-complete features

NASA Astrophysics Data System (ADS)

Ahmed, H. O. A.; Wong, M. L. D.; Nandi, A. K.

2018-01-01

Condition classification of rolling element bearings in rotating machines is important to prevent the breakdown of industrial machinery. A considerable amount of literature has been published on bearing faults classification. These studies aim to determine automatically the current status of a roller element bearing. Of these studies, methods based on compressed sensing (CS) have received some attention recently due to their ability to allow one to sample below the Nyquist sampling rate. This technology has many possible uses in machine condition monitoring and has been investigated as a possible approach for fault detection and classification in the compressed domain, i.e., without reconstructing the original signal. However, previous CS based methods have been found to be too weak for highly compressed data. The present paper explores computationally, for the first time, the effects of sparse autoencoder based over-complete sparse representations on the classification performance of highly compressed measurements of bearing vibration signals. For this study, the CS method was used to produce highly compressed measurements of the original bearing dataset. Then, an effective deep neural network (DNN) with unsupervised feature learning algorithm based on sparse autoencoder is used for learning over-complete sparse representations of these compressed datasets. Finally, the fault classification is achieved using two stages, namely, pre-training classification based on stacked autoencoder and softmax regression layer form the deep net stage (the first stage), and re-training classification based on backpropagation (BP) algorithm forms the fine-tuning stage (the second stage). The experimental results show that the proposed method is able to achieve high levels of accuracy even with extremely compressed measurements compared with the existing techniques.

A History of Cluster Analysis Using the Classification Society's Bibliography Over Four Decades

NASA Astrophysics Data System (ADS)

Murtagh, Fionn; Kurtz, Michael J.

2016-04-01

The Classification Literature Automated Search Service, an annual bibliography based on citation of one or more of a set of around 80 book or journal publications, ran from 1972 to 2012. We analyze here the years 1994 to 2011. The Classification Society's Service, as it was termed, has been produced by the Classification Society. In earlier decades it was distributed as a diskette or CD with the Journal of Classification. Among our findings are the following: an enormous increase in scholarly production post approximately 2000; a very major increase in quantity, coupled with work in different disciplines, from approximately 2004; and a major shift also from cluster analysis in earlier times having mathematics and psychology as disciplines of the journals published in, and affiliations of authors, contrasted with, in more recent times, a "centre of gravity" in management and engineering.

Automatic adventitious respiratory sound analysis: A systematic review.

PubMed

Pramono, Renard Xaviero Adhi; Bowyer, Stuart; Rodriguez-Villegas, Esther

2017-01-01

Automatic detection or classification of adventitious sounds is useful to assist physicians in diagnosing or monitoring diseases such as asthma, Chronic Obstructive Pulmonary Disease (COPD), and pneumonia. While computerised respiratory sound analysis, specifically for the detection or classification of adventitious sounds, has recently been the focus of an increasing number of studies, a standardised approach and comparison has not been well established. To provide a review of existing algorithms for the detection or classification of adventitious respiratory sounds. This systematic review provides a complete summary of methods used in the literature to give a baseline for future works. A systematic review of English articles published between 1938 and 2016, searched using the Scopus (1938-2016) and IEEExplore (1984-2016) databases. Additional articles were further obtained by references listed in the articles found. Search terms included adventitious sound detection, adventitious sound classification, abnormal respiratory sound detection, abnormal respiratory sound classification, wheeze detection, wheeze classification, crackle detection, crackle classification, rhonchi detection, rhonchi classification, stridor detection, stridor classification, pleural rub detection, pleural rub classification, squawk detection, and squawk classification. Only articles were included that focused on adventitious sound detection or classification, based on respiratory sounds, with performance reported and sufficient information provided to be approximately repeated. Investigators extracted data about the adventitious sound type analysed, approach and level of analysis, instrumentation or data source, location of sensor, amount of data obtained, data management, features, methods, and performance achieved. A total of 77 reports from the literature were included in this review. 55 (71.43%) of the studies focused on wheeze, 40 (51.95%) on crackle, 9 (11.69%) on stridor, 9 (11.69%) on rhonchi, and 18 (23.38%) on other sounds such as pleural rub, squawk, as well as the pathology. Instrumentation used to collect data included microphones, stethoscopes, and accelerometers. Several references obtained data from online repositories or book audio CD companions. Detection or classification methods used varied from empirically determined thresholds to more complex machine learning techniques. Performance reported in the surveyed works were converted to accuracy measures for data synthesis. Direct comparison of the performance of surveyed works cannot be performed as the input data used by each was different. A standard validation method has not been established, resulting in different works using different methods and performance measure definitions. A review of the literature was performed to summarise different analysis approaches, features, and methods used for the analysis. The performance of recent studies showed a high agreement with conventional non-automatic identification. This suggests that automated adventitious sound detection or classification is a promising solution to overcome the limitations of conventional auscultation and to assist in the monitoring of relevant diseases.

Automatic adventitious respiratory sound analysis: A systematic review

PubMed Central

Bowyer, Stuart; Rodriguez-Villegas, Esther

2017-01-01

Background Automatic detection or classification of adventitious sounds is useful to assist physicians in diagnosing or monitoring diseases such as asthma, Chronic Obstructive Pulmonary Disease (COPD), and pneumonia. While computerised respiratory sound analysis, specifically for the detection or classification of adventitious sounds, has recently been the focus of an increasing number of studies, a standardised approach and comparison has not been well established. Objective To provide a review of existing algorithms for the detection or classification of adventitious respiratory sounds. This systematic review provides a complete summary of methods used in the literature to give a baseline for future works. Data sources A systematic review of English articles published between 1938 and 2016, searched using the Scopus (1938-2016) and IEEExplore (1984-2016) databases. Additional articles were further obtained by references listed in the articles found. Search terms included adventitious sound detection, adventitious sound classification, abnormal respiratory sound detection, abnormal respiratory sound classification, wheeze detection, wheeze classification, crackle detection, crackle classification, rhonchi detection, rhonchi classification, stridor detection, stridor classification, pleural rub detection, pleural rub classification, squawk detection, and squawk classification. Study selection Only articles were included that focused on adventitious sound detection or classification, based on respiratory sounds, with performance reported and sufficient information provided to be approximately repeated. Data extraction Investigators extracted data about the adventitious sound type analysed, approach and level of analysis, instrumentation or data source, location of sensor, amount of data obtained, data management, features, methods, and performance achieved. Data synthesis A total of 77 reports from the literature were included in this review. 55 (71.43%) of the studies focused on wheeze, 40 (51.95%) on crackle, 9 (11.69%) on stridor, 9 (11.69%) on rhonchi, and 18 (23.38%) on other sounds such as pleural rub, squawk, as well as the pathology. Instrumentation used to collect data included microphones, stethoscopes, and accelerometers. Several references obtained data from online repositories or book audio CD companions. Detection or classification methods used varied from empirically determined thresholds to more complex machine learning techniques. Performance reported in the surveyed works were converted to accuracy measures for data synthesis. Limitations Direct comparison of the performance of surveyed works cannot be performed as the input data used by each was different. A standard validation method has not been established, resulting in different works using different methods and performance measure definitions. Conclusion A review of the literature was performed to summarise different analysis approaches, features, and methods used for the analysis. The performance of recent studies showed a high agreement with conventional non-automatic identification. This suggests that automated adventitious sound detection or classification is a promising solution to overcome the limitations of conventional auscultation and to assist in the monitoring of relevant diseases. PMID:28552969

A Review on Human Activity Recognition Using Vision-Based Method.

PubMed

Zhang, Shugang; Wei, Zhiqiang; Nie, Jie; Huang, Lei; Wang, Shuang; Li, Zhen

2017-01-01

Human activity recognition (HAR) aims to recognize activities from a series of observations on the actions of subjects and the environmental conditions. The vision-based HAR research is the basis of many applications including video surveillance, health care, and human-computer interaction (HCI). This review highlights the advances of state-of-the-art activity recognition approaches, especially for the activity representation and classification methods. For the representation methods, we sort out a chronological research trajectory from global representations to local representations, and recent depth-based representations. For the classification methods, we conform to the categorization of template-based methods, discriminative models, and generative models and review several prevalent methods. Next, representative and available datasets are introduced. Aiming to provide an overview of those methods and a convenient way of comparing them, we classify existing literatures with a detailed taxonomy including representation and classification methods, as well as the datasets they used. Finally, we investigate the directions for future research.

A Review on Human Activity Recognition Using Vision-Based Method

PubMed Central

Nie, Jie

2017-01-01

Human activity recognition (HAR) aims to recognize activities from a series of observations on the actions of subjects and the environmental conditions. The vision-based HAR research is the basis of many applications including video surveillance, health care, and human-computer interaction (HCI). This review highlights the advances of state-of-the-art activity recognition approaches, especially for the activity representation and classification methods. For the representation methods, we sort out a chronological research trajectory from global representations to local representations, and recent depth-based representations. For the classification methods, we conform to the categorization of template-based methods, discriminative models, and generative models and review several prevalent methods. Next, representative and available datasets are introduced. Aiming to provide an overview of those methods and a convenient way of comparing them, we classify existing literatures with a detailed taxonomy including representation and classification methods, as well as the datasets they used. Finally, we investigate the directions for future research. PMID:29065585

Fascia: a morphological description and classification system based on a literature review

PubMed Central

Kumka, Myroslava; Bonar, Jason

2012-01-01

Fascia is virtually inseparable from all structures in the body and acts to create continuity amongst tissues to enhance function and support. In the past fascia has been difficult to study leading to ambiguities in nomenclature, which have only recently been addressed. Through review of the available literature, advances in fascia research were compiled, and issues related to terminology, descriptions, and clinical relevance of fascia were addressed. Our multimodal search strategy was conducted in Medline and PubMed databases, with other targeted searches in Google Scholar and by hand, utilizing reference lists and conference proceedings. In an effort to organize nomenclature for fascial structures provided by the Federative International Committee on Anatomical Terminology (FICAT), we developed a functional classification system which includes four categories of fascia: i) linking, ii) fascicular, iii) compression, and iv) separating fasciae. Each category was developed from descriptions in the literature on gross anatomy, histology, and biomechanics; the category names reflect the function of the fascia. An up-to-date definition of fascia is provided, as well as descriptions of its function and clinical features. Our classification demonstrates the use of internationally accepted terminology in an ontology which can improve understanding of major terms in each category of fascia. PMID:22997468

Clinical research data warehouse governance for distributed research networks in the USA: a systematic review of the literature

PubMed Central

Holmes, John H; Elliott, Thomas E; Brown, Jeffrey S; Raebel, Marsha A; Davidson, Arthur; Nelson, Andrew F; Chung, Annie; La Chance, Pierre; Steiner, John F

2014-01-01

Objective To review the published, peer-reviewed literature on clinical research data warehouse governance in distributed research networks (DRNs). Materials and methods Medline, PubMed, EMBASE, CINAHL, and INSPEC were searched for relevant documents published through July 31, 2013 using a systematic approach. Only documents relating to DRNs in the USA were included. Documents were analyzed using a classification framework consisting of 10 facets to identify themes. Results 6641 documents were retrieved. After screening for duplicates and relevance, 38 were included in the final review. A peer-reviewed literature on data warehouse governance is emerging, but is still sparse. Peer-reviewed publications on UK research network governance were more prevalent, although not reviewed for this analysis. All 10 classification facets were used, with some documents falling into two or more classifications. No document addressed costs associated with governance. Discussion Even though DRNs are emerging as vehicles for research and public health surveillance, understanding of DRN data governance policies and procedures is limited. This is expected to change as more DRN projects disseminate their governance approaches as publicly available toolkits and peer-reviewed publications. Conclusions While peer-reviewed, US-based DRN data warehouse governance publications have increased, DRN developers and administrators are encouraged to publish information about these programs. PMID:24682495

An approach for classification of hydrogeological systems at the regional scale based on groundwater hydrographs

NASA Astrophysics Data System (ADS)

Haaf, Ezra; Barthel, Roland

2016-04-01

When assessing hydrogeological conditions at the regional scale, the analyst is often confronted with uncertainty of structures, inputs and processes while having to base inference on scarce and patchy data. Haaf and Barthel (2015) proposed a concept for handling this predicament by developing a groundwater systems classification framework, where information is transferred from similar, but well-explored and better understood to poorly described systems. The concept is based on the central hypothesis that similar systems react similarly to the same inputs and vice versa. It is conceptually related to PUB (Prediction in ungauged basins) where organization of systems and processes by quantitative methods is intended and used to improve understanding and prediction. Furthermore, using the framework it is expected that regional conceptual and numerical models can be checked or enriched by ensemble generated data from neighborhood-based estimators. In a first step, groundwater hydrographs from a large dataset in Southern Germany are compared in an effort to identify structural similarity in groundwater dynamics. A number of approaches to group hydrographs, mostly based on a similarity measure - which have previously only been used in local-scale studies, can be found in the literature. These are tested alongside different global feature extraction techniques. The resulting classifications are then compared to a visual "expert assessment"-based classification which serves as a reference. A ranking of the classification methods is carried out and differences shown. Selected groups from the classifications are related to geological descriptors. Here we present the most promising results from a comparison of classifications based on series correlation, different series distances and series features, such as the coefficients of the discrete Fourier transform and the intrinsic mode functions of empirical mode decomposition. Additionally, we show examples of classes corresponding to geological descriptors. Haaf, E., Barthel, R., 2015. Methods for assessing hydrogeological similarity and for classification of groundwater systems on the regional scale, EGU General Assembly 2015, Vienna, Austria.

Differences in the molecular biology of adenocarcinoma of the esophagus, gastric cardia, and upper gastric third.

PubMed

Lehmann, Kuno; Schneider, Paul M

2010-01-01

Adenocarcinoma of the distal esophagus, gastric cardia, and upper gastric third are grouped in type I-III by the Siewert classification. This classification is based on the endoscopic localisation of the tumor center, and is the most important diagnostic tool to group these tumors. On a molecular level, there is currently no marker that would allow to differentiate the three different types. Furthermore, the Siewert classification was not uniformly used in the recent literature, making interpretation and generalization of these results difficult. However, several potential targets have been identified that may help to separate these tumors by molecular markers, and are summarized in this chapter.

Classification of involuntary movements in dogs: Tremors and twitches.

PubMed

Lowrie, Mark; Garosi, Laurent

2016-08-01

This review focuses on important new findings in the field of involuntary movements (IM) in dogs and illustrates the importance of developing a clear classification tool for diagnosing tremor and twitches. Developments over the last decade have changed our understanding of IM and highlight several caveats in the current tremor classification. Given the ambiguous association between tremor phenomenology and tremor aetiology, a more cautious definition of tremors based on clinical assessment is required. An algorithm for the characterisation of tremors is presented herein. The classification of tremors is based on the distinction between tremors that occur at rest and tremors that are action-related; tremors associated with action are divided into postural or kinetic. Controversial issues are outlined and thus reflect the open questions that are yet to be answered from an evidence base of peer-reviewed published literature. Peripheral nerve hyper-excitability (PNH; cramps and twitches) may manifest as fasciculations, myokymia, neuromyotonia, cramps, tetany and tetanus. It is anticipated that as we learn more about the aetiology and pathogenesis of IMs, future revisions to the classification will be needed. It is therefore the intent of this work to stimulate discussions and thus contribute to the development of IM research. Crown Copyright © 2016. Published by Elsevier Ltd. All rights reserved.

Crisis in Cataloging Revisited: The Year's Work in Subject Analysis, 1990.

ERIC Educational Resources Information Center

Young, James Bradford

1991-01-01

Reviews the 1990 literature that concerns subject analysis. Issues addressed include subject cataloging, including Library of Congress Subject Headings (LCSH); classification, including Dewey Decimal Classification (DDC), Library of Congress Classification, and classification in online systems; subject access, including the online use of…

Instructional Method Classifications Lack User Language and Orientation

ERIC Educational Resources Information Center

Neumann, Susanne; Koper, Rob

2010-01-01

Following publications emphasizing the need of a taxonomy for instructional methods, this article presents a literature review on classifications for learning and teaching in order to identify possible classifications for instructional methods. Data was collected for 37 classifications capturing the origins, theoretical underpinnings, purposes and…

Classification techniques on computerized systems to predict and/or to detect Apnea: A systematic review.

PubMed

Pombo, Nuno; Garcia, Nuno; Bousson, Kouamana

2017-03-01

Sleep apnea syndrome (SAS), which can significantly decrease the quality of life is associated with a major risk factor of health implications such as increased cardiovascular disease, sudden death, depression, irritability, hypertension, and learning difficulties. Thus, it is relevant and timely to present a systematic review describing significant applications in the framework of computational intelligence-based SAS, including its performance, beneficial and challenging effects, and modeling for the decision-making on multiple scenarios. This study aims to systematically review the literature on systems for the detection and/or prediction of apnea events using a classification model. Forty-five included studies revealed a combination of classification techniques for the diagnosis of apnea, such as threshold-based (14.75%) and machine learning (ML) models (85.25%). In addition, the ML models, were clustered in a mind map, include neural networks (44.26%), regression (4.91%), instance-based (11.47%), Bayesian algorithms (1.63%), reinforcement learning (4.91%), dimensionality reduction (8.19%), ensemble learning (6.55%), and decision trees (3.27%). A classification model should provide an auto-adaptive and no external-human action dependency. In addition, the accuracy of the classification models is related with the effective features selection. New high-quality studies based on randomized controlled trials and validation of models using a large and multiple sample of data are recommended. Copyright © 2017 Elsevier Ireland Ltd. All rights reserved.

Hybrid ANN optimized artificial fish swarm algorithm based classifier for classification of suspicious lesions in breast DCE-MRI

NASA Astrophysics Data System (ADS)

Janaki Sathya, D.; Geetha, K.

2017-12-01

Automatic mass or lesion classification systems are developed to aid in distinguishing between malignant and benign lesions present in the breast DCE-MR images, the systems need to improve both the sensitivity and specificity of DCE-MR image interpretation in order to be successful for clinical use. A new classifier (a set of features together with a classification method) based on artificial neural networks trained using artificial fish swarm optimization (AFSO) algorithm is proposed in this paper. The basic idea behind the proposed classifier is to use AFSO algorithm for searching the best combination of synaptic weights for the neural network. An optimal set of features based on the statistical textural features is presented. The investigational outcomes of the proposed suspicious lesion classifier algorithm therefore confirm that the resulting classifier performs better than other such classifiers reported in the literature. Therefore this classifier demonstrates that the improvement in both the sensitivity and specificity are possible through automated image analysis.

The road to 11th edition of the International Classification of Diseases: trajectories of scientific consensus and contested science in the classification of intellectual disability/intellectual developmental disorders.

PubMed

Salvador-Carulla, Luis; Bertelli, Marco; Martinez-Leal, Rafael

2018-03-01

To increase the expert knowledge-base on intellectual developmental disorders (IDDs) by investigating the typology trajectories of consensus formation in the classification systems up to the 11th edition of the International Classification of Diseases (ICD-11). This expert review combines an analysis of key recent literature and the revision of the consensus formation and contestation in the expert committees contributing to the classification systems since the 1950s. Historically two main approaches have contributed to the development of this knowledge-base: a neurodevelopmental-clinical approach and a psychoeducational-social approach. These approaches show a complex interaction throughout the history of IDD and have had a diverse influence on its classification. Although in theory Diagnostic and Statistical Manual (DSM)-5 and ICD adhere to the neurodevelopmental-clinical model, the new definition in the ICD-11 follows a restrictive normality approach to intellectual quotient and to the measurement of adaptive behaviour. On the contrary DSM-5 is closer to the recommendations made by the WHO 'Working Group on Mental Retardation' for ICD-11 for an integrative approach. A cyclical pattern of consensus formation has been identified in IDD. The revision of the three major classification systems in the last decade has increased the terminological and conceptual variability and the overall scientific contestation on IDD.

Evaluating Support for the Current Classification of Eukaryotic Diversity

PubMed Central

Parfrey, Laura Wegener; Barbero, Erika; Lasser, Elyse; Dunthorn, Micah; Bhattacharya, Debashish; Patterson, David J; Katz, Laura A

2006-01-01

Perspectives on the classification of eukaryotic diversity have changed rapidly in recent years, as the four eukaryotic groups within the five-kingdom classification—plants, animals, fungi, and protists—have been transformed through numerous permutations into the current system of six “supergroups.” The intent of the supergroup classification system is to unite microbial and macroscopic eukaryotes based on phylogenetic inference. This supergroup approach is increasing in popularity in the literature and is appearing in introductory biology textbooks. We evaluate the stability and support for the current six-supergroup classification of eukaryotes based on molecular genealogies. We assess three aspects of each supergroup: (1) the stability of its taxonomy, (2) the support for monophyly (single evolutionary origin) in molecular analyses targeting a supergroup, and (3) the support for monophyly when a supergroup is included as an out-group in phylogenetic studies targeting other taxa. Our analysis demonstrates that supergroup taxonomies are unstable and that support for groups varies tremendously, indicating that the current classification scheme of eukaryotes is likely premature. We highlight several trends contributing to the instability and discuss the requirements for establishing robust clades within the eukaryotic tree of life. PMID:17194223

Food Classification Systems Based on Food Processing: Significance and Implications for Policies and Actions: A Systematic Literature Review and Assessment.

PubMed

Moubarac, Jean-Claude; Parra, Diana C; Cannon, Geoffrey; Monteiro, Carlos A

2014-06-01

This paper is the first to make a systematic review and assessment of the literature that attempts methodically to incorporate food processing into classification of diets. The review identified 1276 papers, of which 110 were screened and 21 studied, derived from five classification systems. This paper analyses and assesses the five systems, one of which has been devised and developed by a research team that includes co-authors of this paper. The quality of the five systems is assessed and scored according to how specific, coherent, clear, comprehensive and workable they are. Their relevance to food, nutrition and health, and their use in various settings, is described. The paper shows that the significance of industrial food processing in shaping global food systems and supplies and thus dietary patterns worldwide, and its role in the pandemic of overweight and obesity, remains overlooked and underestimated. Once food processing is systematically incorporated into food classifications, they will be more useful in assessing and monitoring dietary patterns. Food classification systems that emphasize industrial food processing, and that define and distinguish relevant different types of processing, will improve understanding of how to prevent and control overweight, obesity and related chronic non-communicable diseases, and also malnutrition. They will also be a firmer basis for rational policies and effective actions designed to protect and improve public health at all levels from global to local.

Boosted classification trees result in minor to modest improvement in the accuracy in classifying cardiovascular outcomes compared to conventional classification trees

PubMed Central

Austin, Peter C; Lee, Douglas S

2011-01-01

Purpose: Classification trees are increasingly being used to classifying patients according to the presence or absence of a disease or health outcome. A limitation of classification trees is their limited predictive accuracy. In the data-mining and machine learning literature, boosting has been developed to improve classification. Boosting with classification trees iteratively grows classification trees in a sequence of reweighted datasets. In a given iteration, subjects that were misclassified in the previous iteration are weighted more highly than subjects that were correctly classified. Classifications from each of the classification trees in the sequence are combined through a weighted majority vote to produce a final classification. The authors' objective was to examine whether boosting improved the accuracy of classification trees for predicting outcomes in cardiovascular patients. Methods: We examined the utility of boosting classification trees for classifying 30-day mortality outcomes in patients hospitalized with either acute myocardial infarction or congestive heart failure. Results: Improvements in the misclassification rate using boosted classification trees were at best minor compared to when conventional classification trees were used. Minor to modest improvements to sensitivity were observed, with only a negligible reduction in specificity. For predicting cardiovascular mortality, boosted classification trees had high specificity, but low sensitivity. Conclusions: Gains in predictive accuracy for predicting cardiovascular outcomes were less impressive than gains in performance observed in the data mining literature. PMID:22254181

Adipose Tissue Quantification by Imaging Methods: A Proposed Classification

PubMed Central

Shen, Wei; Wang, ZiMian; Punyanita, Mark; Lei, Jianbo; Sinav, Ahmet; Kral, John G.; Imielinska, Celina; Ross, Robert; Heymsfield, Steven B.

2007-01-01

Recent advances in imaging techniques and understanding of differences in the molecular biology of adipose tissue has rendered classical anatomy obsolete, requiring a new classification of the topography of adipose tissue. Adipose tissue is one of the largest body compartments, yet a classification that defines specific adipose tissue depots based on their anatomic location and related functions is lacking. The absence of an accepted taxonomy poses problems for investigators studying adipose tissue topography and its functional correlates. The aim of this review was to critically examine the literature on imaging of whole body and regional adipose tissue and to create the first systematic classification of adipose tissue topography. Adipose tissue terminology was examined in over 100 original publications. Our analysis revealed inconsistencies in the use of specific definitions, especially for the compartment termed “visceral” adipose tissue. This analysis leads us to propose an updated classification of total body and regional adipose tissue, providing a well-defined basis for correlating imaging studies of specific adipose tissue depots with molecular processes. PMID:12529479

Noise tolerant dendritic lattice associative memories

NASA Astrophysics Data System (ADS)

Ritter, Gerhard X.; Schmalz, Mark S.; Hayden, Eric; Tucker, Marc

2011-09-01

Linear classifiers based on computation over the real numbers R (e.g., with operations of addition and multiplication) denoted by (R, +, x), have been represented extensively in the literature of pattern recognition. However, a different approach to pattern classification involves the use of addition, maximum, and minimum operations over the reals in the algebra (R, +, maximum, minimum) These pattern classifiers, based on lattice algebra, have been shown to exhibit superior information storage capacity, fast training and short convergence times, high pattern classification accuracy, and low computational cost. Such attributes are not always found, for example, in classical neural nets based on the linear inner product. In a special type of lattice associative memory (LAM), called a dendritic LAM or DLAM, it is possible to achieve noise-tolerant pattern classification by varying the design of noise or error acceptance bounds. This paper presents theory and algorithmic approaches for the computation of noise-tolerant lattice associative memories (LAMs) under a variety of input constraints. Of particular interest are the classification of nonergodic data in noise regimes with time-varying statistics. DLAMs, which are a specialization of LAMs derived from concepts of biological neural networks, have successfully been applied to pattern classification from hyperspectral remote sensing data, as well as spatial object recognition from digital imagery. The authors' recent research in the development of DLAMs is overviewed, with experimental results that show utility for a wide variety of pattern classification applications. Performance results are presented in terms of measured computational cost, noise tolerance, classification accuracy, and throughput for a variety of input data and noise levels.

Acromioclavicular joint dislocations: radiological correlation between Rockwood classification system and injury patterns in human cadaver species.

PubMed

Eschler, Anica; Rösler, Klaus; Rotter, Robert; Gradl, Georg; Mittlmeier, Thomas; Gierer, Philip

2014-09-01

The classification system of Rockwood and Young is a commonly used classification for acromioclavicular joint separations subdividing types I-VI. This classification hypothesizes specific lesions to anatomical structures (acromioclavicular and coracoclavicular ligaments, capsule, attached muscles) leading to the injury. In recent literature, our understanding for anatomical correlates leading to the radiological-based Rockwood classification is questioned. The goal of this experimental-based investigation was to approve the correlation between the anatomical injury pattern and the Rockwood classification. In four human cadavers (seven shoulders), the acromioclavicular and coracoclavicular ligaments were transected stepwise. Radiological correlates were recorded (Zanca view) with 15-kg longitudinal tension applied at the wrist. The resulting acromio- and coracoclavicular distances were measured. Radiographs after acromioclavicular ligament transection showed joint space enlargement (8.6 ± 0.3 vs. 3.1 ± 0.5 mm, p < 0.05) and no significant change in coracoclavicular distance (10.4 ± 0.9 vs. 10.0 ± 0.8 mm). According to the Rockwood classification only type I and II lesions occurred. After additional coracoclavicular ligament cut, the acromioclavicular joint space width increased to 16.7 ± 2.7 vs. 8.6 ± 0.3 mm, p < 0.05. The mean coracoclavicular distance increased to 20.6 ± 2.1 mm resulting in type III-V lesions concerning the Rockwood classification. Trauma with intact coracoclavicular ligaments did not result in acromioclavicular joint lesions higher than Rockwood type I and II. The clinical consequence for reconstruction of low-grade injuries might be a solely surgical approach for the acromioclavicular ligaments or conservative treatment. High-grade injuries were always based on additional structural damage to the coracoclavicular ligaments. Rockwood type V lesions occurred while muscle attachments were intact.

Juvenile nasopharyngeal angiofibroma staging: An overview.

PubMed

Alshaikh, Nada Ali; Eleftheriadou, Anna

2015-06-01

Staging of tumors is very important in treatment and surgical decision making, as well as in predicting disease recurrence and prognosis. This review focuses on the different available classifications of juvenile nasopharyngeal angiofibroma (JNA) and their impact on the evaluation, management, and prognosis of JNA. The literature was reviewed, and publications on JNA staging were examined. Our MEDLINE search of the entire English-language literature found no review article on the current available staging systems for JNA. In this article, we review the common JNA classification systems that have been published, and we discuss some of their advantages and disadvantages. The most commonly used staging systems for JNA are the Radkowski and the Andrews-Fisch staging systems. However, some newer staging systems that are based on advances in technology and surgical approaches-the Onerci, INCan, and UPMC systems-have shown promising utility, and they will probably gain popularity in the future.

Cascaded deep decision networks for classification of endoscopic images

NASA Astrophysics Data System (ADS)

Murthy, Venkatesh N.; Singh, Vivek; Sun, Shanhui; Bhattacharya, Subhabrata; Chen, Terrence; Comaniciu, Dorin

2017-02-01

Both traditional and wireless capsule endoscopes can generate tens of thousands of images for each patient. It is desirable to have the majority of irrelevant images filtered out by automatic algorithms during an offline review process or to have automatic indication for highly suspicious areas during an online guidance. This also applies to the newly invented endomicroscopy, where online indication of tumor classification plays a significant role. Image classification is a standard pattern recognition problem and is well studied in the literature. However, performance on the challenging endoscopic images still has room for improvement. In this paper, we present a novel Cascaded Deep Decision Network (CDDN) to improve image classification performance over standard Deep neural network based methods. During the learning phase, CDDN automatically builds a network which discards samples that are classified with high confidence scores by a previously trained network and concentrates only on the challenging samples which would be handled by the subsequent expert shallow networks. We validate CDDN using two different types of endoscopic imaging, which includes a polyp classification dataset and a tumor classification dataset. From both datasets we show that CDDN can outperform other methods by about 10%. In addition, CDDN can also be applied to other image classification problems.

Effects of Worker Classification, Crystallization, and Job Autonomy on Congruence-Satisfaction Relationships.

ERIC Educational Resources Information Center

Obermesik, John W.; Beehr, Terry A.

A majority of the congruence-satisfaction literature has used interest measures based on Holland's theory, although the measures' accuracy in predicting job satisfaction is questionable. Divergent findings among studies on occupational congruence-job satisfaction may be due to ineffective measures of congruence and job satisfaction and lack of…

HMMBinder: DNA-Binding Protein Prediction Using HMM Profile Based Features.

PubMed

Zaman, Rianon; Chowdhury, Shahana Yasmin; Rashid, Mahmood A; Sharma, Alok; Dehzangi, Abdollah; Shatabda, Swakkhar

2017-01-01

DNA-binding proteins often play important role in various processes within the cell. Over the last decade, a wide range of classification algorithms and feature extraction techniques have been used to solve this problem. In this paper, we propose a novel DNA-binding protein prediction method called HMMBinder. HMMBinder uses monogram and bigram features extracted from the HMM profiles of the protein sequences. To the best of our knowledge, this is the first application of HMM profile based features for the DNA-binding protein prediction problem. We applied Support Vector Machines (SVM) as a classification technique in HMMBinder. Our method was tested on standard benchmark datasets. We experimentally show that our method outperforms the state-of-the-art methods found in the literature.

Disability, human rights, and the International Classification of Functioning, Disability, and Health: systematic review.

PubMed

Aluas, Maria; Colombetti, Elena; Osimani, Barbara; Musio, Alessio; Pessina, Adriano

2012-02-01

This literature review focuses on the literature on disability from the ethical and human rights perspective in the light of the International Classification of Functioning, Disability, and Health in the period from January 1, 2008, to June 30, 2010. This article identifies and examines studies that deal with the subject of disability with reference to rights, ethical issues, and justice. A total of 42 articles and 33 books were selected. The subject most frequently dealt with in studies on disability is that of human rights (76% of the articles and 79% of the books examined), followed by topics relating to welfare (52% of articles and 64% of books), International Classification of Functioning, Disability, and Health (38% of articles and 45% of books), justice (24% of articles and 48% of books), education (21% of articles and 61% of books), and work (19% of articles and 39% of books). The subject of disability is dealt with in various fields of study and various disciplines. Most of the studies are based on the legal approach. It is to be hoped that there will be an increase in the philosophical and ethical study of disability, which has only recently entered the European debate.

A Novel Feature Selection Technique for Text Classification Using Naïve Bayes.

PubMed

Dey Sarkar, Subhajit; Goswami, Saptarsi; Agarwal, Aman; Aktar, Javed

2014-01-01

With the proliferation of unstructured data, text classification or text categorization has found many applications in topic classification, sentiment analysis, authorship identification, spam detection, and so on. There are many classification algorithms available. Naïve Bayes remains one of the oldest and most popular classifiers. On one hand, implementation of naïve Bayes is simple and, on the other hand, this also requires fewer amounts of training data. From the literature review, it is found that naïve Bayes performs poorly compared to other classifiers in text classification. As a result, this makes the naïve Bayes classifier unusable in spite of the simplicity and intuitiveness of the model. In this paper, we propose a two-step feature selection method based on firstly a univariate feature selection and then feature clustering, where we use the univariate feature selection method to reduce the search space and then apply clustering to select relatively independent feature sets. We demonstrate the effectiveness of our method by a thorough evaluation and comparison over 13 datasets. The performance improvement thus achieved makes naïve Bayes comparable or superior to other classifiers. The proposed algorithm is shown to outperform other traditional methods like greedy search based wrapper or CFS.

User-customized brain computer interfaces using Bayesian optimization

NASA Astrophysics Data System (ADS)

Bashashati, Hossein; Ward, Rabab K.; Bashashati, Ali

2016-04-01

Objective. The brain characteristics of different people are not the same. Brain computer interfaces (BCIs) should thus be customized for each individual person. In motor-imagery based synchronous BCIs, a number of parameters (referred to as hyper-parameters) including the EEG frequency bands, the channels and the time intervals from which the features are extracted should be pre-determined based on each subject’s brain characteristics. Approach. To determine the hyper-parameter values, previous work has relied on manual or semi-automatic methods that are not applicable to high-dimensional search spaces. In this paper, we propose a fully automatic, scalable and computationally inexpensive algorithm that uses Bayesian optimization to tune these hyper-parameters. We then build different classifiers trained on the sets of hyper-parameter values proposed by the Bayesian optimization. A final classifier aggregates the results of the different classifiers. Main Results. We have applied our method to 21 subjects from three BCI competition datasets. We have conducted rigorous statistical tests, and have shown the positive impact of hyper-parameter optimization in improving the accuracy of BCIs. Furthermore, We have compared our results to those reported in the literature. Significance. Unlike the best reported results in the literature, which are based on more sophisticated feature extraction and classification methods, and rely on prestudies to determine the hyper-parameter values, our method has the advantage of being fully automated, uses less sophisticated feature extraction and classification methods, and yields similar or superior results compared to the best performing designs in the literature.

A review of classification algorithms for EEG-based brain–computer interfaces: a 10 year update

NASA Astrophysics Data System (ADS)

Lotte, F.; Bougrain, L.; Cichocki, A.; Clerc, M.; Congedo, M.; Rakotomamonjy, A.; Yger, F.

2018-06-01

Objective. Most current electroencephalography (EEG)-based brain–computer interfaces (BCIs) are based on machine learning algorithms. There is a large diversity of classifier types that are used in this field, as described in our 2007 review paper. Now, approximately ten years after this review publication, many new algorithms have been developed and tested to classify EEG signals in BCIs. The time is therefore ripe for an updated review of EEG classification algorithms for BCIs. Approach. We surveyed the BCI and machine learning literature from 2007 to 2017 to identify the new classification approaches that have been investigated to design BCIs. We synthesize these studies in order to present such algorithms, to report how they were used for BCIs, what were the outcomes, and to identify their pros and cons. Main results. We found that the recently designed classification algorithms for EEG-based BCIs can be divided into four main categories: adaptive classifiers, matrix and tensor classifiers, transfer learning and deep learning, plus a few other miscellaneous classifiers. Among these, adaptive classifiers were demonstrated to be generally superior to static ones, even with unsupervised adaptation. Transfer learning can also prove useful although the benefits of transfer learning remain unpredictable. Riemannian geometry-based methods have reached state-of-the-art performances on multiple BCI problems and deserve to be explored more thoroughly, along with tensor-based methods. Shrinkage linear discriminant analysis and random forests also appear particularly useful for small training samples settings. On the other hand, deep learning methods have not yet shown convincing improvement over state-of-the-art BCI methods. Significance. This paper provides a comprehensive overview of the modern classification algorithms used in EEG-based BCIs, presents the principles of these methods and guidelines on when and how to use them. It also identifies a number of challenges to further advance EEG classification in BCI.

Automatic plankton image classification combining multiple view features via multiple kernel learning.

PubMed

Zheng, Haiyong; Wang, Ruchen; Yu, Zhibin; Wang, Nan; Gu, Zhaorui; Zheng, Bing

2017-12-28

Plankton, including phytoplankton and zooplankton, are the main source of food for organisms in the ocean and form the base of marine food chain. As the fundamental components of marine ecosystems, plankton is very sensitive to environment changes, and the study of plankton abundance and distribution is crucial, in order to understand environment changes and protect marine ecosystems. This study was carried out to develop an extensive applicable plankton classification system with high accuracy for the increasing number of various imaging devices. Literature shows that most plankton image classification systems were limited to only one specific imaging device and a relatively narrow taxonomic scope. The real practical system for automatic plankton classification is even non-existent and this study is partly to fill this gap. Inspired by the analysis of literature and development of technology, we focused on the requirements of practical application and proposed an automatic system for plankton image classification combining multiple view features via multiple kernel learning (MKL). For one thing, in order to describe the biomorphic characteristics of plankton more completely and comprehensively, we combined general features with robust features, especially by adding features like Inner-Distance Shape Context for morphological representation. For another, we divided all the features into different types from multiple views and feed them to multiple classifiers instead of only one by combining different kernel matrices computed from different types of features optimally via multiple kernel learning. Moreover, we also applied feature selection method to choose the optimal feature subsets from redundant features for satisfying different datasets from different imaging devices. We implemented our proposed classification system on three different datasets across more than 20 categories from phytoplankton to zooplankton. The experimental results validated that our system outperforms state-of-the-art plankton image classification systems in terms of accuracy and robustness. This study demonstrated automatic plankton image classification system combining multiple view features using multiple kernel learning. The results indicated that multiple view features combined by NLMKL using three kernel functions (linear, polynomial and Gaussian kernel functions) can describe and use information of features better so that achieve a higher classification accuracy.

A systematic literature review of automated clinical coding and classification systems

PubMed Central

Williams, Margaret; Fenton, Susan H; Jenders, Robert A; Hersh, William R

2010-01-01

Clinical coding and classification processes transform natural language descriptions in clinical text into data that can subsequently be used for clinical care, research, and other purposes. This systematic literature review examined studies that evaluated all types of automated coding and classification systems to determine the performance of such systems. Studies indexed in Medline or other relevant databases prior to March 2009 were considered. The 113 studies included in this review show that automated tools exist for a variety of coding and classification purposes, focus on various healthcare specialties, and handle a wide variety of clinical document types. Automated coding and classification systems themselves are not generalizable, nor are the results of the studies evaluating them. Published research shows these systems hold promise, but these data must be considered in context, with performance relative to the complexity of the task and the desired outcome. PMID:20962126

A systematic literature review of automated clinical coding and classification systems.

PubMed

Stanfill, Mary H; Williams, Margaret; Fenton, Susan H; Jenders, Robert A; Hersh, William R

2010-01-01

Clinical coding and classification processes transform natural language descriptions in clinical text into data that can subsequently be used for clinical care, research, and other purposes. This systematic literature review examined studies that evaluated all types of automated coding and classification systems to determine the performance of such systems. Studies indexed in Medline or other relevant databases prior to March 2009 were considered. The 113 studies included in this review show that automated tools exist for a variety of coding and classification purposes, focus on various healthcare specialties, and handle a wide variety of clinical document types. Automated coding and classification systems themselves are not generalizable, nor are the results of the studies evaluating them. Published research shows these systems hold promise, but these data must be considered in context, with performance relative to the complexity of the task and the desired outcome.

Classification, prevention and management of entero-atmospheric fistula: a state-of-the-art review.

PubMed

Di Saverio, Salomone; Tarasconi, Antonio; Walczak, Dominik A; Cirocchi, Roberto; Mandrioli, Matteo; Birindelli, Arianna; Tugnoli, Gregorio

2016-02-01

Entero-atmospheric fistula (EAF) is an enteric fistula occurring in the setting of an open abdomen, thus creating a communication between the GI tract and the external atmosphere. Management and nursing of patients suffering EAF carries several challenges, and prevention of EAF should be the first and best treatment option. Here, we present a novel modified classification of EAF and review the current state of the art in its prevention and management including nutritional issues and feeding strategies. We also provide an overview on surgical management principles, highlighting several surgical techniques for dealing with EAF that have been reported in the literature throughout the years. The treatment strategy for EAF should be multidisciplinary and multifaceted. Surgical treatment is most often multistep and should be tailored to the single patient, based on the type and characteristics of the EAF, following its correct identification and classification. The specific experience of surgeons and nursing staff in the management of EAF could be enhanced, applying distinct simulation-based ex vivo training models.

Clinical research data warehouse governance for distributed research networks in the USA: a systematic review of the literature.

PubMed

Holmes, John H; Elliott, Thomas E; Brown, Jeffrey S; Raebel, Marsha A; Davidson, Arthur; Nelson, Andrew F; Chung, Annie; La Chance, Pierre; Steiner, John F

2014-01-01

To review the published, peer-reviewed literature on clinical research data warehouse governance in distributed research networks (DRNs). Medline, PubMed, EMBASE, CINAHL, and INSPEC were searched for relevant documents published through July 31, 2013 using a systematic approach. Only documents relating to DRNs in the USA were included. Documents were analyzed using a classification framework consisting of 10 facets to identify themes. 6641 documents were retrieved. After screening for duplicates and relevance, 38 were included in the final review. A peer-reviewed literature on data warehouse governance is emerging, but is still sparse. Peer-reviewed publications on UK research network governance were more prevalent, although not reviewed for this analysis. All 10 classification facets were used, with some documents falling into two or more classifications. No document addressed costs associated with governance. Even though DRNs are emerging as vehicles for research and public health surveillance, understanding of DRN data governance policies and procedures is limited. This is expected to change as more DRN projects disseminate their governance approaches as publicly available toolkits and peer-reviewed publications. While peer-reviewed, US-based DRN data warehouse governance publications have increased, DRN developers and administrators are encouraged to publish information about these programs. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

A review of the automated detection and classification of acute leukaemia: Coherent taxonomy, datasets, validation and performance measurements, motivation, open challenges and recommendations.

PubMed

Alsalem, M A; Zaidan, A A; Zaidan, B B; Hashim, M; Madhloom, H T; Azeez, N D; Alsyisuf, S

2018-05-01

Acute leukaemia diagnosis is a field requiring automated solutions, tools and methods and the ability to facilitate early detection and even prediction. Many studies have focused on the automatic detection and classification of acute leukaemia and their subtypes to promote enable highly accurate diagnosis. This study aimed to review and analyse literature related to the detection and classification of acute leukaemia. The factors that were considered to improve understanding on the field's various contextual aspects in published studies and characteristics were motivation, open challenges that confronted researchers and recommendations presented to researchers to enhance this vital research area. We systematically searched all articles about the classification and detection of acute leukaemia, as well as their evaluation and benchmarking, in three main databases: ScienceDirect, Web of Science and IEEE Xplore from 2007 to 2017. These indices were considered to be sufficiently extensive to encompass our field of literature. Based on our inclusion and exclusion criteria, 89 articles were selected. Most studies (58/89) focused on the methods or algorithms of acute leukaemia classification, a number of papers (22/89) covered the developed systems for the detection or diagnosis of acute leukaemia and few papers (5/89) presented evaluation and comparative studies. The smallest portion (4/89) of articles comprised reviews and surveys. Acute leukaemia diagnosis, which is a field requiring automated solutions, tools and methods, entails the ability to facilitate early detection or even prediction. Many studies have been performed on the automatic detection and classification of acute leukaemia and their subtypes to promote accurate diagnosis. Research areas on medical-image classification vary, but they are all equally vital. We expect this systematic review to help emphasise current research opportunities and thus extend and create additional research fields. Copyright © 2018 Elsevier B.V. All rights reserved.

Inter-sectoral costs and benefits of mental health prevention: towards a new classification scheme.

PubMed

Drost, Ruben M W A; Paulus, Aggie T G; Ruwaard, Dirk; Evers, Silvia M A A

2013-12-01

Many preventive interventions for mental disorders have costs and benefits that spill over to sectors outside the healthcare sector. Little is known about these "inter-sectoral costs and benefits" (ICBs) of prevention. However, to achieve an efficient allocation of scarce resources, insights on ICBs are indispensable. The main aim was to identify the ICBs related to the prevention of mental disorders and provide a sector-specific classification scheme for these ICBs. Using PubMed, a literature search was conducted for ICBs of mental disorders and related (psycho)social effects. A policy perspective was used to build the scheme's structure, which was adapted to the outcomes of the literature search. In order to validate the scheme's international applicability inside and outside the mental health domain, semi-structured interviews were conducted with (inter)national experts in the broad fields of health promotion and disease prevention. The searched-for items appeared in a total of 52 studies. The ICBs found were classified in one of four sectors: "Education", "Labor and Social Security", "Household and Leisure" or "Criminal Justice System". Psycho(social) effects were placed in a separate section under "Individual and Family". Based on interviews, the scheme remained unadjusted, apart from adding a population-based dimension. This is the first study which offers a sector-specific classification of ICBs. Given the explorative nature of the study, no guidelines on sector-specific classification of ICBs were available. Nevertheless, the classification scheme was acknowledged by an international audience and could therefore provide added value to researchers and policymakers in the field of mental health economics and prevention. The identification and classification of ICBs offers decision makers supporting information on how to optimally allocate scarce resources with respect to preventive interventions for mental disorders. By exploring a new area of research, which has remained largely unexplored until now, the current study has an added value as it may form the basis for the development of a tool which can be used to calculate the ICBs of specific mental health related preventive interventions.

Comparison of Unsupervised Vegetation Classification Methods from Vhr Images after Shadows Removal by Innovative Algorithms

NASA Astrophysics Data System (ADS)

Movia, A.; Beinat, A.; Crosilla, F.

2015-04-01

The recognition of vegetation by the analysis of very high resolution (VHR) aerial images provides meaningful information about environmental features; nevertheless, VHR images frequently contain shadows that generate significant problems for the classification of the image components and for the extraction of the needed information. The aim of this research is to classify, from VHR aerial images, vegetation involved in the balance process of the environmental biochemical cycle, and to discriminate it with respect to urban and agricultural features. Three classification algorithms have been experimented in order to better recognize vegetation, and compared to NDVI index; unfortunately all these methods are conditioned by the presence of shadows on the images. Literature presents several algorithms to detect and remove shadows in the scene: most of them are based on the RGB to HSI transformations. In this work some of them have been implemented and compared with one based on RGB bands. Successively, in order to remove shadows and restore brightness on the images, some innovative algorithms, based on Procrustes theory, have been implemented and applied. Among these, we evaluate the capability of the so called "not-centered oblique Procrustes" and "anisotropic Procrustes" methods to efficiently restore brightness with respect to a linear correlation correction based on the Cholesky decomposition. Some experimental results obtained by different classification methods after shadows removal carried out with the innovative algorithms are presented and discussed.

Classifier ensemble construction with rotation forest to improve medical diagnosis performance of machine learning algorithms.

PubMed

Ozcift, Akin; Gulten, Arif

2011-12-01

Improving accuracies of machine learning algorithms is vital in designing high performance computer-aided diagnosis (CADx) systems. Researches have shown that a base classifier performance might be enhanced by ensemble classification strategies. In this study, we construct rotation forest (RF) ensemble classifiers of 30 machine learning algorithms to evaluate their classification performances using Parkinson's, diabetes and heart diseases from literature. While making experiments, first the feature dimension of three datasets is reduced using correlation based feature selection (CFS) algorithm. Second, classification performances of 30 machine learning algorithms are calculated for three datasets. Third, 30 classifier ensembles are constructed based on RF algorithm to assess performances of respective classifiers with the same disease data. All the experiments are carried out with leave-one-out validation strategy and the performances of the 60 algorithms are evaluated using three metrics; classification accuracy (ACC), kappa error (KE) and area under the receiver operating characteristic (ROC) curve (AUC). Base classifiers succeeded 72.15%, 77.52% and 84.43% average accuracies for diabetes, heart and Parkinson's datasets, respectively. As for RF classifier ensembles, they produced average accuracies of 74.47%, 80.49% and 87.13% for respective diseases. RF, a newly proposed classifier ensemble algorithm, might be used to improve accuracy of miscellaneous machine learning algorithms to design advanced CADx systems. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

A Bayesian Approach to Genome/Linguistic Relationships in Native South Americans

PubMed Central

Amorim, Carlos Eduardo Guerra; Bisso-Machado, Rafael; Ramallo, Virginia; Bortolini, Maria Cátira; Bonatto, Sandro Luis; Salzano, Francisco Mauro; Hünemeier, Tábita

2013-01-01

The relationship between the evolution of genes and languages has been studied for over three decades. These studies rely on the assumption that languages, as many other cultural traits, evolve in a gene-like manner, accumulating heritable diversity through time and being subjected to evolutionary mechanisms of change. In the present work we used genetic data to evaluate South American linguistic classifications. We compared discordant models of language classifications to the current Native American genome-wide variation using realistic demographic models analyzed under an Approximate Bayesian Computation (ABC) framework. Data on 381 STRs spread along the autosomes were gathered from the literature for populations representing the five main South Amerindian linguistic groups: Andean, Arawakan, Chibchan-Paezan, Macro-Jê, and Tupí. The results indicated a higher posterior probability for the classification proposed by J.H. Greenberg in 1987, although L. Campbell's 1997 classification cannot be ruled out. Based on Greenberg's classification, it was possible to date the time of Tupí-Arawakan divergence (2.8 kya), and the time of emergence of the structure between present day major language groups in South America (3.1 kya). PMID:23696865

A scheme for a flexible classification of dietary and health biomarkers.

PubMed

Gao, Qian; Praticò, Giulia; Scalbert, Augustin; Vergères, Guy; Kolehmainen, Marjukka; Manach, Claudine; Brennan, Lorraine; Afman, Lydia A; Wishart, David S; Andres-Lacueva, Cristina; Garcia-Aloy, Mar; Verhagen, Hans; Feskens, Edith J M; Dragsted, Lars O

2017-01-01

Biomarkers are an efficient means to examine intakes or exposures and their biological effects and to assess system susceptibility. Aided by novel profiling technologies, the biomarker research field is undergoing rapid development and new putative biomarkers are continuously emerging in the scientific literature. However, the existing concepts for classification of biomarkers in the dietary and health area may be ambiguous, leading to uncertainty about their application. In order to better understand the potential of biomarkers and to communicate their use and application, it is imperative to have a solid scheme for biomarker classification that will provide a well-defined ontology for the field. In this manuscript, we provide an improved scheme for biomarker classification based on their intended use rather than the technology or outcomes (six subclasses are suggested: food compound intake biomarkers (FCIBs), food or food component intake biomarkers (FIBs), dietary pattern biomarkers (DPBs), food compound status biomarkers (FCSBs), effect biomarkers, physiological or health state biomarkers). The application of this scheme is described in detail for the dietary and health area and is compared with previous biomarker classification for this field of research.

A bayesian approach to genome/linguistic relationships in native South Americans.

PubMed

Amorim, Carlos Eduardo Guerra; Bisso-Machado, Rafael; Ramallo, Virginia; Bortolini, Maria Cátira; Bonatto, Sandro Luis; Salzano, Francisco Mauro; Hünemeier, Tábita

2013-01-01

The relationship between the evolution of genes and languages has been studied for over three decades. These studies rely on the assumption that languages, as many other cultural traits, evolve in a gene-like manner, accumulating heritable diversity through time and being subjected to evolutionary mechanisms of change. In the present work we used genetic data to evaluate South American linguistic classifications. We compared discordant models of language classifications to the current Native American genome-wide variation using realistic demographic models analyzed under an Approximate Bayesian Computation (ABC) framework. Data on 381 STRs spread along the autosomes were gathered from the literature for populations representing the five main South Amerindian linguistic groups: Andean, Arawakan, Chibchan-Paezan, Macro-Jê, and Tupí. The results indicated a higher posterior probability for the classification proposed by J.H. Greenberg in 1987, although L. Campbell's 1997 classification cannot be ruled out. Based on Greenberg's classification, it was possible to date the time of Tupí-Arawakan divergence (2.8 kya), and the time of emergence of the structure between present day major language groups in South America (3.1 kya).

Branch classification: A new mechanism for improving branch predictor performance

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chang, P.Y.; Hao, E.; Patt, Y.

There is wide agreement that one of the most significant impediments to the performance of current and future pipelined superscalar processors is the presence of conditional branches in the instruction stream. Speculative execution is one solution to the branch problem, but speculative work is discarded if a branch is mispredicted. For it to be effective, speculative work is discarded if a branch is mispredicted. For it to be effective, speculative execution requires a very accurate branch predictor; 95% accuracy is not good enough. This paper proposes branch classification, a methodology for building more accurate branch predictors. Branch classification allows anmore » individual branch instruction to be associated with the branch predictor best suited to predict its direction. Using this approach, a hybrid branch predictor can be constructed such that each component branch predictor predicts those branches for which it is best suited. To demonstrate the usefulness of branch classification, an example classification scheme is given and a new hybrid predictor is built based on this scheme which achieves a higher prediction accuracy than any branch predictor previously reported in the literature.« less

Random forests for classification in ecology

USGS Publications Warehouse

Cutler, D.R.; Edwards, T.C.; Beard, K.H.; Cutler, A.; Hess, K.T.; Gibson, J.; Lawler, J.J.

2007-01-01

Classification procedures are some of the most widely used statistical methods in ecology. Random forests (RF) is a new and powerful statistical classifier that is well established in other disciplines but is relatively unknown in ecology. Advantages of RF compared to other statistical classifiers include (1) very high classification accuracy; (2) a novel method of determining variable importance; (3) ability to model complex interactions among predictor variables; (4) flexibility to perform several types of statistical data analysis, including regression, classification, survival analysis, and unsupervised learning; and (5) an algorithm for imputing missing values. We compared the accuracies of RF and four other commonly used statistical classifiers using data on invasive plant species presence in Lava Beds National Monument, California, USA, rare lichen species presence in the Pacific Northwest, USA, and nest sites for cavity nesting birds in the Uinta Mountains, Utah, USA. We observed high classification accuracy in all applications as measured by cross-validation and, in the case of the lichen data, by independent test data, when comparing RF to other common classification methods. We also observed that the variables that RF identified as most important for classifying invasive plant species coincided with expectations based on the literature. ?? 2007 by the Ecological Society of America.

Treatment of Holocaust Denial Literature in Association of Research Libraries

ERIC Educational Resources Information Center

Spidal, Debra F.

2012-01-01

Holocaust denial literature has been treated inconsistently in library collections. At one time Holocaust denial literature was classed and subject headings assigned with Holocaust literature. After specific Library of Congress classification numbers and subject headings for Holocaust denial and Holocaust denial literature became available in the…

Intraosseous haemangioma: semantic and medical confusion.

PubMed

Kadlub, N; Dainese, L; Coulomb-L'Hermine, A; Galmiche, L; Soupre, V; Lepointe, H Ducou; Vazquez, M-P; Picard, A

2015-06-01

The literature is rich in case reports of intraosseous haemangioma, although most of these are actually cases of venous or capillary malformations. To illustrate this confusion in terminology, we present three cases of slow-flow vascular malformations misnamed as intraosseous haemangioma. A retrospective study of children diagnosed with intraosseous haemangioma was conducted. Clinical and radiological data were evaluated. Histopathological examinations and immunohistochemical studies were redone by three independent pathologists to classify the lesions according to the International Society for the Study of Vascular Anomalies (ISSVA) and World Health Organization (WHO) classifications. Three children who had presented with jaw haemangiomas were identified. Computed tomography scan patterns were not specific. All tumours were GLUT-1-negative and D2-40-negative. The lesions were classified as central haemangiomas according to the WHO, and as slow-flow malformations according to the ISSVA. The classification of vascular anomalies is based on clinical, radiological, and histological differences between vascular tumours and malformations. Based on this classification, the evolution of the lesion can be predicted and adequate treatment applied. The binary ISSVA classification is widely accepted and should be applied for all vascular lesions. Copyright © 2015 International Association of Oral and Maxillofacial Surgeons. Published by Elsevier Ltd. All rights reserved.

Phytotherapy management: a new intervention for nursing intervention classification.

PubMed

Paloma, Echevarria; Ovidio, Céspedes; Jessica, Rojas; Francisca, Sánchez Ayllón; Isabel, Morales; Maravillas, Gimenez

2014-01-01

We present a new nurse intervention: "Phytotherapy Management," which has been accepted by the editorial board of the Nursing Interventions Classification for inclusion in the 7th edition of the Nursing Intervention Classification. This could have implications for nursing practice and research. Content analysis, extensive search in the literature.

Enigmatic human tails: A review of their history, embryology, classification, and clinical manifestations.

PubMed

Tubbs, R Shane; Malefant, Jason; Loukas, Marios; Jerry Oakes, W; Oskouian, Rod J; Fries, Fabian N

2016-05-01

The presence of a human tail is a rare and intriguing phenomenon. While cases have been reported in the literature, confusion remains with respect to the proper classification, definition, and treatment methods. We review the literature concerning this anatomical derailment. We also consider the importance of excluding underlying congenital anomalies in these patients to prevent neurological deficits and other abnormal manifestations. © 2016 Wiley Periodicals, Inc.

SVM feature selection based rotation forest ensemble classifiers to improve computer-aided diagnosis of Parkinson disease.

PubMed

Ozcift, Akin

2012-08-01

Parkinson disease (PD) is an age-related deterioration of certain nerve systems, which affects movement, balance, and muscle control of clients. PD is one of the common diseases which affect 1% of people older than 60 years. A new classification scheme based on support vector machine (SVM) selected features to train rotation forest (RF) ensemble classifiers is presented for improving diagnosis of PD. The dataset contains records of voice measurements from 31 people, 23 with PD and each record in the dataset is defined with 22 features. The diagnosis model first makes use of a linear SVM to select ten most relevant features from 22. As a second step of the classification model, six different classifiers are trained with the subset of features. Subsequently, at the third step, the accuracies of classifiers are improved by the utilization of RF ensemble classification strategy. The results of the experiments are evaluated using three metrics; classification accuracy (ACC), Kappa Error (KE) and Area under the Receiver Operating Characteristic (ROC) Curve (AUC). Performance measures of two base classifiers, i.e. KStar and IBk, demonstrated an apparent increase in PD diagnosis accuracy compared to similar studies in literature. After all, application of RF ensemble classification scheme improved PD diagnosis in 5 of 6 classifiers significantly. We, numerically, obtained about 97% accuracy in RF ensemble of IBk (a K-Nearest Neighbor variant) algorithm, which is a quite high performance for Parkinson disease diagnosis.

Arthrogryposis: an update on clinical aspects, etiology, and treatment strategies

PubMed Central

Feluś, Jarosław

2016-01-01

Arthrogryposes – multiple joint contractures – are a clinically and etiologically heterogeneous class of diseases, where accurate diagnosis, recognition of the underlying pathology and classification are of key importance for the prognosis as well as for selection of appropriate management. This treatment remains challenging and optimally in arthrogrypotic patients should be carried out by a team of specialists familiar with all aspects of arthrogryposis pathology and treatment modalities: rehabilitation, orthotics and surgery. In this comprehensive review article, based on literature and clinical experience, the authors present an update on current knowledge on etiology, classifications and treatment options for skeletal deformations possible in arthrogryposis. PMID:26925114

Radial Artery Coursing Behind the Biceps Brachii Tendon: Significance for the Transradial Catheterization and a Clinically Oriented Classification of the Radial Artery Variations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jelev, L., E-mail: ljelev@abv.bg; Surchev, L.

2008-09-15

In routine clinical practice the variations of the radial artery are the main reason for technical failure during transradial catheterization. If these variations are well documented, however, they do not represent a problem in the transradial approach. Therefore, we report here a rare case of the radial artery which is very strange but potentially valuable for the clinical practice: it arises at a right angle from the brachial artery and passes behind the biceps brachii tendon. Based on our findings and on an extensive literature review, we propose for the first time a clinically oriented classification of the variations ofmore » the radial artery. This classification is related to the catheterization success at the usual access site of the radial artery at the wrist.« less

Gender classification from video under challenging operating conditions

NASA Astrophysics Data System (ADS)

Mendoza-Schrock, Olga; Dong, Guozhu

2014-06-01

The literature is abundant with papers on gender classification research. However the majority of such research is based on the assumption that there is enough resolution so that the subject's face can be resolved. Hence the majority of the research is actually in the face recognition and facial feature area. A gap exists for gender classification under challenging operating conditions—different seasonal conditions, different clothing, etc.—and when the subject's face cannot be resolved due to lack of resolution. The Seasonal Weather and Gender (SWAG) Database is a novel database that contains subjects walking through a scene under operating conditions that span a calendar year. This paper exploits a subset of that database—the SWAG One dataset—using data mining techniques, traditional classifiers (ex. Naïve Bayes, Support Vector Machine, etc.) and traditional (canny edge detection, etc.) and non-traditional (height/width ratios, etc.) feature extractors to achieve high correct gender classification rates (greater than 85%). Another novelty includes exploiting frame differentials.

Investigating the Potential of Deep Neural Networks for Large-Scale Classification of Very High Resolution Satellite Images

NASA Astrophysics Data System (ADS)

Postadjian, T.; Le Bris, A.; Sahbi, H.; Mallet, C.

2017-05-01

Semantic classification is a core remote sensing task as it provides the fundamental input for land-cover map generation. The very recent literature has shown the superior performance of deep convolutional neural networks (DCNN) for many classification tasks including the automatic analysis of Very High Spatial Resolution (VHR) geospatial images. Most of the recent initiatives have focused on very high discrimination capacity combined with accurate object boundary retrieval. Therefore, current architectures are perfectly tailored for urban areas over restricted areas but not designed for large-scale purposes. This paper presents an end-to-end automatic processing chain, based on DCNNs, that aims at performing large-scale classification of VHR satellite images (here SPOT 6/7). Since this work assesses, through various experiments, the potential of DCNNs for country-scale VHR land-cover map generation, a simple yet effective architecture is proposed, efficiently discriminating the main classes of interest (namely buildings, roads, water, crops, vegetated areas) by exploiting existing VHR land-cover maps for training.

Measuring body structures and body functions from the International Classification of Functioning, Disability, and Health perspective: considerations for biomedical parameters in spinal cord injury research.

PubMed

Eriks-Hoogland, Inge E; Brinkhof, Martin W G; Al-Khodairy, Abdul; Baumberger, Michael; Brechbühl, Jörg; Curt, Armin; Mäder, Mark; Stucki, Gerold; Post, Marcel W M

2011-11-01

The aims of this study were to provide a selection of biomedical domains based on the comprehensive International Classification of Functioning, Disability, and Health (ICF) core sets for spinal cord injury (SCI) and to present an overview of the corresponding measurement instruments. Based on the Biomedical Domain Set, the SCI literature, the International Spinal Cord Society international data sets, and the Spinal Cord Injury Rehabilitation Evidence project publications were used to derive category specifications for use in SCI research. Expert opinion was used to derive a priority selection. The same sources were used to determine candidate measurement instruments for the specification of body functions and body structures using an example, and guiding principles were applied to select the most appropriate biomedical measurement instrument(s) for use in an SCI research project. Literature searches were performed for 41 second-level ICF body functions categories and for four second-level ICF body structures categories. For some of these categories, only a few candidate measurement instruments were found with limited variation in the type of measurement instruments. An ICF-based measurement set for biomedical aspects of functioning with SCI was established. For some categories of the ICF core sets for SCI, there is a need to develop measurement instruments.

Formalization of the classification pattern: survey of classification modeling in information systems engineering.

PubMed

Partridge, Chris; de Cesare, Sergio; Mitchell, Andrew; Odell, James

2018-01-01

Formalization is becoming more common in all stages of the development of information systems, as a better understanding of its benefits emerges. Classification systems are ubiquitous, no more so than in domain modeling. The classification pattern that underlies these systems provides a good case study of the move toward formalization in part because it illustrates some of the barriers to formalization, including the formal complexity of the pattern and the ontological issues surrounding the "one and the many." Powersets are a way of characterizing the (complex) formal structure of the classification pattern, and their formalization has been extensively studied in mathematics since Cantor's work in the late nineteenth century. One can use this formalization to develop a useful benchmark. There are various communities within information systems engineering (ISE) that are gradually working toward a formalization of the classification pattern. However, for most of these communities, this work is incomplete, in that they have not yet arrived at a solution with the expressiveness of the powerset benchmark. This contrasts with the early smooth adoption of powerset by other information systems communities to, for example, formalize relations. One way of understanding the varying rates of adoption is recognizing that the different communities have different historical baggage. Many conceptual modeling communities emerged from work done on database design, and this creates hurdles to the adoption of the high level of expressiveness of powersets. Another relevant factor is that these communities also often feel, particularly in the case of domain modeling, a responsibility to explain the semantics of whatever formal structures they adopt. This paper aims to make sense of the formalization of the classification pattern in ISE and surveys its history through the literature, starting from the relevant theoretical works of the mathematical literature and gradually shifting focus to the ISE literature. The literature survey follows the evolution of ISE's understanding of how to formalize the classification pattern. The various proposals are assessed using the classical example of classification; the Linnaean taxonomy formalized using powersets as a benchmark for formal expressiveness. The broad conclusion of the survey is that (1) the ISE community is currently in the early stages of the process of understanding how to formalize the classification pattern, particularly in the requirements for expressiveness exemplified by powersets, and (2) that there is an opportunity to intervene and speed up the process of adoption by clarifying this expressiveness. Given the central place that the classification pattern has in domain modeling, this intervention has the potential to lead to significant improvements.

Literature classification for semi-automated updating of biological knowledgebases

PubMed Central

2013-01-01

Background As the output of biological assays increase in resolution and volume, the body of specialized biological data, such as functional annotations of gene and protein sequences, enables extraction of higher-level knowledge needed for practical application in bioinformatics. Whereas common types of biological data, such as sequence data, are extensively stored in biological databases, functional annotations, such as immunological epitopes, are found primarily in semi-structured formats or free text embedded in primary scientific literature. Results We defined and applied a machine learning approach for literature classification to support updating of TANTIGEN, a knowledgebase of tumor T-cell antigens. Abstracts from PubMed were downloaded and classified as either "relevant" or "irrelevant" for database update. Training and five-fold cross-validation of a k-NN classifier on 310 abstracts yielded classification accuracy of 0.95, thus showing significant value in support of data extraction from the literature. Conclusion We here propose a conceptual framework for semi-automated extraction of epitope data embedded in scientific literature using principles from text mining and machine learning. The addition of such data will aid in the transition of biological databases to knowledgebases. PMID:24564403

Diagnostic Principles of Peri-Implantitis: a Systematic Review and Guidelines for Peri-Implantitis Diagnosis Proposal.

PubMed

Ramanauskaite, Ausra; Juodzbalys, Gintaras

2016-01-01

To review and summarize the literature concerning peri-implantitis diagnostic parameters and to propose guidelines for peri-implantitis diagnosis. An electronic literature search was conducted of the MEDLINE (Ovid) and EMBASE databases for articles published between 2011 and 2016. Sequential screening at the title/abstract and full-text levels was performed. Systematic reviews/guidelines of consensus conferences proposing classification or suggesting diagnostic parameters for peri-implantitis in the English language were included. The review was recorded on PROSPERO system with the code CRD42016033287. The search resulted in 10 articles that met the inclusion criteria. Four were papers from consensus conferences, two recommended diagnostic guidelines, three proposed classification of peri-implantitis, and one suggested an index for implant success. The following parameters were suggested to be used for peri-implantitis diagnosis: pain, mobility, bleeding on probing, probing depth, suppuration/exudate, and radiographic bone loss. In all of the papers, different definitions of peri-implantitis or implant success, as well as different thresholds for the above mentioned clinical and radiographical parameters, were used. Current evidence rationale for the diagnosis of peri-implantitis and classification based on consecutive evaluation of soft-tissue conditions and the amount of bone loss were suggested. Currently there is no single uniform definition of peri-implantitis or the parameters that should be used. Rationale for diagnosis and prognosis of peri-implantitis as well as classification of the disease is proposed.

Neonatal physical therapy. Part II: Practice frameworks and evidence-based practice guidelines.

PubMed

Sweeney, Jane K; Heriza, Carolyn B; Blanchard, Yvette; Dusing, Stacey C

2010-01-01

(1) To outline frameworks for neonatal physical therapy based on 3 theoretical models, (2) to describe emerging literature supporting neonatal physical therapy practice, and (3) to identify evidence-based practice recommendations. Three models are presented as a framework for neonatal practice: (1) dynamic systems theory including synactive theory and the theory of neuronal group selection, (2) the International Classification of Functioning, Disability and Health, and (3) family-centered care. Literature is summarized to support neonatal physical therapists in the areas of examination, developmental care, intervention, and parent education. Practice recommendations are offered with levels of evidence identified. Neonatal physical therapy practice has a theoretical and evidence-based structure, and evidence is emerging for selected clinical procedures. Continued research to expand the science of neonatal physical therapy is critical to elevate the evidence and support practice recommendations.

The Classification of Art Slides: A Survey and Recommendations.

ERIC Educational Resources Information Center

Watt, Richard S.

The nature and variety of classification systems for museum and university art department slide collections are surveyed through a review of the literature on slide classification in the United States, Great Britain, and Australia, and through case studies of major slide collections at Duke University, the University of North Carolina at Chapel…

Review and Content Analysis of the "International Review of Research in Open and Distance/Distributed Learning" (2000-2015)

ERIC Educational Resources Information Center

Zawacki-Richter, Olaf; Alturki, Uthman; Aldraiweesh, Ahmed

2017-01-01

This paper presents a review of distance education literature published in the "International Review of Research in Open and Distance/Distributed Learning" (IRRODL) to describe the status thereof and to identify gaps and priority areas in distance education research based on a validated classification of research areas. All articles (N =…

The Quality of Teacher Educators in the European Policy Debate: Actions and Measures to Improve the Professionalism of Teacher Educators

ERIC Educational Resources Information Center

Snoek, Marco; Swennen, Anja; van der Klink, Marcel

2011-01-01

This study examines how the contemporary European policy debate addresses the further development of the quality of teacher educators. A classification framework based on the literature on professionalism was used to compare European and Member State policy actions and measures on the quality of teacher educators through an analysis of seven…

Review of the therapeutic management of Parkinson's disease. Report of a joint task force of the European Federation of Neurological Societies and the Movement Disorder Society-European Section. Part I: early (uncomplicated) Parkinson's disease.

PubMed

Horstink, M; Tolosa, E; Bonuccelli, U; Deuschl, G; Friedman, A; Kanovsky, P; Larsen, J P; Lees, A; Oertel, W; Poewe, W; Rascol, O; Sampaio, C

2006-11-01

The aim of the study was to provide evidence-based recommendations for the management of early (uncomplicated) Parkinson's disease (PD), based on a review of the literature. Uncomplicated PD refers to patients suffering from the classical motor syndrome of PD only, without treatment-induced motor complications and without neuropsychiatric or autonomic problems. MEDLINE, Cochrane Library and International Network of Agencies for Health Technology Assessment (INAHTA) database literature searches were conducted. National guidelines were requested from all European Federation of Neurological Societies (EFNS) societies. Non-European guidelines were searched for using MEDLINE. Part I of the guidelines deals with prevention of disease progression, symptomatic treatment of motor features (parkinsonism), and prevention of motor and neuropsychiatric complications of therapy. For each topic, a list of therapeutic interventions is provided, including classification of evidence. Following this, recommendations for management are given, alongside ratings of efficacy. Classifications of evidence and ratings of efficacy are made according to EFNS guidance. In cases where there is insufficient scientific evidence, a consensus statement (good practice point) is made.

Computer-based quantitative computed tomography image analysis in idiopathic pulmonary fibrosis: A mini review.

PubMed

Ohkubo, Hirotsugu; Nakagawa, Hiroaki; Niimi, Akio

2018-01-01

Idiopathic pulmonary fibrosis (IPF) is the most common type of progressive idiopathic interstitial pneumonia in adults. Many computer-based image analysis methods of chest computed tomography (CT) used in patients with IPF include the mean CT value of the whole lungs, density histogram analysis, density mask technique, and texture classification methods. Most of these methods offer good assessment of pulmonary functions, disease progression, and mortality. Each method has merits that can be used in clinical practice. One of the texture classification methods is reported to be superior to visual CT scoring by radiologist for correlation with pulmonary function and prediction of mortality. In this mini review, we summarize the current literature on computer-based CT image analysis of IPF and discuss its limitations and several future directions. Copyright © 2017 The Japanese Respiratory Society. Published by Elsevier B.V. All rights reserved.

Impact of oesophagitis classification in evaluating healing of erosive oesophagitis after therapy with proton pump inhibitors: a pooled analysis.

PubMed

Yaghoobi, Mohammad; Padol, Sara; Yuan, Yuhong; Hunt, Richard H

2010-05-01

The results of clinical trials with proton pump inhibitors (PPIs) are usually based on the Hetzel-Dent (HD), Savary-Miller (SM), or Los Angeles (LA) classifications to describe the severity and assess the healing of erosive oesophagitis. However, it is not known whether these classifications are comparable. The aim of this study was to review systematically the literature to compare the healing rates of erosive oesophagitis with PPIs in clinical trials assessed by the HD, SM, or LA classifications. A recursive, English language literature search in PubMed and Cochrane databases to December 2006 was performed. Double-blind randomized control trials comparing a PPI with another PPI, an H2-RA or placebo using endoscopic assessment of the healing of oesophagitis by the HD, SM or LA, or their modified classifications at 4 or 8 weeks, were included in the study. The healing rates on treatment with the same PPI(s), and same endoscopic grade(s) were pooled and compared between different classifications using Fisher's exact test or chi2 test where appropriate. Forty-seven studies from 965 potential citations met inclusion criteria. Seventy-eight PPI arms were identified, with 27 using HD, 29 using SM, and 22 using LA for five marketed PPIs. There was insufficient data for rabeprazole and esomeprazole (week 4 only) to compare because they were evaluated by only one classification. When data from all PPIs were pooled, regardless of baseline oesophagitis grades, the LA healing rate was significantly higher than SM and HD at both 4 and 8 weeks (74, 71, and 68% at 4 weeks and 89, 84, and 83% at 8 weeks, respectively). The distribution of different grades in study population was available only for pantoprazole where it was not significantly different between LA and SM subgroups. When analyzing data for PPI and dose, the LA classification showed a higher healing rate for omeprazole 20 mg/day and pantoprazole 40 mg/day (significant at 8 weeks), whereas healing by SM classification was significantly higher for omeprazole 40 mg/day (no data for LA) and lansoprazole 30 mg/day at 4 and 8 weeks. The healing rate by individual oesophagitis grade was not always available or robust enough for meaningful analysis. However, a difference between classifications remained. There is a significant, but not always consistent, difference in oesophagitis healing rates with the same PPI(s) reported by the LA, SM, or HD classifications. The possible difference between grading classifications should be considered when interpreting or comparing healing rates for oesophagitis from different studies.

Automating multistep flow synthesis: approach and challenges in integrating chemistry, machines and logic

PubMed Central

Shukla, Chinmay A

2017-01-01

The implementation of automation in the multistep flow synthesis is essential for transforming laboratory-scale chemistry into a reliable industrial process. In this review, we briefly introduce the role of automation based on its application in synthesis viz. auto sampling and inline monitoring, optimization and process control. Subsequently, we have critically reviewed a few multistep flow synthesis and suggested a possible control strategy to be implemented so that it helps to reliably transfer the laboratory-scale synthesis strategy to a pilot scale at its optimum conditions. Due to the vast literature in multistep synthesis, we have classified the literature and have identified the case studies based on few criteria viz. type of reaction, heating methods, processes involving in-line separation units, telescopic synthesis, processes involving in-line quenching and process with the smallest time scale of operation. This classification will cover the broader range in the multistep synthesis literature. PMID:28684977

Influence of leaching conditions for ecotoxicological classification of ash.

PubMed

Stiernström, S; Enell, A; Wik, O; Hemström, K; Breitholtz, M

2014-02-01

The Waste Framework Directive (WFD; 2008/98/EC) states that classification of hazardous ecotoxicological properties of wastes (i.e. criteria H-14), should be based on the Community legislation on chemicals (i.e. CLP Regulation 1272/2008). However, harmonizing the waste and chemical classification may involve drastic changes related to choice of leaching tests as compared to e.g. the current European standard for ecotoxic characterization of waste (CEN 14735). The primary aim of the present study was therefore to evaluate the influence of leaching conditions, i.e. pH (inherent pH (∼10), and 7), liquid to solid (L/S) ratio (10 and 1000 L/kg) and particle size (<4 mm, <1 mm, and <0.125 mm), for subsequent chemical analysis and ecotoxicity testing in relation to classification of municipal waste incineration bottom ash. The hazard potential, based on either comparisons between element levels in leachate and literature toxicity data or ecotoxicity testing of the leachates, was overall significantly higher at low particle size (<0.125 mm) as compared to particle fractions <1mm and <4mm, at pH 10 as compared to pH 7, and at L/S 10 as compared to L/S 1000. These results show that the choice of leaching conditions is crucial for H-14 classification of ash and must be carefully considered in deciding on future guidance procedures in Europe. Copyright © 2013 Elsevier Ltd. All rights reserved.

Epileptic seizure detection in EEG signal using machine learning techniques.

PubMed

Jaiswal, Abeg Kumar; Banka, Haider

2018-03-01

Epilepsy is a well-known nervous system disorder characterized by seizures. Electroencephalograms (EEGs), which capture brain neural activity, can detect epilepsy. Traditional methods for analyzing an EEG signal for epileptic seizure detection are time-consuming. Recently, several automated seizure detection frameworks using machine learning technique have been proposed to replace these traditional methods. The two basic steps involved in machine learning are feature extraction and classification. Feature extraction reduces the input pattern space by keeping informative features and the classifier assigns the appropriate class label. In this paper, we propose two effective approaches involving subpattern based PCA (SpPCA) and cross-subpattern correlation-based PCA (SubXPCA) with Support Vector Machine (SVM) for automated seizure detection in EEG signals. Feature extraction was performed using SpPCA and SubXPCA. Both techniques explore the subpattern correlation of EEG signals, which helps in decision-making process. SVM is used for classification of seizure and non-seizure EEG signals. The SVM was trained with radial basis kernel. All the experiments have been carried out on the benchmark epilepsy EEG dataset. The entire dataset consists of 500 EEG signals recorded under different scenarios. Seven different experimental cases for classification have been conducted. The classification accuracy was evaluated using tenfold cross validation. The classification results of the proposed approaches have been compared with the results of some of existing techniques proposed in the literature to establish the claim.

[Knowledge produced from the outcomes of the "Nursing Outcomes Classification--NOC": integrative review].

PubMed

da Silva, Natália Chantal Magalhães; de Souza Oliveira, Ana Railka; de Carvalho, Emília Campos

2015-12-01

To identify the knowledge produced from the outcomes of the Nursing Outcomes Classification (NOC). A literature review using the integrative databases: Latin American and Caribbean Health Sciences (LILACS), US National Library of Medicine (PubMed), Cumulative Index to Nursing & Allied Health Literature (CINAHL) and Scopus Info Site (SCOPUS), during the months of August and September 2014. The review consisted of 21 articles that addressed different issues: Translation and Cultural adaptation (4.77%); Applicability in clinical practice (33.33%); and, Validation (63.90%). Analysis of these articles showed that the knowledge produced from the Nursing Outcomes Classification includes translation and cultural adaptation, evaluation of applicability and validation of its items. Considering the continuous evolution of this classification, periodic reviews should be carried out to identify the knowledge, use and effects of the NOC.

Comparing writing style feature-based classification methods for estimating user reputations in social media.

PubMed

Suh, Jong Hwan

2016-01-01

In recent years, the anonymous nature of the Internet has made it difficult to detect manipulated user reputations in social media, as well as to ensure the qualities of users and their posts. To deal with this, this study designs and examines an automatic approach that adopts writing style features to estimate user reputations in social media. Under varying ways of defining Good and Bad classes of user reputations based on the collected data, it evaluates the classification performance of the state-of-art methods: four writing style features, i.e. lexical, syntactic, structural, and content-specific, and eight classification techniques, i.e. four base learners-C4.5, Neural Network (NN), Support Vector Machine (SVM), and Naïve Bayes (NB)-and four Random Subspace (RS) ensemble methods based on the four base learners. When South Korea's Web forum, Daum Agora, was selected as a test bed, the experimental results show that the configuration of the full feature set containing content-specific features and RS-SVM combining RS and SVM gives the best accuracy for classification if the test bed poster reputations are segmented strictly into Good and Bad classes by portfolio approach. Pairwise t tests on accuracy confirm two expectations coming from the literature reviews: first, the feature set adding content-specific features outperform the others; second, ensemble learning methods are more viable than base learners. Moreover, among the four ways on defining the classes of user reputations, i.e. like, dislike, sum, and portfolio, the results show that the portfolio approach gives the highest accuracy.

A Biochar Classification System and Associated Test Methods

DOE Office of Scientific and Technical Information (OSTI.GOV)

Camps-Arbestain, Marta; Amonette, James E.; Singh, Balwant

2015-02-18

In this chapter, a biochar classification system related to its use as soil amendment is proposed. This document builds upon previous work and constrains its scope to materials with properties that satisfy the criteria for biochar as defined by either the International Biochar Initiative (IBI) Biochar Standards or the European Biochar Community (EBC) Standards, and it is intended to minimise the need for testing in addition to those required according to the above-mentioned standards. The classification system envisions enabling stakeholders and commercial entities to (i) identify the most suitable biochar to fulfil the requirements for a particular soil and/or land-use,more » and (ii) distinguish the application of biochar for specific niches (e.g., soilless agriculture). It is based on the best current knowledge and the intention is to periodically review and update the document based on new data and knowledge that become available in the scientific literature. The main thrust of this classification system is based on the direct or indirect beneficial effects that biochar provides from its application to soil. We have classified the potential beneficial effects of biochar application to soils into five categories with their corresponding classes, where applicable: (i) carbon (C) storage value, (ii) fertiliser value, (iii) liming value, (iv) particle-size, and (v) use in soil-less agriculture. A summary of recommended test methods is provided at the end of the chapter.« less

A pre-classification strategy based on UPLC-Triple-TOF/MS for metabolic screening and identification of Radix glehniae in rats.

PubMed

Wang, Shuang; Qi, Pengcheng; Zhou, Na; Zhao, Minmin; Ding, Weijing; Li, Song; Liu, Minyan; Wang, Qiao; Jin, Shumin

2016-10-01

Traditional Chinese Medicines (TCMs) have gained increasing popularity in modern society. However, the profiles of TCMs in vivo are still unclear owing to their complexity and low level in vivo. In this study, UPLC-Triple-TOF techniques were employed for data acquiring, and a novel pre-classification strategy was developed to rapidly and systematically screen and identify the absorbed constituents and metabolites of TCMs in vivo using Radix glehniae as the research object. In this strategy, pre-classification for absorbed constituents was first performed according to the similarity of their structures. Then representative constituents were elected from every class and analyzed separately to screen non-target absorbed constituents and metabolites in biosamples. This pre-classification strategy is basing on target (known) constituents to screen non-target (unknown) constituents from the massive data acquired by mass spectrometry. Finally, the screened candidate compounds were interpreted and identified based on a predicted metabolic pathway, well - studied fragmentation rules, a predicted metabolic pathway, polarity and retention time of the compounds, and some related literature. With this method, a total of 111 absorbed constituents and metabolites of Radix glehniae in rats' urine, plasma, and bile samples were screened and identified or tentatively characterized successfully. This strategy provides an idea for the screening and identification of the metabolites of other TCMs.

Complexity and Automation Displays of Air Traffic Control: Literature Review and Analysis

DTIC Science & Technology

2005-04-01

Security ...Classif. (of this report) 20. Security Classif. (of...Branstrom, & Brasil , 1998), little effort has been devoted to assessing the complexity of ATC automation displays. Given the fact that many new

A concept analysis of voluntary active euthanasia.

PubMed

Guo, Fenglin

2006-01-01

Euthanasia has a wide range of classifications. Confusion exists in the application of specific concepts to various studies. To analyze the concept of voluntary active euthanasia using Walker and Avant's concept analysis method. A comprehensive literature review from various published literature and bibliographies. Clinical, ethical, and policy differences and similarities of euthanasia need to be debated openly, both within the medical profession and publicly. Awareness of the classifications about euthanasia may help nurses dealing with "end of life issues" properly.

Does Maximizing Information at the Cut Score Always Maximize Classification Accuracy and Consistency?

ERIC Educational Resources Information Center

Wyse, Adam E.; Babcock, Ben

2016-01-01

A common suggestion made in the psychometric literature for fixed-length classification tests is that one should design tests so that they have maximum information at the cut score. Designing tests in this way is believed to maximize the classification accuracy and consistency of the assessment. This article uses simulated examples to illustrate…

Posture and performance: sitting vs. standing for security screening.

PubMed

Drury, C G; Hsiao, Y L; Joseph, C; Joshi, S; Lapp, J; Pennathur, P R

2008-03-01

A classification of the literature on the effects of workplace posture on performance of different mental tasks showed few consistent patterns. A parallel classification of the complementary effect of performance on postural variables gave similar results. Because of a lack of data for signal detection tasks, an experiment was performed using 12 experienced security operators performing an X-ray baggage-screening task with three different workplace arrangements. The current workplace, sitting on a high chair viewing a screen placed on top of the X-ray machine, was compared to a standing workplace and a conventional desk-sitting workplace. No performance effects of workplace posture were found, although the experiment was able to measure performance effects of learning and body part discomfort effects of workplace posture. There are implications for the classification of posture and performance and for the justification of ergonomics improvements based on performance increases.

Classification of topological phonons in linear mechanical metamaterials

PubMed Central

Süsstrunk, Roman

2016-01-01

Topological phononic crystals, alike their electronic counterparts, are characterized by a bulk–edge correspondence where the interior of a material dictates the existence of stable surface or boundary modes. In the mechanical setup, such surface modes can be used for various applications such as wave guiding, vibration isolation, or the design of static properties such as stable floppy modes where parts of a system move freely. Here, we provide a classification scheme of topological phonons based on local symmetries. We import and adapt the classification of noninteracting electron systems and embed it into the mechanical setup. Moreover, we provide an extensive set of examples that illustrate our scheme and can be used to generate models in unexplored symmetry classes. Our work unifies the vast recent literature on topological phonons and paves the way to future applications of topological surface modes in mechanical metamaterials. PMID:27482105

Formulation design for poorly water-soluble drugs based on biopharmaceutics classification system: basic approaches and practical applications.

PubMed

Kawabata, Yohei; Wada, Koichi; Nakatani, Manabu; Yamada, Shizuo; Onoue, Satomi

2011-11-25

The poor oral bioavailability arising from poor aqueous solubility should make drug research and development more difficult. Various approaches have been developed with a focus on enhancement of the solubility, dissolution rate, and oral bioavailability of poorly water-soluble drugs. To complete development works within a limited amount of time, the establishment of a suitable formulation strategy should be a key consideration for the pharmaceutical development of poorly water-soluble drugs. In this article, viable formulation options are reviewed on the basis of the biopharmaceutics classification system of drug substances. The article describes the basic approaches for poorly water-soluble drugs, such as crystal modification, micronization, amorphization, self-emulsification, cyclodextrin complexation, and pH modification. Literature-based examples of the formulation options for poorly water-soluble compounds and their practical application to marketed products are also provided. Classification of drug candidates based on their biopharmaceutical properties can provide an indication of the difficulty of drug development works. A better understanding of the physicochemical and biopharmaceutical properties of drug substances and the limitations of each delivery option should lead to efficient formulation development for poorly water-soluble drugs. Copyright © 2011 Elsevier B.V. All rights reserved.

Investigation of physicians' attitudes concerning the implementation of international classification systems of diseases as a precondition for evidence-based policy making.

PubMed

Tsikna, Vasiliki; Siskou, Olga; Galanis, Petros; Prezerakos, Panagiotis; Kaitelidou, Daphne

2013-01-01

This study investigated the main factors affecting physicians' attitudes toward the implementation of international classification systems of diseases. A cross-sectional study was carried out during September 2010. The sample consisted of 158 physicians older than 24 years who were working in a public hospital and a private hospital in central Greece. A questionnaire was drawn up based on the relevant literature. Results indicated that younger physicians and those who worked in the public hospital were most familiar with classification systems. Female physicians and specialists with more than 10 years of experience (since qualifying as a specialist) were not particularly familiar with these systems (58 percent and 56 percent, respectively). Both having a master's degree and attending conferences or seminars had a remarkable impact on knowledge of these systems. Almost all physicians (98 percent) holding a master's degree or a PhD believed that these systems contribute to the compilation of valid statistical data. The majority of physicians would like to use these systems in the future, as long as they are provided with the appropriate training.

A Novel Detection Model and Its Optimal Features to Classify Falls from Low- and High-Acceleration Activities of Daily Life Using an Insole Sensor System

PubMed Central

Cates, Benjamin; Sim, Taeyong; Heo, Hyun Mu; Kim, Bori; Kim, Hyunggun; Mun, Joung Hwan

2018-01-01

In order to overcome the current limitations in current threshold-based and machine learning-based fall detectors, an insole system and novel fall classification model were created. Because high-acceleration activities have a high risk for falls, and because of the potential damage that is associated with falls during high-acceleration activities, four low-acceleration activities, four high-acceleration activities, and eight types of high-acceleration falls were performed by twenty young male subjects. Encompassing a total of 800 falls and 320 min of activities of daily life (ADLs), the created Support Vector Machine model’s Leave-One-Out cross-validation provides a fall detection sensitivity (0.996), specificity (1.000), and accuracy (0.999). These classification results are similar or superior to other fall detection models in the literature, while also including high-acceleration ADLs to challenge the classification model, and simultaneously reducing the burden that is associated with wearable sensors and increasing user comfort by inserting the insole system into the shoe. PMID:29673165

EEG-based recognition of video-induced emotions: selecting subject-independent feature set.

PubMed

Kortelainen, Jukka; Seppänen, Tapio

2013-01-01

Emotions are fundamental for everyday life affecting our communication, learning, perception, and decision making. Including emotions into the human-computer interaction (HCI) could be seen as a significant step forward offering a great potential for developing advanced future technologies. While the electrical activity of the brain is affected by emotions, offers electroencephalogram (EEG) an interesting channel to improve the HCI. In this paper, the selection of subject-independent feature set for EEG-based emotion recognition is studied. We investigate the effect of different feature sets in classifying person's arousal and valence while watching videos with emotional content. The classification performance is optimized by applying a sequential forward floating search algorithm for feature selection. The best classification rate (65.1% for arousal and 63.0% for valence) is obtained with a feature set containing power spectral features from the frequency band of 1-32 Hz. The proposed approach substantially improves the classification rate reported in the literature. In future, further analysis of the video-induced EEG changes including the topographical differences in the spectral features is needed.

Applicability of geomechanical classifications for estimation of strength properties in Brazilian rock masses.

PubMed

Santos, Tatiana B; Lana, Milene S; Santos, Allan E M; Silveira, Larissa R C

2017-01-01

Many authors have been proposed several correlation equations between geomechanical classifications and strength parameters. However, these correlation equations have been based in rock masses with different characteristics when compared to Brazilian rock masses. This paper aims to study the applicability of the geomechanical classifications to obtain strength parameters of three Brazilian rock masses. Four classification systems have been used; the Rock Mass Rating (RMR), the Rock Mass Quality (Q), the Geological Strength Index (GSI) and the Rock Mass Index (RMi). A strong rock mass and two soft rock masses with different degrees of weathering located in the cities of Ouro Preto and Mariana, Brazil; were selected for the study. Correlation equations were used to estimate the strength properties of these rock masses. However, such correlations do not always provide compatible results with the rock mass behavior. For the calibration of the strength values obtained through the use of classification systems, ​​stability analyses of failures in these rock masses have been done. After calibration of these parameters, the applicability of the various correlation equations found in the literature have been discussed. According to the results presented in this paper, some of these equations are not suitable for the studied rock masses.

Perspectives on Machine Learning for Classification of Schizotypy Using fMRI Data.

PubMed

Madsen, Kristoffer H; Krohne, Laerke G; Cai, Xin-Lu; Wang, Yi; Chan, Raymond C K

2018-03-15

Functional magnetic resonance imaging is capable of estimating functional activation and connectivity in the human brain, and lately there has been increased interest in the use of these functional modalities combined with machine learning for identification of psychiatric traits. While these methods bear great potential for early diagnosis and better understanding of disease processes, there are wide ranges of processing choices and pitfalls that may severely hamper interpretation and generalization performance unless carefully considered. In this perspective article, we aim to motivate the use of machine learning schizotypy research. To this end, we describe common data processing steps while commenting on best practices and procedures. First, we introduce the important role of schizotypy to motivate the importance of reliable classification, and summarize existing machine learning literature on schizotypy. Then, we describe procedures for extraction of features based on fMRI data, including statistical parametric mapping, parcellation, complex network analysis, and decomposition methods, as well as classification with a special focus on support vector classification and deep learning. We provide more detailed descriptions and software as supplementary material. Finally, we present current challenges in machine learning for classification of schizotypy and comment on future trends and perspectives.

Development and initial validation of the Classification of Early-Onset Scoliosis (C-EOS).

PubMed

Williams, Brendan A; Matsumoto, Hiroko; McCalla, Daren J; Akbarnia, Behrooz A; Blakemore, Laurel C; Betz, Randal R; Flynn, John M; Johnston, Charles E; McCarthy, Richard E; Roye, David P; Skaggs, David L; Smith, John T; Snyder, Brian D; Sponseller, Paul D; Sturm, Peter F; Thompson, George H; Yazici, Muharrem; Vitale, Michael G

2014-08-20

Early-onset scoliosis is a heterogeneous condition, with highly variable manifestations and natural history. No standardized classification system exists to describe and group patients, to guide optimal care, or to prognosticate outcomes within this population. A classification system for early-onset scoliosis is thus a necessary prerequisite to the timely evolution of care of these patients. Fifteen experienced surgeons participated in a nominal group technique designed to achieve a consensus-based classification system for early-onset scoliosis. A comprehensive list of factors important in managing early-onset scoliosis was generated using a standardized literature review, semi-structured interviews, and open forum discussion. Three group meetings and two rounds of surveying guided the selection of classification components, subgroupings, and cut-points. Initial validation of the system was conducted using an interobserver reliability assessment based on the classification of a series of thirty cases. Nominal group technique was used to identify three core variables (major curve angle, etiology, and kyphosis) with high group content validity scores. Age and curve progression ranked slightly lower. Participants evaluated the cases of thirty patients with early-onset scoliosis for reliability testing. The mean kappa value for etiology (0.64) was substantial, while the mean kappa values for major curve angle (0.95) and kyphosis (0.93) indicated almost perfect agreement. The final classification consisted of a continuous age prefix, etiology (congenital or structural, neuromuscular, syndromic, and idiopathic), major curve angle (1, 2, 3, or 4), and kyphosis (-, N, or +) variables, and an optional progression modifier (P0, P1, or P2). Utilizing formal consensus-building methods in a large group of surgeons experienced in treating early-onset scoliosis, a novel classification system for early-onset scoliosis was developed with all core components demonstrating substantial to excellent interobserver reliability. This classification system will serve as a foundation to guide ongoing research efforts and standardize communication in the clinical setting. Copyright © 2014 by The Journal of Bone and Joint Surgery, Incorporated.

A bioturbation classification of European marine infaunal invertebrates

PubMed Central

Queirós, Ana M; Birchenough, Silvana N R; Bremner, Julie; Godbold, Jasmin A; Parker, Ruth E; Romero-Ramirez, Alicia; Reiss, Henning; Solan, Martin; Somerfield, Paul J; Van Colen, Carl; Van Hoey, Gert; Widdicombe, Stephen

2013-01-01

Bioturbation, the biogenic modification of sediments through particle reworking and burrow ventilation, is a key mediator of many important geochemical processes in marine systems. In situ quantification of bioturbation can be achieved in a myriad of ways, requiring expert knowledge, technology, and resources not always available, and not feasible in some settings. Where dedicated research programmes do not exist, a practical alternative is the adoption of a trait-based approach to estimate community bioturbation potential (BPc). This index can be calculated from inventories of species, abundance and biomass data (routinely available for many systems), and a functional classification of organism traits associated with sediment mixing (less available). Presently, however, there is no agreed standard categorization for the reworking mode and mobility of benthic species. Based on information from the literature and expert opinion, we provide a functional classification for 1033 benthic invertebrate species from the northwest European continental shelf, as a tool to enable the standardized calculation of BPc in the region. Future uses of this classification table will increase the comparability and utility of large-scale assessments of ecosystem processes and functioning influenced by bioturbation (e.g., to support legislation). The key strengths, assumptions, and limitations of BPc as a metric are critically reviewed, offering guidelines for its calculation and application. PMID:24198953

Genetic programming and serial processing for time series classification.

PubMed

Alfaro-Cid, Eva; Sharman, Ken; Esparcia-Alcázar, Anna I

2014-01-01

This work describes an approach devised by the authors for time series classification. In our approach genetic programming is used in combination with a serial processing of data, where the last output is the result of the classification. The use of genetic programming for classification, although still a field where more research in needed, is not new. However, the application of genetic programming to classification tasks is normally done by considering the input data as a feature vector. That is, to the best of our knowledge, there are not examples in the genetic programming literature of approaches where the time series data are processed serially and the last output is considered as the classification result. The serial processing approach presented here fills a gap in the existing literature. This approach was tested in three different problems. Two of them are real world problems whose data were gathered for online or conference competitions. As there are published results of these two problems this gives us the chance to compare the performance of our approach against top performing methods. The serial processing of data in combination with genetic programming obtained competitive results in both competitions, showing its potential for solving time series classification problems. The main advantage of our serial processing approach is that it can easily handle very large datasets.

Mild traumatic brain injury literature review and proposed changes to classification.

PubMed

Krainin, Benjamin M; Forsten, Robert D; Kotwal, Russ S; Lutz, Robert H; Guskiewicz, Kevin M

2011-01-01

Mild traumatic brain injury (mTBI) reportedly occurs in 8-22% of U.S. servicemembers who conduct combat operations in Afghanistan and Iraq. The current definition for mTBI found in the medical literature, to include the Department of Defense (DoD) and Veterans Administration (VA) clinical practice guidelines is limited by the parameters of loss of consciousness, altered consciousness, or post-traumatic amnesia, and does not account for other constellations of potential symptoms. Although mTBI symptoms typically resolve within seven days, some servicemembers experience symptoms that continue for weeks, months, or years following an injury. Mild TBI is one of few disorders in medicine where a benign and misleading diagnostic classification is bestowed on patients at the time of injury, yet still can be associated with lifelong complications. This article comprehensively reviews the clinical literature over the past 20 years and proposes a new classification for TBI that addresses acute, sub-acute, and chronic phases, and includes neurocognitive, somatic, and psychological symptom presentation. 2011.

Pathway activity inference for multiclass disease classification through a mathematical programming optimisation framework.

PubMed

Yang, Lingjian; Ainali, Chrysanthi; Tsoka, Sophia; Papageorgiou, Lazaros G

2014-12-05

Applying machine learning methods on microarray gene expression profiles for disease classification problems is a popular method to derive biomarkers, i.e. sets of genes that can predict disease state or outcome. Traditional approaches where expression of genes were treated independently suffer from low prediction accuracy and difficulty of biological interpretation. Current research efforts focus on integrating information on protein interactions through biochemical pathway datasets with expression profiles to propose pathway-based classifiers that can enhance disease diagnosis and prognosis. As most of the pathway activity inference methods in literature are either unsupervised or applied on two-class datasets, there is good scope to address such limitations by proposing novel methodologies. A supervised multiclass pathway activity inference method using optimisation techniques is reported. For each pathway expression dataset, patterns of its constituent genes are summarised into one composite feature, termed pathway activity, and a novel mathematical programming model is proposed to infer this feature as a weighted linear summation of expression of its constituent genes. Gene weights are determined by the optimisation model, in a way that the resulting pathway activity has the optimal discriminative power with regards to disease phenotypes. Classification is then performed on the resulting low-dimensional pathway activity profile. The model was evaluated through a variety of published gene expression profiles that cover different types of disease. We show that not only does it improve classification accuracy, but it can also perform well in multiclass disease datasets, a limitation of other approaches from the literature. Desirable features of the model include the ability to control the maximum number of genes that may participate in determining pathway activity, which may be pre-specified by the user. Overall, this work highlights the potential of building pathway-based multi-phenotype classifiers for accurate disease diagnosis and prognosis problems.

Oral carcinoma after hematopoietic stem cell transplantation – a new classification based on a literature review over 30 years

PubMed Central

Kruse, Astrid LD; Grätz, Klaus W

2009-01-01

Background Patients undergoing hematopoietic stem cell transplantation (HSCT) have a higher risk of developing secondary solid tumors, in particular squamous cell carcinoma, because of several risk factors, including full-body irradiation (TBI), chemotherapy, and chronic graft versus host disease (GVHD). Based on the review presented here, a classification of oral changes is suggested in order to provide a tool to detect high-risk patients. Methods and Results The literature over the last 30 years was reviewed for development of malignoma of the oral cavity after HSCT. Overall, 64 cases were found. In 16 out of 30 cases, the tongue was the primary location, followed by the salivary gland (10 out of 30); 56.4% appeared in a latency time of 5 to 9 years after HSCT. In 76.6%, GVHD was noticed before the occurrence of oral malignancy. Premalignant changes of the oral mucosa were mucositis, xerostomia, and lichenoid changes, developing into erosive form. Conclusion All physicians involved in the treatment of post-HSCT patients should be aware of the increased risk, even after 5 years from the development of oral malignancy, in particular when oral graft versus host changes are visible. In order to develop evidence based management, screening and offer adequate therapy as early as possible in this patient group, multicenter studies, involving oncologists and head and neck surgeons, should be established. PMID:19624855

Classification of platelet concentrates (Platelet-Rich Plasma-PRP, Platelet-Rich Fibrin-PRF) for topical and infiltrative use in orthopedic and sports medicine: current consensus, clinical implications and perspectives.

PubMed

Dohan Ehrenfest, David M; Andia, Isabel; Zumstein, Matthias A; Zhang, Chang-Qing; Pinto, Nelson R; Bielecki, Tomasz

2014-01-01

Platelet concentrates for topical and infiltrative use - commonly termed Platetet-Rich Plasma (PRP) or Platelet-Rich Fibrin (PRF) - are used or tested as surgical adjuvants or regenerative medicine preparations in most medical fields, particularly in sports medicine and orthopaedic surgery. Even if these products offer interesting therapeutic perspectives, their clinical relevance is largely debated, as the literature on the topic is often confused and contradictory. The long history of these products was always associated with confusions, mostly related to the lack of consensual terminology, characterization and classification of the many products that were tested in the last 40 years. The current consensus is based on a simple classification system dividing the many products in 4 main families, based on their fibrin architecture and cell content: Pure Platelet-Rich Plasma (P-PRP), such as the PRGF-Endoret technique; Leukocyte- and Platelet-Rich Plasma (LPRP), such as Biomet GPS system; Pure Platelet-Rich Fibrin (P-PRF), such as Fibrinet; Leukocyte- and Platelet-Rich Fibrin (L-PRF), such as Intra-Spin L-PRF. The 4 main families of products present different biological signatures and mechanisms, and obvious differences for clinical applications. This classification serves as a basis for further investigations of the effects of these products. Perspectives of evolutions of this classification and terminology are also discussed, particularly concerning the impact of the cell content, preservation and activation on these products in sports medicine and orthopaedics.

The first step in the development of text mining technology for cancer risk assessment: identifying and organizing scientific evidence in risk assessment literature

PubMed Central

Korhonen, Anna; Silins, Ilona; Sun, Lin; Stenius, Ulla

2009-01-01

Background One of the most neglected areas of biomedical Text Mining (TM) is the development of systems based on carefully assessed user needs. We have recently investigated the user needs of an important task yet to be tackled by TM -- Cancer Risk Assessment (CRA). Here we take the first step towards the development of TM technology for the task: identifying and organizing the scientific evidence required for CRA in a taxonomy which is capable of supporting extensive data gathering from biomedical literature. Results The taxonomy is based on expert annotation of 1297 abstracts downloaded from relevant PubMed journals. It classifies 1742 unique keywords found in the corpus to 48 classes which specify core evidence required for CRA. We report promising results with inter-annotator agreement tests and automatic classification of PubMed abstracts to taxonomy classes. A simple user test is also reported in a near real-world CRA scenario which demonstrates along with other evaluation that the resources we have built are well-defined, accurate, and applicable in practice. Conclusion We present our annotation guidelines and a tool which we have designed for expert annotation of PubMed abstracts. A corpus annotated for keywords and document relevance is also presented, along with the taxonomy which organizes the keywords into classes defining core evidence for CRA. As demonstrated by the evaluation, the materials we have constructed provide a good basis for classification of CRA literature along multiple dimensions. They can support current manual CRA as well as facilitate the development of an approach based on TM. We discuss extending the taxonomy further via manual and machine learning approaches and the subsequent steps required to develop TM technology for the needs of CRA. PMID:19772619

A Classification System to Guide Physical Therapy Management in Huntington Disease: A Case Series.

PubMed

Fritz, Nora E; Busse, Monica; Jones, Karen; Khalil, Hanan; Quinn, Lori

2017-07-01

Individuals with Huntington disease (HD), a rare neurological disease, experience impairments in mobility and cognition throughout their disease course. The Medical Research Council framework provides a schema that can be applied to the development and evaluation of complex interventions, such as those provided by physical therapists. Treatment-based classifications, based on expert consensus and available literature, are helpful in guiding physical therapy management across the stages of HD. Such classifications also contribute to the development and further evaluation of well-defined complex interventions in this highly variable and complex neurodegenerative disease. The purpose of this case series was to illustrate the use of these classifications in the management of 2 individuals with late-stage HD. Two females, 40 and 55 years of age, with late-stage HD participated in this case series. Both experienced progressive declines in ambulatory function and balance as well as falls or fear of falling. Both individuals received daily care in the home for activities of daily living. Physical therapy Treatment-Based Classifications for HD guided the interventions and outcomes. Eight weeks of in-home balance training, strength training, task-specific practice of functional activities including transfers and walking tasks, and family/carer education were provided. Both individuals demonstrated improvements that met or exceeded the established minimal detectible change values for gait speed and Timed Up and Go performance. Both also demonstrated improvements on Berg Balance Scale and Physical Performance Test performance, with 1 of the 2 individuals exceeding the established minimal detectible changes for both tests. Reductions in fall risk were evident in both cases. These cases provide proof-of-principle to support use of treatment-based classifications for physical therapy management in individuals with HD. Traditional classification of early-, mid-, and late-stage disease progression may not reflect patients' true capabilities; those with late-stage HD may be as responsive to interventions as those at an earlier disease stage.Video Abstract available for additional insights from the authors (see Supplemental Digital Content 1, available at: http://links.lww.com/JNPT/A172).

Genomic profiling using array comparative genomic hybridization define distinct subtypes of diffuse large b-cell lymphoma: a review of the literature

PubMed Central

2012-01-01

Diffuse large B-cell lymphoma (DLBCL) is the most common type of non-Hodgkin Lymphoma comprising of greater than 30% of adult non-Hodgkin Lymphomas. DLBCL represents a diverse set of lymphomas, defined as diffuse proliferation of large B lymphoid cells. Numerous cytogenetic studies including karyotypes and fluorescent in situ hybridization (FISH), as well as morphological, biological, clinical, microarray and sequencing technologies have attempted to categorize DLBCL into morphological variants, molecular and immunophenotypic subgroups, as well as distinct disease entities. Despite such efforts, most lymphoma remains undistinguishable and falls into DLBCL, not otherwise specified (DLBCL-NOS). The advent of microarray-based studies (chromosome, RNA, gene expression, etc) has provided a plethora of high-resolution data that could potentially facilitate the finer classification of DLBCL. This review covers the microarray data currently published for DLBCL. We will focus on these types of data; 1) array based CGH; 2) classical CGH; and 3) gene expression profiling studies. The aims of this review were three-fold: (1) to catalog chromosome loci that are present in at least 20% or more of distinct DLBCL subtypes; a detailed list of gains and losses for different subtypes was generated in a table form to illustrate specific chromosome loci affected in selected subtypes; (2) to determine common and distinct copy number alterations among the different subtypes and based on this information, characteristic and similar chromosome loci for the different subtypes were depicted in two separate chromosome ideograms; and, (3) to list re-classified subtypes and those that remained indistinguishable after review of the microarray data. To the best of our knowledge, this is the first effort to compile and review available literatures on microarray analysis data and their practical utility in classifying DLBCL subtypes. Although conventional cytogenetic methods such as Karyotypes and FISH have played a major role in classification schemes of lymphomas, better classification models are clearly needed to further understanding the biology, disease outcome and therapeutic management of DLBCL. In summary, microarray data reviewed here can provide better subtype specific classifications models for DLBCL. PMID:22967872

An efficient diagnosis system for Parkinson's disease using kernel-based extreme learning machine with subtractive clustering features weighting approach.

PubMed

Ma, Chao; Ouyang, Jihong; Chen, Hui-Ling; Zhao, Xue-Hua

2014-01-01

A novel hybrid method named SCFW-KELM, which integrates effective subtractive clustering features weighting and a fast classifier kernel-based extreme learning machine (KELM), has been introduced for the diagnosis of PD. In the proposed method, SCFW is used as a data preprocessing tool, which aims at decreasing the variance in features of the PD dataset, in order to further improve the diagnostic accuracy of the KELM classifier. The impact of the type of kernel functions on the performance of KELM has been investigated in detail. The efficiency and effectiveness of the proposed method have been rigorously evaluated against the PD dataset in terms of classification accuracy, sensitivity, specificity, area under the receiver operating characteristic (ROC) curve (AUC), f-measure, and kappa statistics value. Experimental results have demonstrated that the proposed SCFW-KELM significantly outperforms SVM-based, KNN-based, and ELM-based approaches and other methods in the literature and achieved highest classification results reported so far via 10-fold cross validation scheme, with the classification accuracy of 99.49%, the sensitivity of 100%, the specificity of 99.39%, AUC of 99.69%, the f-measure value of 0.9964, and kappa value of 0.9867. Promisingly, the proposed method might serve as a new candidate of powerful methods for the diagnosis of PD with excellent performance.

An Efficient Diagnosis System for Parkinson's Disease Using Kernel-Based Extreme Learning Machine with Subtractive Clustering Features Weighting Approach

PubMed Central

Ma, Chao; Ouyang, Jihong; Chen, Hui-Ling; Zhao, Xue-Hua

2014-01-01

A novel hybrid method named SCFW-KELM, which integrates effective subtractive clustering features weighting and a fast classifier kernel-based extreme learning machine (KELM), has been introduced for the diagnosis of PD. In the proposed method, SCFW is used as a data preprocessing tool, which aims at decreasing the variance in features of the PD dataset, in order to further improve the diagnostic accuracy of the KELM classifier. The impact of the type of kernel functions on the performance of KELM has been investigated in detail. The efficiency and effectiveness of the proposed method have been rigorously evaluated against the PD dataset in terms of classification accuracy, sensitivity, specificity, area under the receiver operating characteristic (ROC) curve (AUC), f-measure, and kappa statistics value. Experimental results have demonstrated that the proposed SCFW-KELM significantly outperforms SVM-based, KNN-based, and ELM-based approaches and other methods in the literature and achieved highest classification results reported so far via 10-fold cross validation scheme, with the classification accuracy of 99.49%, the sensitivity of 100%, the specificity of 99.39%, AUC of 99.69%, the f-measure value of 0.9964, and kappa value of 0.9867. Promisingly, the proposed method might serve as a new candidate of powerful methods for the diagnosis of PD with excellent performance. PMID:25484912

Filing Reprints: A Simple System For The Family Physician

PubMed Central

Berner, Mark

1978-01-01

This flexible method of filing medical literature without using cards is based on the International Classification of Health Problems in Primary Care. 1Articles, reprints, notes of lectures and rounds, etc. are filed in manilla folders according to a few simple guidelines. This system has proved to be practical and efficient, can be modified for individual needs, and once established requires little time to maintain. PMID:20469289

Glyphosate: environmental contamination, toxicity and potential risks to human health via food contamination.

PubMed

Bai, Shahla Hosseini; Ogbourne, Steven M

2016-10-01

Glyphosate has been the most widely used herbicide during the past three decades. The US Environmental Protection Agency (EPA) classifies glyphosate as 'practically non-toxic and not an irritant' under the acute toxicity classification system. This classification is based primarily on toxicity data and due to its unique mode of action via a biochemical pathway that only exists in a small number of organisms that utilise the shikimic acid pathway to produce amino acids, most of which are green plants. This classification is supported by the majority of scientific literature on the toxic effects of glyphosate. However, in 2005, the Food and Agriculture Organisation (FAO) reported that glyphosate and its major metabolite, aminomethylphosphonic acid (AMPA), are of potential toxicological concern, mainly as a result of accumulation of residues in the food chain. The FAO further states that the dietary risk of glyphosate and AMPA is unlikely if the maximum daily intake of 1 mg kg(-1) body weight (bw) is not exceeded. Research has now established that glyphosate can persist in the environment, and therefore, assessments of the health risks associated with glyphosate are more complicated than suggested by acute toxicity data that relate primarily to accidental high-rate exposure. We have used recent literature to assess the possible risks associated with the presence of glyphosate residues in food and the environment.

Subtyping of polyposis nasi: phenotypes, endotypes and comorbidities.

PubMed

Koennecke, Michael; Klimek, Ludger; Mullol, Joaquim; Gevaert, Philippe; Wollenberg, Barbara

2018-01-01

Chronic rhinosinusitis (CRS) is a heterogeneous, multifactorial inflammatory disease of the nasal and paranasal mucosa. It has not been possible to date to develop an internationally standardized, uniform classification for this disorder. A phenotype classification according to CRS with (CRSwNP) and without polyposis (CRSsNP) is usually made. However, a large number of studies have shown that there are also different endotypes of CRS within these phenotypes, with different pathophysiologies of chronic inflammation of the nasal mucosa. This review describes the central immunological processes in nasal polyps, as well as the impact of related diseases on the inflammatory profile of nasal polyps. The current knowledge on the immunological and molecular processes of CRS, in particular CRSwNP and its classification into specific endotypes, was put together by means of a structured literature search in Medline, PubMed, the national and international guideline registers, and the Cochrane Library. Based on the current literature, the different immunological processes in CRS and nasal polyps were elaborated and a graphical representation in the form of an immunological network developed. In addition, different inflammatory profiles can be found in CRSwNP depending on related diseases, such as bronchial asthma, cystic fibrosis (CF), or NASID-Exacerbated Respiratory Disease (N‑ERD). The identification of different endotypes of CRSwNP may help to improve diagnostics and develop novel individual treatment approaches in CRSwNP.

The new WHO 2016 classification of brain tumors-what neurosurgeons need to know.

PubMed

Banan, Rouzbeh; Hartmann, Christian

2017-03-01

The understanding of molecular alterations of tumors has severely changed the concept of classification in all fields of pathology. The availability of high-throughput technologies such as next-generation sequencing allows for a much more precise definition of tumor entities. Also in the field of brain tumors a dramatic increase of knowledge has occurred over the last years partially calling into question the purely morphologically based concepts that were used as exclusive defining criteria in the WHO 2007 classification. Review of the WHO 2016 classification of brain tumors as well as a search and review of publications in the literature relevant for brain tumor classification from 2007 up to now. The idea of incorporating the molecular features in classifying tumors of the central nervous system led the authors of the new WHO 2016 classification to encounter inevitable conceptual problems, particularly with respect to linking morphology to molecular alterations. As a solution they introduced the concept of a "layered diagnosis" to the classification of brain tumors that still allows at a lower level a purely morphologically based diagnosis while partially forcing the incorporation of molecular characteristics for an "integrated diagnosis" at the highest diagnostic level. In this context the broad availability of molecular assays was debated. On the one hand molecular antibodies specifically targeting mutated proteins should be available in nearly all neuropathological laboratories. On the other hand, different high-throughput assays are accessible only in few first-world neuropathological institutions. As examples oligodendrogliomas are now primarily defined by molecular characteristics since the required assays are generally established, whereas molecular grouping of ependymomas, found to clearly outperform morphologically based tumor interpretation, was rejected from inclusion in the WHO 2016 classification because the required assays are currently only established in a small number of institutions. In summary, while neuropathologists have now encountered various challenges in the transitional phase from the previous WHO 2007 version to the new WHO 2016 classification of brain tumors, clinical neurooncologists now face many new diagnoses allowing a clearly improved understanding that could offer them more effective therapeutic opportunities in neurooncological treatment. The new WHO 2016 classification presumably presents the highest number of modifications since the initial WHO classification of 1979 and thereby forces all professionals in the field of neurooncology to intensively understand the new concepts. This review article aims to present the basic concepts of the new WHO 2016 brain tumor classification for neurosurgeons with a focus on neurooncology.

Discovering disease-disease associations by fusing systems-level molecular data

PubMed Central

Žitnik, Marinka; Janjić, Vuk; Larminie, Chris; Zupan, Blaž; Pržulj, Nataša

2013-01-01

The advent of genome-scale genetic and genomic studies allows new insight into disease classification. Recently, a shift was made from linking diseases simply based on their shared genes towards systems-level integration of molecular data. Here, we aim to find relationships between diseases based on evidence from fusing all available molecular interaction and ontology data. We propose a multi-level hierarchy of disease classes that significantly overlaps with existing disease classification. In it, we find 14 disease-disease associations currently not present in Disease Ontology and provide evidence for their relationships through comorbidity data and literature curation. Interestingly, even though the number of known human genetic interactions is currently very small, we find they are the most important predictor of a link between diseases. Finally, we show that omission of any one of the included data sources reduces prediction quality, further highlighting the importance in the paradigm shift towards systems-level data fusion. PMID:24232732

Discovering disease-disease associations by fusing systems-level molecular data.

PubMed

Žitnik, Marinka; Janjić, Vuk; Larminie, Chris; Zupan, Blaž; Pržulj, Nataša

2013-11-15

The advent of genome-scale genetic and genomic studies allows new insight into disease classification. Recently, a shift was made from linking diseases simply based on their shared genes towards systems-level integration of molecular data. Here, we aim to find relationships between diseases based on evidence from fusing all available molecular interaction and ontology data. We propose a multi-level hierarchy of disease classes that significantly overlaps with existing disease classification. In it, we find 14 disease-disease associations currently not present in Disease Ontology and provide evidence for their relationships through comorbidity data and literature curation. Interestingly, even though the number of known human genetic interactions is currently very small, we find they are the most important predictor of a link between diseases. Finally, we show that omission of any one of the included data sources reduces prediction quality, further highlighting the importance in the paradigm shift towards systems-level data fusion.

Plant landscape design simulating natural community by using AHP method based on TWINSPAN classification

NASA Astrophysics Data System (ADS)

Wang, Li Han

2018-06-01

Taking the forest vegetation in Zijin Mountain (Purple Mountain) Area of Nanjing as the research object, based on the simulation natural and semi natural plant communities, the systematic research on the construction of Nanjing regional plant landscape is carried out by the method such as literature and theory, investigation and evaluation, discussion and reference. On the basis of TWINSPAN classification, the species composition (flora and geographical composition), community structure, species diversity, interspecific relationship and ecological niche of Zijin Mountain natural vegetation are studied and analyzed as a basis for simulation design and planting. Then, from the three levels of ornamental value, resource development and utilization potential and biological characteristics, a comprehensive evaluation system used for wild ornamental plant resources in Zijin Mountain is built. Finally, some suggestions on the planting species of deep forest vegetation in Zijin Mountain are put forward.

Correlation Equations for Condensing Heat Exchangers Based on an Algorithmic Performance-Data Classification

NASA Astrophysics Data System (ADS)

Pacheco-Vega, Arturo

2016-09-01

In this work a new set of correlation equations is developed and introduced to accurately describe the thermal performance of compact heat exchangers with possible condensation. The feasible operating conditions for the thermal system correspond to dry- surface, dropwise condensation, and film condensation. Using a prescribed form for each condition, a global regression analysis for the best-fit correlation to experimental data is carried out with a simulated annealing optimization technique. The experimental data were taken from the literature and algorithmically classified into three groups -related to the possible operating conditions- with a previously-introduced Gaussian-mixture-based methodology. Prior to their use in the analysis, the correct data classification was assessed and confirmed via artificial neural networks. Predictions from the correlations obtained for the different conditions are within the uncertainty of the experiments and substantially more accurate than those commonly used.

2016 Classification Criteria for Macrophage Activation Syndrome Complicating Systemic Juvenile Idiopathic Arthritis: A European League Against Rheumatism/American College of Rheumatology/Paediatric Rheumatology International Trials Organisation Collaborative Initiative.

PubMed

Ravelli, Angelo; Minoia, Francesca; Davì, Sergio; Horne, AnnaCarin; Bovis, Francesca; Pistorio, Angela; Aricò, Maurizio; Avcin, Tadej; Behrens, Edward M; De Benedetti, Fabrizio; Filipovic, Lisa; Grom, Alexei A; Henter, Jan-Inge; Ilowite, Norman T; Jordan, Michael B; Khubchandani, Raju; Kitoh, Toshiyuki; Lehmberg, Kai; Lovell, Daniel J; Miettunen, Paivi; Nichols, Kim E; Ozen, Seza; Pachlopnik Schmid, Jana; Ramanan, Athimalaipet V; Russo, Ricardo; Schneider, Rayfel; Sterba, Gary; Uziel, Yosef; Wallace, Carol; Wouters, Carine; Wulffraat, Nico; Demirkaya, Erkan; Brunner, Hermine I; Martini, Alberto; Ruperto, Nicolino; Cron, Randy Q

2016-03-01

To develop criteria for the classification of macrophage activation syndrome (MAS) in patients with systemic juvenile idiopathic arthritis (JIA). A multistep process, based on a combination of expert consensus and analysis of real patient data, was conducted. A panel of 28 experts was first asked to classify 428 patient profiles as having or not having MAS, based on clinical and laboratory features at the time of disease onset. The 428 profiles comprised 161 patients with systemic JIA-associated MAS and 267 patients with a condition that could potentially be confused with MAS (active systemic JIA without evidence of MAS, or systemic infection). Next, the ability of candidate criteria to classify individual patients as having MAS or not having MAS was assessed by evaluating the agreement between the classification yielded using the criteria and the consensus classification of the experts. The final criteria were selected in a consensus conference. Experts achieved consensus on the classification of 391 of the 428 patient profiles (91.4%). A total of 982 candidate criteria were tested statistically. The 37 best-performing criteria and 8 criteria obtained from the literature were evaluated at the consensus conference. During the conference, 82% consensus among experts was reached on the final MAS classification criteria. In validation analyses, these criteria had a sensitivity of 0.73 and a specificity of 0.99. Agreement between the classification (MAS or not MAS) obtained using the criteria and the original diagnosis made by the treating physician was high (κ = 0.76). We have developed a set of classification criteria for MAS complicating systemic JIA and provided preliminary evidence of its validity. Use of these criteria will potentially improve understanding of MAS in systemic JIA and enhance efforts to discover effective therapies, by ensuring appropriate patient enrollment in studies. © 2015, American College of Rheumatology.

Classification of probability densities on the basis of Pearson?s curves with application to coronal heating simulations

NASA Astrophysics Data System (ADS)

Podladchikova, O.; Lefebvre, B.; Krasnoselskikh, V.; Podladchikov, V.

An important task for the problem of coronal heating is to produce reliable evaluation of the statistical properties of energy release and eruptive events such as micro-and nanoflares in the solar corona. Different types of distributions for the peak flux, peak count rate measurements, pixel intensities, total energy flux or emission measures increases or waiting times have appeared in the literature. This raises the question of a precise evaluation and classification of such distributions. For this purpose, we use the method proposed by K. Pearson at the beginning of the last century, based on the relationship between the first 4 moments of the distribution. Pearson's technique encompasses and classifies a broad range of distributions, including some of those which have appeared in the literature about coronal heating. This technique is successfully applied to simulated data from the model of Krasnoselskikh et al. (2002). It allows to provide successful fits to the empirical distributions of the dissipated energy, and to classify them as a function of model parameters such as dissipation mechanisms and threshold.

"My Feelings": Power, Politics and Childhood Subjectivities

ERIC Educational Resources Information Center

Tesar, Marek

2014-01-01

This article focuses on the production of children's literature in New Zealand. It problematizes the current practices of releasing and distributing children's literature, and explores these practices as technologies of control through processes of censorship and classification set by government agencies such as the Office for Film and Literature.…

46 CFR 169.107 - Definitions.

Code of Federal Regulations, 2012 CFR

2012-10-01

... under section 501(a) of such Code, as now or hereafter amended. Recognized Classification Society means the American Bureau of Shipping or other classification society recognized by the Commandant. Rules of..., oceanography, other nautical and marine sciences, and maritime history and literature. In conjunction with any...

Relationships among classes of self-oscillating transistor parallel inverters. [for power conditioning applications

NASA Technical Reports Server (NTRS)

Wilson, T. G.; Lee, F. C. Y.; Burns, W. W., III; Owen, H. A., Jr.

1975-01-01

It recently has been shown in the literature that many dc-to-square-wave parallel inverters which are widely used in power-conditioning applications can be grouped into one of two families. Each family is characterized by an equivalent RLC network. Based on this approach, a classification procedure is presented for self-oscillating parallel inverters which makes evident natural relationships which exist between various inverter configurations. By utilizing concepts from the basic theory of negative resistance oscillators and the principle of duality as applied to nonlinear networks, a chain of relationships is established which enables a methodical transfer of knowledge gained about one family of inverters to any of the other families in the classification array.

GA(M)E-QSAR: a novel, fully automatic genetic-algorithm-(meta)-ensembles approach for binary classification in ligand-based drug design.

PubMed

Pérez-Castillo, Yunierkis; Lazar, Cosmin; Taminau, Jonatan; Froeyen, Mathy; Cabrera-Pérez, Miguel Ángel; Nowé, Ann

2012-09-24

Computer-aided drug design has become an important component of the drug discovery process. Despite the advances in this field, there is not a unique modeling approach that can be successfully applied to solve the whole range of problems faced during QSAR modeling. Feature selection and ensemble modeling are active areas of research in ligand-based drug design. Here we introduce the GA(M)E-QSAR algorithm that combines the search and optimization capabilities of Genetic Algorithms with the simplicity of the Adaboost ensemble-based classification algorithm to solve binary classification problems. We also explore the usefulness of Meta-Ensembles trained with Adaboost and Voting schemes to further improve the accuracy, generalization, and robustness of the optimal Adaboost Single Ensemble derived from the Genetic Algorithm optimization. We evaluated the performance of our algorithm using five data sets from the literature and found that it is capable of yielding similar or better classification results to what has been reported for these data sets with a higher enrichment of active compounds relative to the whole actives subset when only the most active chemicals are considered. More important, we compared our methodology with state of the art feature selection and classification approaches and found that it can provide highly accurate, robust, and generalizable models. In the case of the Adaboost Ensembles derived from the Genetic Algorithm search, the final models are quite simple since they consist of a weighted sum of the output of single feature classifiers. Furthermore, the Adaboost scores can be used as ranking criterion to prioritize chemicals for synthesis and biological evaluation after virtual screening experiments.

Elbow instability: Are we able to classify it? Review of the literature and proposal of an all-inclusive classification system.

PubMed

Marinelli, A; Guerra, E; Rotini, R

2016-12-01

In the recent years, considerable improvements have come in biomechanical knowledge about the role of elbow stabilizers. In particular, the complex interactions among the different stabilizers when injured at the same time have been better understood. Anyway, uncertainties about both nomenclature and classification still exist in the definition of the different patterns of instability. The authors examine the literature of the last 130 years about elbow instability classification, analyzing the intuitions and the value of each of them. However, because of the lack of a satisfactory classification, in 2015 a working group has been created inside SICSeG (Italian Society of Shoulder and Elbow Surgery) with the aim of defining an exhaustive classification as simple, complete and reproducible as possible. A new all-inclusive elbow instability classification is proposed. This classification considers two main parameters: timing (acute and chronic forms) and involved stabilizers (simple and complex forms), and four secondary parameters: etiology (traumatic, rheumatic, congenital…), the involved joint (radius and ulna as a single unit articulating with the humerus or the proximal radio-ulnar joint), the degree of displacement (dislocation or subluxation) and the mechanism of instability or dislocation (PLRI, PMRI, direct axial loading, pure varus or valgus stress). This classification is at the same time complete enough to include all the instability patterns and practical enough to be effectively used in the clinical practice. This classification can help in defining a shared language, can improve our understanding of the disorder, reduce misunderstanding of diagnosis and improve comparison among different case series.

Chicago Classification Criteria of Esophageal Motility Disorders Defined in High Resolution Esophageal Pressure Topography (EPT)†

PubMed Central

Bredenoord, Albert J; Fox, Mark; Kahrilas, Peter J; Pandolfino, John E; Schwizer, Werner; Smout, AJPM; Conklin, Jeffrey L; Cook, Ian J; Gyawali, Prakash; Hebbard, Geoffrey; Holloway, Richard H; Ke, Meiyun; Keller, Jutta; Mittal, Ravinder K; Peters, Jeff; Richter, Joel; Roman, Sabine; Rommel, Nathalie; Sifrim, Daniel; Tutuian, Radu; Valdovinos, Miguel; Vela, Marcelo F; Zerbib, Frank

2011-01-01

Background The Chicago Classification of esophageal motility was developed to facilitate the interpretation of clinical high resolution esophageal pressure topography (EPT) studies, concurrent with the widespread adoption of this technology into clinical practice. The Chicago Classification has been, and will continue to be, an evolutionary process, molded first by published evidence pertinent to the clinical interpretation of high resolution manometry (HRM) studies and secondarily by group experience when suitable evidence is lacking. Methods This publication summarizes the state of our knowledge as of the most recent meeting of the International High Resolution Manometry Working Group in Ascona, Switzerland in April 2011. The prior iteration of the Chicago Classification was updated through a process of literature analysis and discussion. Key Results The major changes in this document from the prior iteration are largely attributable to research studies published since the prior iteration, in many cases research conducted in response to prior deliberations of the International High Resolution Manometry Working Group. The classification now includes criteria for subtyping achalasia, EGJ outflow obstruction, motility disorders not observed in normal subjects (Distal esophageal spasm, Hypercontractile esophagus, and Absent peristalsis), and statistically defined peristaltic abnormalities (Weak peristalsis, Frequent failed peristalsis, Rapid contractions with normal latency, and Hypertensive peristalsis). Conclusions & Inferences The Chicago Classification is an algorithmic scheme for diagnosis of esophageal motility disorders from clinical EPT studies. Moving forward, we anticipate continuing this process with increased emphasis placed on natural history studies and outcome data based on the classification. PMID:22248109

Chicago classification criteria of esophageal motility disorders defined in high resolution esophageal pressure topography.

PubMed

Bredenoord, A J; Fox, M; Kahrilas, P J; Pandolfino, J E; Schwizer, W; Smout, A J P M

2012-03-01

The Chicago Classification of esophageal motility was developed to facilitate the interpretation of clinical high resolution esophageal pressure topography (EPT) studies, concurrent with the widespread adoption of this technology into clinical practice. The Chicago Classification has been an evolutionary process, molded first by published evidence pertinent to the clinical interpretation of high resolution manometry (HRM) studies and secondarily by group experience when suitable evidence is lacking. This publication summarizes the state of our knowledge as of the most recent meeting of the International High Resolution Manometry Working Group in Ascona, Switzerland in April 2011. The prior iteration of the Chicago Classification was updated through a process of literature analysis and discussion. The major changes in this document from the prior iteration are largely attributable to research studies published since the prior iteration, in many cases research conducted in response to prior deliberations of the International High Resolution Manometry Working Group. The classification now includes criteria for subtyping achalasia, EGJ outflow obstruction, motility disorders not observed in normal subjects (Distal esophageal spasm, Hypercontractile esophagus, and Absent peristalsis), and statistically defined peristaltic abnormalities (Weak peristalsis, Frequent failed peristalsis, Rapid contractions with normal latency, and Hypertensive peristalsis). The Chicago Classification is an algorithmic scheme for diagnosis of esophageal motility disorders from clinical EPT studies. Moving forward, we anticipate continuing this process with increased emphasis placed on natural history studies and outcome data based on the classification. © 2012 Blackwell Publishing Ltd.

Summary of the NICHD-BPCA Pediatric Formulation Initiatives Workshop-Pediatric Biopharmaceutics Classification System (PBCS) Working Group

PubMed Central

Abdel-Rahman, Susan; Amidon, Gordon L.; Kaul, Ajay; Lukacova, Viera; Vinks, Alexander A.; Knipp, Gregory

2012-01-01

The Biopharmaceutics Classification System (BCS) allows compounds to be classified based on their in vitro solubility and intestinal permeability. The BCS has found widespread use in the pharmaceutical community as an enabling guide for the rational selection of compounds, formulation for clinical advancement and generic biowaivers. The Pediatric Biopharmaceutics Classification System (PBCS) working group was convened to consider the possibility of developing an analogous pediatric based classification system. Since there are distinct developmental differences that can alter intestinal contents, volumes, permeability and potentially biorelevant solubilities at the different ages, the PBCS working group focused on identifying age specific issues that would need to be considered in establishing a flexible, yet rigorous PBCS. Objective To summarize the findings of the PBCS working group and provide insights into considerations required for the development of a pediatric based biopharmaceutics classification system. Methods Through several meetings conducted both at The Eunice Kennedy Shriver National Institute of Child Health, Human Development (NICHD)-US Pediatric Formulation Initiative (PFI) workshop (November 2011) and via teleconferences, the PBCS working group considered several high level questions that were raised to frame the classification system. In addition, the PBCS working group identified a number of knowledge gaps that would need to be addressed in order to develop a rigorous PBCS. Results It was determined that for a PBCS to be truly meaningful, it would need to be broken down into several different age groups that would account for developmental changes in intestinal permeability, luminal contents, and gastrointestinal transit. Several critical knowledge gaps where identified including: 1) a lack of fully understanding the ontogeny of drug metabolizing enzymes and transporters along the gastrointestinal (GI) tract, in the liver and in the kidney; 2) an incomplete understanding of age-based changes in the GI, liver and kidney physiology; 3) a clear need to better understand age-based intestinal permeability and fraction absorbed required to develop the PBCS; 4) a clear need for the development and organization of pediatric tissue biobanks to serve as a source for ontogenic research; and 5) a lack of literature published in age-based pediatric pharmacokinetics in order to build Physiologically- and Population-Based Pharmacokinetic (PBPK) databases. Conclusions To begin the process of establishing a PBPK model, ten pediatric therapeutic agents were selected (based on their adult BCS classifications). Those agents should be targeted for additional research in the future. The PBCS working group also identified several areas where a greater emphasis on research is needed to enable the development of a PBCS. PMID:23149009

Consensus classification of posterior cortical atrophy

PubMed Central

Crutch, Sebastian J.; Schott, Jonathan M.; Rabinovici, Gil D.; Murray, Melissa; Snowden, Julie S.; van der Flier, Wiesje M.; Dickerson, Bradford C.; Vandenberghe, Rik; Ahmed, Samrah; Bak, Thomas H.; Boeve, Bradley F.; Butler, Christopher; Cappa, Stefano F.; Ceccaldi, Mathieu; de Souza, Leonardo Cruz; Dubois, Bruno; Felician, Olivier; Galasko, Douglas; Graff-Radford, Jonathan; Graff-Radford, Neill R.; Hof, Patrick R.; Krolak-Salmon, Pierre; Lehmann, Manja; Magnin, Eloi; Mendez, Mario F.; Nestor, Peter J.; Onyike, Chiadi U.; Pelak, Victoria S.; Pijnenburg, Yolande; Primativo, Silvia; Rossor, Martin N.; Ryan, Natalie S.; Scheltens, Philip; Shakespeare, Timothy J.; González, Aida Suárez; Tang-Wai, David F.; Yong, Keir X. X.; Carrillo, Maria; Fox, Nick C.

2017-01-01

Introduction A classification framework for posterior cortical atrophy (PCA) is proposed to improve the uniformity of definition of the syndrome in a variety of research settings. Methods Consensus statements about PCA were developed through a detailed literature review, the formation of an international multidisciplinary working party which convened on four occasions, and a Web-based quantitative survey regarding symptom frequency and the conceptualization of PCA. Results A three-level classification framework for PCA is described comprising both syndrome- and disease-level descriptions. Classification level 1 (PCA) defines the core clinical, cognitive, and neuroimaging features and exclusion criteria of the clinico-radiological syndrome. Classification level 2 (PCA-pure, PCA-plus) establishes whether, in addition to the core PCA syndrome, the core features of any other neurodegenerative syndromes are present. Classification level 3 (PCA attributable to AD [PCA-AD], Lewy body disease [PCA-LBD], corticobasal degeneration [PCA-CBD], prion disease [PCA-prion]) provides a more formal determination of the underlying cause of the PCA syndrome, based on available pathophysiological biomarker evidence. The issue of additional syndrome-level descriptors is discussed in relation to the challenges of defining stages of syndrome severity and characterizing phenotypic heterogeneity within the PCA spectrum. Discussion There was strong agreement regarding the definition of the core clinico-radiological syndrome, meaning that the current consensus statement should be regarded as a refinement, development, and extension of previous single-center PCA criteria rather than any wholesale alteration or redescription of the syndrome. The framework and terminology may facilitate the interpretation of research data across studies, be applicable across a broad range of research scenarios (e.g., behavioral interventions, pharmacological trials), and provide a foundation for future collaborative work. PMID:28259709

Consensus classification of posterior cortical atrophy.

PubMed

Crutch, Sebastian J; Schott, Jonathan M; Rabinovici, Gil D; Murray, Melissa; Snowden, Julie S; van der Flier, Wiesje M; Dickerson, Bradford C; Vandenberghe, Rik; Ahmed, Samrah; Bak, Thomas H; Boeve, Bradley F; Butler, Christopher; Cappa, Stefano F; Ceccaldi, Mathieu; de Souza, Leonardo Cruz; Dubois, Bruno; Felician, Olivier; Galasko, Douglas; Graff-Radford, Jonathan; Graff-Radford, Neill R; Hof, Patrick R; Krolak-Salmon, Pierre; Lehmann, Manja; Magnin, Eloi; Mendez, Mario F; Nestor, Peter J; Onyike, Chiadi U; Pelak, Victoria S; Pijnenburg, Yolande; Primativo, Silvia; Rossor, Martin N; Ryan, Natalie S; Scheltens, Philip; Shakespeare, Timothy J; Suárez González, Aida; Tang-Wai, David F; Yong, Keir X X; Carrillo, Maria; Fox, Nick C

2017-08-01

A classification framework for posterior cortical atrophy (PCA) is proposed to improve the uniformity of definition of the syndrome in a variety of research settings. Consensus statements about PCA were developed through a detailed literature review, the formation of an international multidisciplinary working party which convened on four occasions, and a Web-based quantitative survey regarding symptom frequency and the conceptualization of PCA. A three-level classification framework for PCA is described comprising both syndrome- and disease-level descriptions. Classification level 1 (PCA) defines the core clinical, cognitive, and neuroimaging features and exclusion criteria of the clinico-radiological syndrome. Classification level 2 (PCA-pure, PCA-plus) establishes whether, in addition to the core PCA syndrome, the core features of any other neurodegenerative syndromes are present. Classification level 3 (PCA attributable to AD [PCA-AD], Lewy body disease [PCA-LBD], corticobasal degeneration [PCA-CBD], prion disease [PCA-prion]) provides a more formal determination of the underlying cause of the PCA syndrome, based on available pathophysiological biomarker evidence. The issue of additional syndrome-level descriptors is discussed in relation to the challenges of defining stages of syndrome severity and characterizing phenotypic heterogeneity within the PCA spectrum. There was strong agreement regarding the definition of the core clinico-radiological syndrome, meaning that the current consensus statement should be regarded as a refinement, development, and extension of previous single-center PCA criteria rather than any wholesale alteration or redescription of the syndrome. The framework and terminology may facilitate the interpretation of research data across studies, be applicable across a broad range of research scenarios (e.g., behavioral interventions, pharmacological trials), and provide a foundation for future collaborative work. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Bimanual Fine Motor Function (BFMF) Classification in Children with Cerebral Palsy: Aspects of Construct and Content Validity.

PubMed

Elvrum, Ann-Kristin G; Andersen, Guro L; Himmelmann, Kate; Beckung, Eva; Öhrvall, Ann-Marie; Lydersen, Stian; Vik, Torstein

2016-01-01

The Bimanual Fine Motor Function (BFMF) is currently the principal classification of hand function recorded by the Surveillance of Cerebral Palsy in Europe (SCPE) register. The BFMF is used in a number of epidemiological studies, but has not yet been validated. To examine aspects of construct and content validity of the BFMF. Construct validity of the BFMF was assessed by comparison with the Manual Ability Classification System (MACS) using register-based data from 539 children born 1999-2003 (304 boys; 4-12 years). The high correlation with the MACS (Spearman's rho = 0.89, CI: 0.86-0.91, p<.001) supports construct validity of the BFMF. The content of the BFMF was appraised through literature review, and by using the ICF-CY as a framework to compare the BFMF and MACS. The items hold, grasp and manipulate were found to be relevant to describe increasingly advanced fine motor abilities in children with CP, but the description of the BFMF does not state whether it is a classification of fine motor capacity or performance. Our results suggest that the BFMF may provide complementary information to the MACS regarding fine motor function and actual use of the hands, particularly if used as a classification of fine motor capacity.

The Fugitive Literature of Acid Rain: Making Use of Nonconventional Information Sources in a Vertical File.

ERIC Educational Resources Information Center

Lovenburg, Susan L.; Stoss, Frederick W.

1988-01-01

Discusses the advantages of vertical file collections for nonconventional literature, and describes the classification scheme used for fugitive literature by the Acid Rain Information Clearinghouse at the Center for Environmental Information. An annotated list of organizations and examples of titles they offer is provided. (8 notes with…

Patients' support for health information exchange: a literature review and classification of key factors.

PubMed

Esmaeilzadeh, Pouyan; Sambasivan, Murali

2017-04-04

Literature indicates that one of the most important factors affecting the widespread adoption of Health Information Exchange (HIE) is patient support and endorsement. In order to reap all the expected benefits of HIE, patients' acceptance of technology is a challenge that is not fully studied. There are a few studies which have focused on requirements of electronic medical information exchange from consumers' views and expectations. This study is aimed at reviewing the literature to articulate factors that affect patients to support HIE efforts. A literature review of current studies addressing patients' views on HIE from 2005 was undertaken. Five electronic research databases (Science Direct, PubMed, Web of Science, CINAHL, and Academic Search Premiere) were searched to retrieve articles reporting pros and cons of HIE from patients' opinion. One hundred and ninety six articles were initially retrieved from the databases. Out of 196, 36 studies met the inclusion criteria and were fully reviewed. Our findings indicate that patient's attitude toward HIE is affected by seven main factors: perceived benefits, perceived concerns, patient characteristics, patient participation level in HIE, type of health information, identity of recipients, and patient preferences regarding consent and features. The findings provide useful theoretical implications for research by developing a classification of significant factors and a framework based on the lessons learned from the literature to help guide HIE efforts. Our results also have fundamental practical implications for policy makers, current and potential organizers of HIEs by highlighting the role of patients in the widespread implementation of HIE. The study indicates that new approaches should be applied to completely underline HIE benefits for patients and also address their concerns.

Linking descriptive geology and quantitative machine learning through an ontology of lithological concepts

NASA Astrophysics Data System (ADS)

Klump, J. F.; Huber, R.; Robertson, J.; Cox, S. J. D.; Woodcock, R.

2014-12-01

Despite the recent explosion of quantitative geological data, geology remains a fundamentally qualitative science. Numerical data only constitute a certain part of data collection in the geosciences. In many cases, geological observations are compiled as text into reports and annotations on drill cores, thin sections or drawings of outcrops. The observations are classified into concepts such as lithology, stratigraphy, geological structure, etc. These descriptions are semantically rich and are generally supported by more quantitative observations using geochemical analyses, XRD, hyperspectral scanning, etc, but the goal is geological semantics. In practice it has been difficult to bring the different observations together due to differing perception or granularity of classification in human observation, or the partial observation of only some characteristics using quantitative sensors. In the past years many geological classification schemas have been transferred into ontologies and vocabularies, formalized using RDF and OWL, and published through SPARQL endpoints. Several lithological ontologies were compiled by stratigraphy.net and published through a SPARQL endpoint. This work is complemented by the development of a Python API to integrate this vocabulary into Python-based text mining applications. The applications for the lithological vocabulary and Python API are automated semantic tagging of geochemical data and descriptions of drill cores, machine learning of geochemical compositions that are diagnostic for lithological classifications, and text mining for lithological concepts in reports and geological literature. This combination of applications can be used to identify anomalies in databases, where composition and lithological classification do not match. It can also be used to identify lithological concepts in the literature and infer quantitative values. The resulting semantic tagging opens new possibilities for linking these diverse sources of data.

What is new in genetics and osteogenesis imperfecta classification?

PubMed

Valadares, Eugênia R; Carneiro, Túlio B; Santos, Paula M; Oliveira, Ana Cristina; Zabel, Bernhard

2014-01-01

Literature review of new genes related to osteogenesis imperfecta (OI) and update of its classification. Literature review in the PubMed and OMIM databases, followed by selection of relevant references. In 1979, Sillence et al. developed a classification of OI subtypes based on clinical features and disease severity: OI type I, mild, common, with blue sclera; OI type II, perinatal lethal form; OI type III, severe and progressively deforming, with normal sclera; and OI type IV, moderate severity with normal sclera. Approximately 90% of individuals with OI are heterozygous for mutations in the COL1A1 and COL1A2 genes, with dominant pattern of inheritance or sporadic mutations. After 2006, mutations were identified in the CRTAP, FKBP10, LEPRE1, PLOD2, PPIB, SERPINF1, SERPINH1, SP7, WNT1, BMP1, and TMEM38B genes, associated with recessive OI and mutation in the IFITM5 gene associated with dominant OI. Mutations in PLS3 were recently identified in families with osteoporosis and fractures, with X-linked inheritance pattern. In addition to the genetic complexity of the molecular basis of OI, extensive phenotypic variability resulting from individual loci has also been documented. Considering the discovery of new genes and limited genotype-phenotype correlation, the use of next-generation sequencing tools has become useful in molecular studies of OI cases. The recommendation of the Nosology Group of the International Society of Skeletal Dysplasias is to maintain the classification of Sillence as the prototypical form, universally accepted to classify the degree of severity in OI, while maintaining it free from direct molecular reference. Copyright © 2014 Sociedade Brasileira de Pediatria. Published by Elsevier Editora Ltda. All rights reserved.

Exploiting ensemble learning for automatic cataract detection and grading.

PubMed

Yang, Ji-Jiang; Li, Jianqiang; Shen, Ruifang; Zeng, Yang; He, Jian; Bi, Jing; Li, Yong; Zhang, Qinyan; Peng, Lihui; Wang, Qing

2016-02-01

Cataract is defined as a lenticular opacity presenting usually with poor visual acuity. It is one of the most common causes of visual impairment worldwide. Early diagnosis demands the expertise of trained healthcare professionals, which may present a barrier to early intervention due to underlying costs. To date, studies reported in the literature utilize a single learning model for retinal image classification in grading cataract severity. We present an ensemble learning based approach as a means to improving diagnostic accuracy. Three independent feature sets, i.e., wavelet-, sketch-, and texture-based features, are extracted from each fundus image. For each feature set, two base learning models, i.e., Support Vector Machine and Back Propagation Neural Network, are built. Then, the ensemble methods, majority voting and stacking, are investigated to combine the multiple base learning models for final fundus image classification. Empirical experiments are conducted for cataract detection (two-class task, i.e., cataract or non-cataractous) and cataract grading (four-class task, i.e., non-cataractous, mild, moderate or severe) tasks. The best performance of the ensemble classifier is 93.2% and 84.5% in terms of the correct classification rates for cataract detection and grading tasks, respectively. The results demonstrate that the ensemble classifier outperforms the single learning model significantly, which also illustrates the effectiveness of the proposed approach. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Novel Mahalanobis-based feature selection improves one-class classification of early hepatocellular carcinoma.

PubMed

Thomaz, Ricardo de Lima; Carneiro, Pedro Cunha; Bonin, João Eliton; Macedo, Túlio Augusto Alves; Patrocinio, Ana Claudia; Soares, Alcimar Barbosa

2018-05-01

Detection of early hepatocellular carcinoma (HCC) is responsible for increasing survival rates in up to 40%. One-class classifiers can be used for modeling early HCC in multidetector computed tomography (MDCT), but demand the specific knowledge pertaining to the set of features that best describes the target class. Although the literature outlines several features for characterizing liver lesions, it is unclear which is most relevant for describing early HCC. In this paper, we introduce an unconstrained GA feature selection algorithm based on a multi-objective Mahalanobis fitness function to improve the classification performance for early HCC. We compared our approach to a constrained Mahalanobis function and two other unconstrained functions using Welch's t-test and Gaussian Data Descriptors. The performance of each fitness function was evaluated by cross-validating a one-class SVM. The results show that the proposed multi-objective Mahalanobis fitness function is capable of significantly reducing data dimensionality (96.4%) and improving one-class classification of early HCC (0.84 AUC). Furthermore, the results provide strong evidence that intensity features extracted at the arterial to portal and arterial to equilibrium phases are important for classifying early HCC.

Unsupervised Biomedical Named Entity Recognition: Experiments with Clinical and Biological Texts

PubMed Central

Zhang, Shaodian; Elhadad, Nóemie

2013-01-01

Named entity recognition is a crucial component of biomedical natural language processing, enabling information extraction and ultimately reasoning over and knowledge discovery from text. Much progress has been made in the design of rule-based and supervised tools, but they are often genre and task dependent. As such, adapting them to different genres of text or identifying new types of entities requires major effort in re-annotation or rule development. In this paper, we propose an unsupervised approach to extracting named entities from biomedical text. We describe a stepwise solution to tackle the challenges of entity boundary detection and entity type classification without relying on any handcrafted rules, heuristics, or annotated data. A noun phrase chunker followed by a filter based on inverse document frequency extracts candidate entities from free text. Classification of candidate entities into categories of interest is carried out by leveraging principles from distributional semantics. Experiments show that our system, especially the entity classification step, yields competitive results on two popular biomedical datasets of clinical notes and biological literature, and outperforms a baseline dictionary match approach. Detailed error analysis provides a road map for future work. PMID:23954592

Advances in Psychiatric Diagnosis: Past, Present, and Future.

PubMed

North, Carol S; Surís, Alina M

2017-04-26

This editorial examines controversies identified by the articles in this special issue, which explore psychopathology in the broad history of the classification of selected psychiatric disorders and syndromes over time through current American criteria. Psychiatric diagnosis has a long history of scientific investigation and application, with periods of rapid change, instability, and heated controversy associated with it. The articles in this issue examine the history of psychiatric nomenclature and explore current and future directions in psychiatric diagnosis through the various versions of accepted diagnostic criteria and accompanying research literature addressing the criteria. The articles seek to guide readers in appreciating the complexities of psychiatric diagnosis as the field of psychiatry pushes forward toward future advancements in diagnosis. Despite efforts of many scientists to advance a diagnostic classification system that incorporates neuroscience and genetics, it has been argued that it may be premature to attempt to move to a biologically-based classification system, because psychiatric disorders cannot yet be fully distinguished by any specific biological markers. For now, the symptom-based criteria that the field has been using continue to serve many essential purposes, including selection of the most effective treatment, communication about disease with colleagues, education about psychiatric illness, and support for ongoing research.

Automatic sleep stage classification based on EEG signals by using neural networks and wavelet packet coefficients.

PubMed

Ebrahimi, Farideh; Mikaeili, Mohammad; Estrada, Edson; Nazeran, Homer

2008-01-01

Currently in the world there is an alarming number of people who suffer from sleep disorders. A number of biomedical signals, such as EEG, EMG, ECG and EOG are used in sleep labs among others for diagnosis and treatment of sleep related disorders. The usual method for sleep stage classification is visual inspection by a sleep specialist. This is a very time consuming and laborious exercise. Automatic sleep stage classification can facilitate this process. The definition of sleep stages and the sleep literature show that EEG signals are similar in Stage 1 of non-rapid eye movement (NREM) sleep and rapid eye movement (REM) sleep. Therefore, in this work an attempt was made to classify four sleep stages consisting of Awake, Stage 1 + REM, Stage 2 and Slow Wave Stage based on the EEG signal alone. Wavelet packet coefficients and artificial neural networks were deployed for this purpose. Seven all night recordings from Physionet database were used in the study. The results demonstrated that these four sleep stages could be automatically discriminated from each other with a specificity of 94.4 +/- 4.5%, a of sensitivity 84.2+3.9% and an accuracy of 93.0 +/- 4.0%.

Prostatitis: myths and realities.

PubMed

Nickel, J C

1998-03-01

To explore the myths surrounding the enigmatic syndrome that the urologic community has labeled as prostatitis and to determine the actual realities associated with this disease. A critical evaluation of the syndrome of prostatitis based on examination of the recent world literature, undisputed scientific facts, solid hypotheses, common sense, and the author's personal opinion. The most common myths surrounding the importance, etiology, diagnosis, classification, and treatment of prostatitis are in fact merely myths. Recent research has led to a new awareness of the importance of prostatitis, new insights into its pathogenesis, improved disease classification and symptom assessment, and will ultimately lead to more rational diagnostic and treatment strategies. The introduction of a new more rational classification system, the development and validation of reliable symptom assessment instruments, new funding initiatives by granting agencies and the pharmaceutical industry, and an awakening appeal for intellectual examination of this common prostate disease by academic urologists guarantees that prostatitis will find an important place on the urologic agenda as we enter the next millennium.

Minimum distance classification in remote sensing

NASA Technical Reports Server (NTRS)

Wacker, A. G.; Landgrebe, D. A.

1972-01-01

The utilization of minimum distance classification methods in remote sensing problems, such as crop species identification, is considered. Literature concerning both minimum distance classification problems and distance measures is reviewed. Experimental results are presented for several examples. The objective of these examples is to: (a) compare the sample classification accuracy of a minimum distance classifier, with the vector classification accuracy of a maximum likelihood classifier, and (b) compare the accuracy of a parametric minimum distance classifier with that of a nonparametric one. Results show the minimum distance classifier performance is 5% to 10% better than that of the maximum likelihood classifier. The nonparametric classifier is only slightly better than the parametric version.

Development of a methodology for classifying software errors

NASA Technical Reports Server (NTRS)

Gerhart, S. L.

1976-01-01

A mathematical formalization of the intuition behind classification of software errors is devised and then extended to a classification discipline: Every classification scheme should have an easily discernible mathematical structure and certain properties of the scheme should be decidable (although whether or not these properties hold is relative to the intended use of the scheme). Classification of errors then becomes an iterative process of generalization from actual errors to terms defining the errors together with adjustment of definitions according to the classification discipline. Alternatively, whenever possible, small scale models may be built to give more substance to the definitions. The classification discipline and the difficulties of definition are illustrated by examples of classification schemes from the literature and a new study of observed errors in published papers of programming methodologies.

Ulnar neuropathy at wrist: entrapment at a very "congested" site.

PubMed

Coraci, Daniele; Loreti, Claudia; Piccinini, Giulia; Doneddu, Pietro E; Biscotti, Silvia; Padua, Luca

2018-05-19

Ulnar tunnel syndrome indicates ulnar neuropathy at different sites within the wrist. Several classifications of ulnar tunnel syndrome are present in literature, based upon typical nerve anatomy. However, anatomical variations are not uncommon and can complicate assessment. The etiology is also complex, due to the numerous potential causes of entrapment. Clinical examination, neurophysiological testing, and imaging are all used to support the diagnosis. At present, many therapeutic approaches are available, ranging from observation to surgical management. Although ulnar neuropathy at the wrist has undergone extensive prior study, unresolved questions on diagnosis and treatment remain. In the current paper, we review relevant literature and present the current knowledge on ulnar tunnel syndrome.

Classification of platelet concentrates (Platelet-Rich Plasma-PRP, Platelet-Rich Fibrin-PRF) for topical and infiltrative use in orthopedic and sports medicine: current consensus, clinical implications and perspectives

PubMed Central

Dohan Ehrenfest, David M.; Andia, Isabel; Zumstein, Matthias A.; Zhang, Chang-Qing; Pinto, Nelson R.; Bielecki, Tomasz

2014-01-01

Summary Platelet concentrates for topical and infiltrative use – commonly termed Platetet-Rich Plasma (PRP) or Platelet-Rich Fibrin (PRF) – are used or tested as surgical adjuvants or regenerative medicine preparations in most medical fields, particularly in sports medicine and orthopaedic surgery. Even if these products offer interesting therapeutic perspectives, their clinical relevance is largely debated, as the literature on the topic is often confused and contradictory. The long history of these products was always associated with confusions, mostly related to the lack of consensual terminology, characterization and classification of the many products that were tested in the last 40 years. The current consensus is based on a simple classification system dividing the many products in 4 main families, based on their fibrin architecture and cell content: Pure Platelet-Rich Plasma (P-PRP), such as the PRGF-Endoret technique; Leukocyte- and Platelet-Rich Plasma (LPRP), such as Biomet GPS system; Pure Platelet-Rich Fibrin (P-PRF), such as Fibrinet; Leukocyte- and Platelet-Rich Fibrin (L-PRF), such as Intra-Spin L-PRF. The 4 main families of products present different biological signatures and mechanisms, and obvious differences for clinical applications. This classification serves as a basis for further investigations of the effects of these products. Perspectives of evolutions of this classification and terminology are also discussed, particularly concerning the impact of the cell content, preservation and activation on these products in sports medicine and orthopaedics. PMID:24932440

A Framework for Text Mining in Scientometric Study: A Case Study in Biomedicine Publications

NASA Astrophysics Data System (ADS)

Silalahi, V. M. M.; Hardiyati, R.; Nadhiroh, I. M.; Handayani, T.; Rahmaida, R.; Amelia, M.

2018-04-01

The data of Indonesians research publications in the domain of biomedicine has been collected to be text mined for the purpose of a scientometric study. The goal is to build a predictive model that provides a classification of research publications on the potency for downstreaming. The model is based on the drug development processes adapted from the literatures. An effort is described to build the conceptual model and the development of a corpus on the research publications in the domain of Indonesian biomedicine. Then an investigation is conducted relating to the problems associated with building a corpus and validating the model. Based on our experience, a framework is proposed to manage the scientometric study based on text mining. Our method shows the effectiveness of conducting a scientometric study based on text mining in order to get a valid classification model. This valid model is mainly supported by the iterative and close interactions with the domain experts starting from identifying the issues, building a conceptual model, to the labelling, validation and results interpretation.

Enhancing Math through Literature.

ERIC Educational Resources Information Center

O'Banion, Carie

1997-01-01

Provides a bibliography of children's literature exploring mathematical concepts: classification; place value and numeration systems; counting, addition, and subtraction; multiplication and division; fractions; estimation; big numbers; geometry; measurement; and games and puzzles. Highlights one book for each concept, suggests class activities,…

Semantic Segmentation of Forest Stands of Pure Species as a Global Optimization Problem

NASA Astrophysics Data System (ADS)

Dechesne, C.; Mallet, C.; Le Bris, A.; Gouet-Brunet, V.

2017-05-01

Forest stand delineation is a fundamental task for forest management purposes, that is still mainly manually performed through visual inspection of geospatial (very) high spatial resolution images. Stand detection has been barely addressed in the literature which has mainly focused, in forested environments, on individual tree extraction and tree species classification. From a methodological point of view, stand detection can be considered as a semantic segmentation problem. It offers two advantages. First, one can retrieve the dominant tree species per segment. Secondly, one can benefit from existing low-level tree species label maps from the literature as a basis for high-level object extraction. Thus, the semantic segmentation issue becomes a regularization issue in a weakly structured environment and can be formulated in an energetical framework. This papers aims at investigating which regularization strategies of the literature are the most adapted to delineate and classify forest stands of pure species. Both airborne lidar point clouds and multispectral very high spatial resolution images are integrated for that purpose. The local methods (such as filtering and probabilistic relaxation) are not adapted for such problem since the increase of the classification accuracy is below 5%. The global methods, based on an energy model, tend to be more efficient with an accuracy gain up to 15%. The segmentation results using such models have an accuracy ranging from 96% to 99%.

[L'impiego dell'ICNP® nella formazione infermieristica con modelli teorici infermieristici: una revisione della letteratura].

PubMed

Macchi, Barbara; Sironi, Cecilia; Di Mauro, Stefania; Ausili, Davide

2016-01-01

The International Classification for Nursing Practice (ICNP®) is the only nursing terminology that has been accepted within the Family of International Classification of the World Health Organization. The academic teaching of ICNP® could contribute to improve nursing clinical practice. However, standards for its implementation in undergraduate nursing education together with a nursing theoretical model are not available. To know the state of the art about the use of ICNP® in undergraduate nursing education and its use with a nursing theoretical model. A narrative literature review was conducted searching main health scientific databases and including monographs, statements from international associations, and published conference papers. Available literature about ICNP® implementation in nursing education and its use with theoretical models is limited. Results supported the organization of a specific course on ICNP® before clinical teaching programs, the development of paper or electronic ICNP® based educational tools, and the use of active learning strategies. Only three experiences reporting the use of ICNP® with theoretical models have been found. Both the use of ICNP® in nursing undergraduate education and its use according to one or more nursing theoretical models, could help students to learn nursing process. However, weak recommendations can be found in the literature to orient ICNP® implementation in undergraduate nursing education and/or with an explicit theoretical framework. Further studies focusing on these issues are strongly needed.

Assessment and classification of cancer breakthrough pain: a systematic literature review.

PubMed

Haugen, Dagny Faksvåg; Hjermstad, Marianne Jensen; Hagen, Neil; Caraceni, Augusto; Kaasa, Stein

2010-06-01

Temporal variations in cancer pain intensity are highly prevalent, and are often difficult to manage. However, the phenomenon is not well understood: several definitions and approaches to classification and bedside assessment of cancer breakthrough pain (BTP) have been described. The present study is a systematic review of published literature on cancer BTP to answer the following questions: which terms and definitions have been used; are there validated assessment tools; which domains of BTP do the tools delineate, and which items do they contain; how have assessment tools been applied within clinical studies; and are there validated classification systems for BTP. A systematic search of the peer-reviewed literature was performed using five major databases. Of 375 titles and abstracts initially identified, 51 articles were examined in detail. Analysis of these publications indicates a range of overlapping but distinct definitions have been used to characterize BTP; 42 of the included papers presented one or more ways of classifying BTP; and while 10 tools to assess patients' experience of BTP were identified, only 2 have been partially validated. We conclude that there is no widely accepted definition, classification system or well-validated assessment tool for cancer-related breakthrough pain, but there is strong concurrence on most of its key attributes. With further work in this area, an internationally agreed upon definition and classification system for cancer-related breakthrough pain, and a standard approach on how to measure it, hold the promise to improve patient care and support research in this poor-prognosis cancer pain syndrome.

Teaching Sexual History-Taking Skills Using the Sexual Events Classification System

ERIC Educational Resources Information Center

Fidler, Donald C.; Petri, Justin Daniel; Chapman, Mark

2010-01-01

Objective: The authors review the literature about educational programs for teaching sexual history-taking skills and describe novel techniques for teaching these skills. Methods: Psychiatric residents enrolled in a brief sexual history-taking course that included instruction on the Sexual Events Classification System, feedback on residents'…

The Cool and Belkin Faceted Classification of Information Interactions Revisited

ERIC Educational Resources Information Center

Huvila, Isto

2010-01-01

Introduction: The complexity of human information activity is a challenge for both practice and research in information sciences and information management. Literature presents a wealth of approaches to analytically structure and make sense of human information activity including a faceted classification model of information interactions published…

Site classification for northern forest species

Treesearch

Willard H. Carmean

1977-01-01

Summarizes the extensive literature for northern forest species covering site index curves, site index species comparisons, growth intercepts, soil-site studies, plant indicators, physiographic site classifications, and soil survey studies. The advantages and disadvantages of each are discussed, and suggestions are made for future research using each of these methods....

Acquisition Order of Coherence Relations in Turkish

ERIC Educational Resources Information Center

Demirgunes, Sercan

2015-01-01

Coherence as one of the criteria for textuality is the main element of a well-produced text. In the literature, there are many studies on the classification of coherence relations. Although there are different classifications on coherence relations, similar findings are reported regarding the acquisition order of coherence relations in different…

A Note on Comparing Examinee Classification Methods for Cognitive Diagnosis Models

ERIC Educational Resources Information Center

Huebner, Alan; Wang, Chun

2011-01-01

Cognitive diagnosis models have received much attention in the recent psychometric literature because of their potential to provide examinees with information regarding multiple fine-grained discretely defined skills, or attributes. This article discusses the issue of methods of examinee classification for cognitive diagnosis models, which are…

The Bellevue Classification System: nursing's voice upon the library shelves*†

PubMed Central

Mages, Keith C

2011-01-01

This article examines the inspiration, construction, and meaning of the Bellevue Classification System (BCS), created during the 1930s for use in the Bellevue School of Nursing Library. Nursing instructor Ann Doyle, with assistance from librarian Mary Casamajor, designed the BCS after consulting with library leaders and examining leading contemporary classification systems, including the Dewey Decimal Classification and Library of Congress, Ballard, and National Health Library classification systems. A close textual reading of the classes, subclasses, and subdivisions of these classification systems against those of the resulting BCS, reveals Doyle's belief that the BCS was created not only to organize the literature, but also to promote the burgeoning intellectualism and professionalism of early twentieth-century American nursing. PMID:21243054

An estimation framework for building information modeling (BIM)-based demolition waste by type.

PubMed

Kim, Young-Chan; Hong, Won-Hwa; Park, Jae-Woo; Cha, Gi-Wook

2017-12-01

Most existing studies on demolition waste (DW) quantification do not have an official standard to estimate the amount and type of DW. Therefore, there are limitations in the existing literature for estimating DW with a consistent classification system. Building information modeling (BIM) is a technology that can generate and manage all the information required during the life cycle of a building, from design to demolition. Nevertheless, there has been a lack of research regarding its application to the demolition stage of a building. For an effective waste management plan, the estimation of the type and volume of DW should begin from the building design stage. However, the lack of tools hinders an early estimation. This study proposes a BIM-based framework that estimates DW in the early design stages, to achieve an effective and streamlined planning, processing, and management. Specifically, the input of construction materials in the Korean construction classification system and those in the BIM library were matched. Based on this matching integration, the estimates of DW by type were calculated by applying the weight/unit volume factors and the rates of DW volume change. To verify the framework, its operation was demonstrated by means of an actual BIM modeling and by comparing its results with those available in the literature. This study is expected to contribute not only to the estimation of DW at the building level, but also to the automated estimation of DW at the district level.

A psychophysical imaging method evidencing auditory cue extraction during speech perception: a group analysis of auditory classification images.

PubMed

Varnet, Léo; Knoblauch, Kenneth; Serniclaes, Willy; Meunier, Fanny; Hoen, Michel

2015-01-01

Although there is a large consensus regarding the involvement of specific acoustic cues in speech perception, the precise mechanisms underlying the transformation from continuous acoustical properties into discrete perceptual units remains undetermined. This gap in knowledge is partially due to the lack of a turnkey solution for isolating critical speech cues from natural stimuli. In this paper, we describe a psychoacoustic imaging method known as the Auditory Classification Image technique that allows experimenters to estimate the relative importance of time-frequency regions in categorizing natural speech utterances in noise. Importantly, this technique enables the testing of hypotheses on the listening strategies of participants at the group level. We exemplify this approach by identifying the acoustic cues involved in da/ga categorization with two phonetic contexts, Al- or Ar-. The application of Auditory Classification Images to our group of 16 participants revealed significant critical regions on the second and third formant onsets, as predicted by the literature, as well as an unexpected temporal cue on the first formant. Finally, through a cluster-based nonparametric test, we demonstrate that this method is sufficiently sensitive to detect fine modifications of the classification strategies between different utterances of the same phoneme.

Assessment of Intraobserver and Interobserver Agreement of a New Classification System for Retrograde Periimplantitis.

PubMed

Shah, Rucha; Thomas, Raison; Kumar, Tarun; Mehta, Dhoom Singh

2016-12-01

Retrograde periimplantitis (RPI) is the inflammatory disease that affects the apical part of an osseointegrated implant while the coronal portion of the implant sustains a normal bone-to-implant interface. The aim of the current study was to assess the intraexaminer and interexaminer reliability of a proposed new classification system for RPI. After thorough electronic literature search, 56 intraoral periapical radiographs (IOPA) of implants with RPI were collected and were classified by 2 independent reviewers as per the new classification system into one of the 3-mild, moderate, and advanced-classes based on the amount of bone loss from the apex of the implant to the most coronal part as a percentage of the total implant length. The IOPAs were assessed twice by the same examiners and both were blinded to each other's observations. The intraobserver agreement ranged from 0.85 to 0.91, which falls under the category of almost perfect agreement. The interexaminer agreement was found to be 0.83, also considered as almost perfect agreement. The proposed classification shows good intraexaminer and interexaminer reliability and can be used for treatment planning and prognosis in cases of RPI.

Skin problems in individuals with lower-limb loss: literature review and proposed classification system.

PubMed

Bui, Kelly M; Raugi, Gregory J; Nguyen, Viet Q; Reiber, Gayle E

2009-01-01

Problems with skin integrity can disrupt daily prosthesis use and lead to decreased mobility and function in individuals with lower-limb loss. This study reviewed the literature to examine how skin problems are defined and diagnosed and to identify the prevalence and types of skin problems in individuals with lower-limb loss. We searched the literature for terms related to amputation and skin problems. We identified 777 articles. Of the articles, 90 met criteria for review of research methodology. Four clinical studies met our selection criteria. The prevalence rate of skin problems was 15% to 41%. The most commonly reported skin problems were wounds, abscesses, and blisters. Given the lack of standardized definitions of skin problems on residual limbs, we conclude this article with a system for classification.

Classification, processing and application of hydrogels: A review.

PubMed

Ullah, Faheem; Othman, Muhammad Bisyrul Hafi; Javed, Fatima; Ahmad, Zulkifli; Md Akil, Hazizan

2015-12-01

This article aims to review the literature concerning the choice of selectivity for hydrogels based on classification, application and processing. Super porous hydrogels (SPHs) and superabsorbent polymers (SAPs) represent an innovative category of recent generation highlighted as an ideal mould system for the study of solution-dependent phenomena. Hydrogels, also termed as smart and/or hungry networks, are currently subject of considerable scientific research due to their potential in hi-tech applications in the biomedical, pharmaceutical, biotechnology, bioseparation, biosensor, agriculture, oil recovery and cosmetics fields. Smart hydrogels display a significant physiochemical change in response to small changes in the surroundings. However, such changes are reversible; therefore, the hydrogels are capable of returning to its initial state after a reaction as soon as the trigger is removed. Copyright © 2015 Elsevier B.V. All rights reserved.

The clinical inadequacy of the DSM-5 classification of somatic symptom and related disorders: an alternative trans-diagnostic model.

PubMed

Cosci, Fiammetta; Fava, Giovanni A

2016-08-01

The Diagnostic and Statistical of Mental Disorders, Fifth Edition (DSM-5) somatic symptom and related disorders chapter has a limited clinical utility. In addition to the problems that the single diagnostic rubrics and the deletion of the diagnosis of hypochondriasis entail, there are 2 major ambiguities: (1) the use of the term "somatic symptoms" reflects an ill-defined concept of somatization and (2) abnormal illness behavior is included in all diagnostic rubrics, but it is never conceptually defined. In the present review of the literature, we will attempt to approach the clinical issue from a different angle, by introducing the trans-diagnostic viewpoint of illness behavior and propose an alternative clinimetric classification system, based on the Diagnostic Criteria for Psychosomatic Research.

Automatic discrimination between safe and unsafe swallowing using a reputation-based classifier

PubMed Central

2011-01-01

Background Swallowing accelerometry has been suggested as a potential non-invasive tool for bedside dysphagia screening. Various vibratory signal features and complementary measurement modalities have been put forth in the literature for the potential discrimination between safe and unsafe swallowing. To date, automatic classification of swallowing accelerometry has exclusively involved a single-axis of vibration although a second axis is known to contain additional information about the nature of the swallow. Furthermore, the only published attempt at automatic classification in adult patients has been based on a small sample of swallowing vibrations. Methods In this paper, a large corpus of dual-axis accelerometric signals were collected from 30 older adults (aged 65.47 ± 13.4 years, 15 male) referred to videofluoroscopic examination on the suspicion of dysphagia. We invoked a reputation-based classifier combination to automatically categorize the dual-axis accelerometric signals into safe and unsafe swallows, as labeled via videofluoroscopic review. From these participants, a total of 224 swallowing samples were obtained, 164 of which were labeled as unsafe swallows (swallows where the bolus entered the airway) and 60 as safe swallows. Three separate support vector machine (SVM) classifiers and eight different features were selected for classification. Results With selected time, frequency and information theoretic features, the reputation-based algorithm distinguished between safe and unsafe swallowing with promising accuracy (80.48 ± 5.0%), high sensitivity (97.1 ± 2%) and modest specificity (64 ± 8.8%). Interpretation of the most discriminatory features revealed that in general, unsafe swallows had lower mean vibration amplitude and faster autocorrelation decay, suggestive of decreased hyoid excursion and compromised coordination, respectively. Further, owing to its performance-based weighting of component classifiers, the static reputation-based algorithm outperformed the democratic majority voting algorithm on this clinical data set. Conclusion Given its computational efficiency and high sensitivity, reputation-based classification of dual-axis accelerometry ought to be considered in future developments of a point-of-care swallow assessment where clinical informatics are desired. PMID:22085802

Classification methods to detect sleep apnea in adults based on respiratory and oximetry signals: a systematic review.

PubMed

Uddin, M B; Chow, C M; Su, S W

2018-03-26

Sleep apnea (SA), a common sleep disorder, can significantly decrease the quality of life, and is closely associated with major health risks such as cardiovascular disease, sudden death, depression, and hypertension. The normal diagnostic process of SA using polysomnography is costly and time consuming. In addition, the accuracy of different classification methods to detect SA varies with the use of different physiological signals. If an effective, reliable, and accurate classification method is developed, then the diagnosis of SA and its associated treatment will be time-efficient and economical. This study aims to systematically review the literature and present an overview of classification methods to detect SA using respiratory and oximetry signals and address the automated detection approach. Sixty-two included studies revealed the application of single and multiple signals (respiratory and oximetry) for the diagnosis of SA. Both airflow and oxygen saturation signals alone were effective in detecting SA in the case of binary decision-making, whereas multiple signals were good for multi-class detection. In addition, some machine learning methods were superior to the other classification methods for SA detection using respiratory and oximetry signals. To deal with the respiratory and oximetry signals, a good choice of classification method as well as the consideration of associated factors would result in high accuracy in the detection of SA. An accurate classification method should provide a high detection rate with an automated (independent of human action) analysis of respiratory and oximetry signals. Future high-quality automated studies using large samples of data from multiple patient groups or record batches are recommended.

Practice patterns when treating patients with low back pain: a survey of physical therapists.

PubMed

Davies, Claire; Nitz, Arthur J; Mattacola, Carl G; Kitzman, Patrick; Howell, Dana; Viele, Kert; Baxter, David; Brockopp, Dorothy

2014-08-01

Low back pain (LBP), is a common musculoskeletal problem, affecting 75-85% of adults in their lifetime. Direct costs of LBP in the USA were estimated over 85 billion dollars in 2005 resulting in a significant economic burden for the healthcare system. LBP classification systems and outcome measures are available to guide physical therapy assessments and intervention. However, little is known about which, if any, physical therapists use in clinical practice. The purpose of this study was to identify the use of and barriers to LBP classification systems and outcome measures among physical therapists in one state. A mixed methods study using a cross-sectional cohort design with descriptive qualitative methods was performed. A survey collected both quantitative and qualitative data relevant to classification systems and outcome measures used by physical therapists working with patients with LBP. Physical therapists responded using classification systems designed to direct treatment predominantly. The McKenzie method was the most frequent approach to classify LBP. Barriers to use of classification systems and outcome measures were lack of knowledge, too limiting and time. Classification systems are being used for decision-making in physical therapy practice for patients with LBP. Lack of knowledge and training seems to be the main barrier to the use of classification systems in practice. The Oswestry Disability Index and Numerical Pain Scale were the most commonly used outcome measures. The main barrier to their use was lack of time. Continuing education and reading the literature were identified as important tools to teach evidence-based practice to physical therapists in practice.

Nationwide forestry applications program. Analysis of forest classification accuracy

NASA Technical Reports Server (NTRS)

Congalton, R. G.; Mead, R. A.; Oderwald, R. G.; Heinen, J. (Principal Investigator)

1981-01-01

The development of LANDSAT classification accuracy assessment techniques, and of a computerized system for assessing wildlife habitat from land cover maps are considered. A literature review on accuracy assessment techniques and an explanation for the techniques development under both projects are included along with listings of the computer programs. The presentations and discussions at the National Working Conference on LANDSAT Classification Accuracy are summarized. Two symposium papers which were published on the results of this project are appended.

Gender classification under extended operating conditions

NASA Astrophysics Data System (ADS)

Rude, Howard N.; Rizki, Mateen

2014-06-01

Gender classification is a critical component of a robust image security system. Many techniques exist to perform gender classification using facial features. In contrast, this paper explores gender classification using body features extracted from clothed subjects. Several of the most effective types of features for gender classification identified in literature were implemented and applied to the newly developed Seasonal Weather And Gender (SWAG) dataset. SWAG contains video clips of approximately 2000 samples of human subjects captured over a period of several months. The subjects are wearing casual business attire and outer garments appropriate for the specific weather conditions observed in the Midwest. The results from a series of experiments are presented that compare the classification accuracy of systems that incorporate various types and combinations of features applied to multiple looks at subjects at different image resolutions to determine a baseline performance for gender classification.

Australian diagnosis related groups: Drivers of complexity adjustment.

PubMed

Jackson, Terri; Dimitropoulos, Vera; Madden, Richard; Gillett, Steve

2015-11-01

In undertaking a major revision to the Australian Refined Diagnosis Related Group (ARDRG) classification, we set out to contrast Australia's approach to using data on additional (not principal) diagnoses with major international approaches in splitting base or Adjacent Diagnosis Related Groups (ADRGs). Comparative policy analysis/narrative review of peer-reviewed and grey literature on international approaches to use of additional (secondary) diagnoses in the development of Australian and international DRG systems. European and US approaches to characterise complexity of inpatient care are well-documented, providing useful points of comparison with Australia's. Australia, with good data sources, has continued to refine its national DRG classification using increasingly sophisticated approaches. Hospital funders in Australia and in other systems are often under pressure from provider groups to expand classifications to reflect clinical complexity. DRG development in most healthcare systems reviewed here reflects four critical factors: these socio-political factors, the quality and depth of the coded data available to characterise the mix of cases in a healthcare system, the size of the underlying population, and the intended scope and use of the classification. Australia's relatively small national population has constrained the size of its DRG classifications, and development has been concentrated on inpatient care in public hospitals. Development of casemix classifications in health care is driven by both technical and socio-political factors. Use of additional diagnoses to adjust for patient complexity and cost needs to respond to these in each casemix application. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Featureless classification of light curves

NASA Astrophysics Data System (ADS)

Kügler, S. D.; Gianniotis, N.; Polsterer, K. L.

2015-08-01

In the era of rapidly increasing amounts of time series data, classification of variable objects has become the main objective of time-domain astronomy. Classification of irregularly sampled time series is particularly difficult because the data cannot be represented naturally as a vector which can be directly fed into a classifier. In the literature, various statistical features serve as vector representations. In this work, we represent time series by a density model. The density model captures all the information available, including measurement errors. Hence, we view this model as a generalization to the static features which directly can be derived, e.g. as moments from the density. Similarity between each pair of time series is quantified by the distance between their respective models. Classification is performed on the obtained distance matrix. In the numerical experiments, we use data from the OGLE (Optical Gravitational Lensing Experiment) and ASAS (All Sky Automated Survey) surveys and demonstrate that the proposed representation performs up to par with the best currently used feature-based approaches. The density representation preserves all static information present in the observational data, in contrast to a less-complete description by features. The density representation is an upper boundary in terms of information made available to the classifier. Consequently, the predictive power of the proposed classification depends on the choice of similarity measure and classifier, only. Due to its principled nature, we advocate that this new approach of representing time series has potential in tasks beyond classification, e.g. unsupervised learning.

Validity Evidence in Scale Development: The Application of Cross Validation and Classification-Sequencing Validation

ERIC Educational Resources Information Center

Acar, Tu¨lin

2014-01-01

In literature, it has been observed that many enhanced criteria are limited by factor analysis techniques. Besides examinations of statistical structure and/or psychological structure, such validity studies as cross validation and classification-sequencing studies should be performed frequently. The purpose of this study is to examine cross…

Diagnostic Classification of Children within the Educational System: Should It Be Eliminated?

ERIC Educational Resources Information Center

Kuther, Tara L.

This paper reviews the literature on positive and negative aspects of diagnostic classification of children, or labeling. It reviews the Education for All Handicapped Children Act, which mandated that special education must be available to all children with disabilities. Definitional issues in diagnostic labeling of students with learning…

Reference set for performance testing of pediatric vaccine safety signal detection methods and systems.

PubMed

Brauchli Pernus, Yolanda; Nan, Cassandra; Verstraeten, Thomas; Pedenko, Mariia; Osokogu, Osemeke U; Weibel, Daniel; Sturkenboom, Miriam; Bonhoeffer, Jan

2016-12-12

Safety signal detection in spontaneous reporting system databases and electronic healthcare records is key to detection of previously unknown adverse events following immunization. Various statistical methods for signal detection in these different datasources have been developed, however none are geared to the pediatric population and none specifically to vaccines. A reference set comprising pediatric vaccine-adverse event pairs is required for reliable performance testing of statistical methods within and across data sources. The study was conducted within the context of the Global Research in Paediatrics (GRiP) project, as part of the seventh framework programme (FP7) of the European Commission. Criteria for the selection of vaccines considered in the reference set were routine and global use in the pediatric population. Adverse events were primarily selected based on importance. Outcome based systematic literature searches were performed for all identified vaccine-adverse event pairs and complemented by expert committee reports, evidence based decision support systems (e.g. Micromedex), and summaries of product characteristics. Classification into positive (PC) and negative control (NC) pairs was performed by two independent reviewers according to a pre-defined algorithm and discussed for consensus in case of disagreement. We selected 13 vaccines and 14 adverse events to be included in the reference set. From a total of 182 vaccine-adverse event pairs, we classified 18 as PC, 113 as NC and 51 as unclassifiable. Most classifications (91) were based on literature review, 45 were based on expert committee reports, and for 46 vaccine-adverse event pairs, an underlying pathomechanism was not plausible classifying the association as NC. A reference set of vaccine-adverse event pairs was developed. We propose its use for comparing signal detection methods and systems in the pediatric population. Published by Elsevier Ltd.

Novel high/low solubility classification methods for new molecular entities.

PubMed

Dave, Rutwij A; Morris, Marilyn E

2016-09-10

This research describes a rapid solubility classification approach that could be used in the discovery and development of new molecular entities. Compounds (N=635) were divided into two groups based on information available in the literature: high solubility (BDDCS/BCS 1/3) and low solubility (BDDCS/BCS 2/4). We established decision rules for determining solubility classes using measured log solubility in molar units (MLogSM) or measured solubility (MSol) in mg/ml units. ROC curve analysis was applied to determine statistically significant threshold values of MSol and MLogSM. Results indicated that NMEs with MLogSM>-3.05 or MSol>0.30mg/mL will have ≥85% probability of being highly soluble and new molecular entities with MLogSM≤-3.05 or MSol≤0.30mg/mL will have ≥85% probability of being poorly soluble. When comparing solubility classification using the threshold values of MLogSM or MSol with BDDCS, we were able to correctly classify 85% of compounds. We also evaluated solubility classification of an independent set of 108 orally administered drugs using MSol (0.3mg/mL) and our method correctly classified 81% and 95% of compounds into high and low solubility classes, respectively. The high/low solubility classification using MLogSM or MSol is novel and independent of traditionally used dose number criteria. Copyright © 2016 Elsevier B.V. All rights reserved.

A new hybrid method based on fuzzy-artificial immune system and k-nn algorithm for breast cancer diagnosis.

PubMed

Sahan, Seral; Polat, Kemal; Kodaz, Halife; Güneş, Salih

2007-03-01

The use of machine learning tools in medical diagnosis is increasing gradually. This is mainly because the effectiveness of classification and recognition systems has improved in a great deal to help medical experts in diagnosing diseases. Such a disease is breast cancer, which is a very common type of cancer among woman. As the incidence of this disease has increased significantly in the recent years, machine learning applications to this problem have also took a great attention as well as medical consideration. This study aims at diagnosing breast cancer with a new hybrid machine learning method. By hybridizing a fuzzy-artificial immune system with k-nearest neighbour algorithm, a method was obtained to solve this diagnosis problem via classifying Wisconsin Breast Cancer Dataset (WBCD). This data set is a very commonly used data set in the literature relating the use of classification systems for breast cancer diagnosis and it was used in this study to compare the classification performance of our proposed method with regard to other studies. We obtained a classification accuracy of 99.14%, which is the highest one reached so far. The classification accuracy was obtained via 10-fold cross validation. This result is for WBCD but it states that this method can be used confidently for other breast cancer diagnosis problems, too.

An Updated Taxonomy and a Graphical Summary Tool for Optimal Classification and Comprehension of Omics Research.

PubMed

Pirih, Nina; Kunej, Tanja

2018-05-01

The volume of publications and the type of research approaches used in omics system sciences are vast and continue to expand rapidly. This increased complexity and heterogeneity of omics data are challenging data extraction, sensemaking, analyses, knowledge translation, and interpretation. An extended and dynamic taxonomy for the classification and summary of omics studies are essential. We present an updated taxonomy for classification of omics research studies based on four criteria: (1) type and number of genomic loci in a research study, (2) number of species and biological samples, (3) the type of omics technology (e.g., genomics, transcriptomics, and proteomics) and omics technology application type (e.g., pharmacogenomics and nutrigenomics), and (4) phenotypes. In addition, we present a graphical summary approach that enables the researchers to define the main characteristics of their study in a single figure, and offers the readers to rapidly grasp the published study and omics data. We searched the PubMed and the Web of Science from 09/2002 to 02/2018, including research and review articles, and identified 90 scientific publications. We propose a call toward omics studies' standardization for reporting in scientific literature. We anticipate the proposed classification scheme will usefully contribute to improved classification of published reports in genomics and other omics fields, and help data extraction from publications for future multiomics data integration.

2016 Classification Criteria for Macrophage Activation Syndrome Complicating Systemic Juvenile Idiopathic Arthritis: A European League Against Rheumatism/American College of Rheumatology/Paediatric Rheumatology International Trials Organisation Collaborative Initiative.

PubMed

Ravelli, Angelo; Minoia, Francesca; Davì, Sergio; Horne, AnnaCarin; Bovis, Francesca; Pistorio, Angela; Aricò, Maurizio; Avcin, Tadej; Behrens, Edward M; De Benedetti, Fabrizio; Filipovic, Lisa; Grom, Alexei A; Henter, Jan-Inge; Ilowite, Norman T; Jordan, Michael B; Khubchandani, Raju; Kitoh, Toshiyuki; Lehmberg, Kai; Lovell, Daniel J; Miettunen, Paivi; Nichols, Kim E; Ozen, Seza; Pachlopnik Schmid, Jana; Ramanan, Athimalaipet V; Russo, Ricardo; Schneider, Rayfel; Sterba, Gary; Uziel, Yosef; Wallace, Carol; Wouters, Carine; Wulffraat, Nico; Demirkaya, Erkan; Brunner, Hermine I; Martini, Alberto; Ruperto, Nicolino; Cron, Randy Q

2016-03-01

To develop criteria for the classification of macrophage activation syndrome (MAS) in patients with systemic juvenile idiopathic arthritis (JIA). A multistep process, based on a combination of expert consensus and analysis of real patient data, was conducted. A panel of 28 experts was first asked to classify 428 patient profiles as having or not having MAS, based on clinical and laboratory features at the time of disease onset. The 428 profiles comprised 161 patients with systemic JIA-associated MAS and 267 patients with a condition that could potentially be confused with MAS (active systemic JIA without evidence of MAS, or systemic infection). Next, the ability of candidate criteria to classify individual patients as having MAS or not having MAS was assessed by evaluating the agreement between the classification yielded using the criteria and the consensus classification of the experts. The final criteria were selected in a consensus conference. Experts achieved consensus on the classification of 391 of the 428 patient profiles (91.4%). A total of 982 candidate criteria were tested statistically. The 37 best-performing criteria and 8 criteria obtained from the literature were evaluated at the consensus conference. During the conference, 82% consensus among experts was reached on the final MAS classification criteria. In validation analyses, these criteria had a sensitivity of 0.73 and a specificity of 0.99. Agreement between the classification (MAS or not MAS) obtained using the criteria and the original diagnosis made by the treating physician was high (κ=0.76). We have developed a set of classification criteria for MAS complicating systemic JIA and provided preliminary evidence of its validity. Use of these criteria will potentially improve understanding of MAS in systemic JIA and enhance efforts to discover effective therapies, by ensuring appropriate patient enrollment in studies. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

A catalog of automated analysis methods for enterprise models.

PubMed

Florez, Hector; Sánchez, Mario; Villalobos, Jorge

2016-01-01

Enterprise models are created for documenting and communicating the structure and state of Business and Information Technologies elements of an enterprise. After models are completed, they are mainly used to support analysis. Model analysis is an activity typically based on human skills and due to the size and complexity of the models, this process can be complicated and omissions or miscalculations are very likely. This situation has fostered the research of automated analysis methods, for supporting analysts in enterprise analysis processes. By reviewing the literature, we found several analysis methods; nevertheless, they are based on specific situations and different metamodels; then, some analysis methods might not be applicable to all enterprise models. This paper presents the work of compilation (literature review), classification, structuring, and characterization of automated analysis methods for enterprise models, expressing them in a standardized modeling language. In addition, we have implemented the analysis methods in our modeling tool.

Reflective random indexing for semi-automatic indexing of the biomedical literature.

PubMed

Vasuki, Vidya; Cohen, Trevor

2010-10-01

The rapid growth of biomedical literature is evident in the increasing size of the MEDLINE research database. Medical Subject Headings (MeSH), a controlled set of keywords, are used to index all the citations contained in the database to facilitate search and retrieval. This volume of citations calls for efficient tools to assist indexers at the US National Library of Medicine (NLM). Currently, the Medical Text Indexer (MTI) system provides assistance by recommending MeSH terms based on the title and abstract of an article using a combination of distributional and vocabulary-based methods. In this paper, we evaluate a novel approach toward indexer assistance by using nearest neighbor classification in combination with Reflective Random Indexing (RRI), a scalable alternative to the established methods of distributional semantics. On a test set provided by the NLM, our approach significantly outperforms the MTI system, suggesting that the RRI approach would make a useful addition to the current methodologies.

Formal Representations of Eligibility Criteria: A Literature Review

PubMed Central

Weng, Chunhua; Tu, Samson W.; Sim, Ida; Richesson, Rachel

2010-01-01

Standards-based, computable knowledge representations for eligibility criteria are increasingly needed to provide computer-based decision support for automated research participant screening, clinical evidence application, and clinical research knowledge management. We surveyed the literature and identified five aspects of eligibility criteria knowledge representations that contribute to the various research and clinical applications: the intended use of computable eligibility criteria, the classification of eligibility criteria, the expression language for representing eligibility rules, the encoding of eligibility concepts, and the modeling of patient data. We consider three of them (expression language, codification of eligibility concepts, and patient data modeling), to be essential constructs of a formal knowledge representation for eligibility criteria. The requirements for each of the three knowledge constructs vary for different use cases, which therefore should inform the development and choice of the constructs toward cost-effective knowledge representation efforts. We discuss the implications of our findings for standardization efforts toward sharable knowledge representation of eligibility criteria. PMID:20034594

An attention-based effective neural model for drug-drug interactions extraction.

PubMed

Zheng, Wei; Lin, Hongfei; Luo, Ling; Zhao, Zhehuan; Li, Zhengguang; Zhang, Yijia; Yang, Zhihao; Wang, Jian

2017-10-10

Drug-drug interactions (DDIs) often bring unexpected side effects. The clinical recognition of DDIs is a crucial issue for both patient safety and healthcare cost control. However, although text-mining-based systems explore various methods to classify DDIs, the classification performance with regard to DDIs in long and complex sentences is still unsatisfactory. In this study, we propose an effective model that classifies DDIs from the literature by combining an attention mechanism and a recurrent neural network with long short-term memory (LSTM) units. In our approach, first, a candidate-drug-oriented input attention acting on word-embedding vectors automatically learns which words are more influential for a given drug pair. Next, the inputs merging the position- and POS-embedding vectors are passed to a bidirectional LSTM layer whose outputs at the last time step represent the high-level semantic information of the whole sentence. Finally, a softmax layer performs DDI classification. Experimental results from the DDIExtraction 2013 corpus show that our system performs the best with respect to detection and classification (84.0% and 77.3%, respectively) compared with other state-of-the-art methods. In particular, for the Medline-2013 dataset with long and complex sentences, our F-score far exceeds those of top-ranking systems by 12.6%. Our approach effectively improves the performance of DDI classification tasks. Experimental analysis demonstrates that our model performs better with respect to recognizing not only close-range but also long-range patterns among words, especially for long, complex and compound sentences.

Mapping species of submerged aquatic vegetation with multi-seasonal satellite images and considering life history information

NASA Astrophysics Data System (ADS)

Luo, Juhua; Duan, Hongtao; Ma, Ronghua; Jin, Xiuliang; Li, Fei; Hu, Weiping; Shi, Kun; Huang, Wenjiang

2017-05-01

Spatial information of the dominant species of submerged aquatic vegetation (SAV) is essential for restoration projects in eutrophic lakes, especially eutrophic Taihu Lake, China. Mapping the distribution of SAV species is very challenging and difficult using only multispectral satellite remote sensing. In this study, we proposed an approach to map the distribution of seven dominant species of SAV in Taihu Lake. Our approach involved information on the life histories of the seven SAV species and eight distribution maps of SAV from February to October. The life history information of the dominant SAV species was summarized from the literature and field surveys. Eight distribution maps of the SAV were extracted from eight 30 m HJ-CCD images from February to October in 2013 based on the classification tree models, and the overall classification accuracies for the SAV were greater than 80%. Finally, the spatial distribution of the SAV species in Taihu in 2013 was mapped using multilayer erasing approach. Based on validation, the overall classification accuracy for the seven species was 68.4%, and kappa was 0.6306, which suggests that larger differences in life histories between species can produce higher identification accuracies. The classification results show that Potamogeton malaianus was the most widely distributed species in Taihu Lake, followed by Myriophyllum spicatum, Potamogeton maackianus, Potamogeton crispus, Elodea nuttallii, Ceratophyllum demersum and Vallisneria spiralis. The information is useful for planning shallow-water habitat restoration projects.

Discriminative spatial-frequency-temporal feature extraction and classification of motor imagery EEG: An sparse regression and Weighted Naïve Bayesian Classifier-based approach.

PubMed

Miao, Minmin; Zeng, Hong; Wang, Aimin; Zhao, Changsen; Liu, Feixiang

2017-02-15

Common spatial pattern (CSP) is most widely used in motor imagery based brain-computer interface (BCI) systems. In conventional CSP algorithm, pairs of the eigenvectors corresponding to both extreme eigenvalues are selected to construct the optimal spatial filter. In addition, an appropriate selection of subject-specific time segments and frequency bands plays an important role in its successful application. This study proposes to optimize spatial-frequency-temporal patterns for discriminative feature extraction. Spatial optimization is implemented by channel selection and finding discriminative spatial filters adaptively on each time-frequency segment. A novel Discernibility of Feature Sets (DFS) criteria is designed for spatial filter optimization. Besides, discriminative features located in multiple time-frequency segments are selected automatically by the proposed sparse time-frequency segment common spatial pattern (STFSCSP) method which exploits sparse regression for significant features selection. Finally, a weight determined by the sparse coefficient is assigned for each selected CSP feature and we propose a Weighted Naïve Bayesian Classifier (WNBC) for classification. Experimental results on two public EEG datasets demonstrate that optimizing spatial-frequency-temporal patterns in a data-driven manner for discriminative feature extraction greatly improves the classification performance. The proposed method gives significantly better classification accuracies in comparison with several competing methods in the literature. The proposed approach is a promising candidate for future BCI systems. Copyright © 2016 Elsevier B.V. All rights reserved.

A curated database of cyanobacterial strains relevant for modern taxonomy and phylogenetic studies.

PubMed

Ramos, Vitor; Morais, João; Vasconcelos, Vitor M

2017-04-25

The dataset herein described lays the groundwork for an online database of relevant cyanobacterial strains, named CyanoType (http://lege.ciimar.up.pt/cyanotype). It is a database that includes categorized cyanobacterial strains useful for taxonomic, phylogenetic or genomic purposes, with associated information obtained by means of a literature-based curation. The dataset lists 371 strains and represents the first version of the database (CyanoType v.1). Information for each strain includes strain synonymy and/or co-identity, strain categorization, habitat, accession numbers for molecular data, taxonomy and nomenclature notes according to three different classification schemes, hierarchical automatic classification, phylogenetic placement according to a selection of relevant studies (including this), and important bibliographic references. The database will be updated periodically, namely by adding new strains meeting the criteria for inclusion and by revising and adding up-to-date metadata for strains already listed. A global 16S rDNA-based phylogeny is provided in order to assist users when choosing the appropriate strains for their studies.

A curated database of cyanobacterial strains relevant for modern taxonomy and phylogenetic studies

PubMed Central

Ramos, Vitor; Morais, João; Vasconcelos, Vitor M.

2017-01-01

The dataset herein described lays the groundwork for an online database of relevant cyanobacterial strains, named CyanoType (http://lege.ciimar.up.pt/cyanotype). It is a database that includes categorized cyanobacterial strains useful for taxonomic, phylogenetic or genomic purposes, with associated information obtained by means of a literature-based curation. The dataset lists 371 strains and represents the first version of the database (CyanoType v.1). Information for each strain includes strain synonymy and/or co-identity, strain categorization, habitat, accession numbers for molecular data, taxonomy and nomenclature notes according to three different classification schemes, hierarchical automatic classification, phylogenetic placement according to a selection of relevant studies (including this), and important bibliographic references. The database will be updated periodically, namely by adding new strains meeting the criteria for inclusion and by revising and adding up-to-date metadata for strains already listed. A global 16S rDNA-based phylogeny is provided in order to assist users when choosing the appropriate strains for their studies. PMID:28440791

The neuron classification problem

PubMed Central

Bota, Mihail; Swanson, Larry W.

2007-01-01

A systematic account of neuron cell types is a basic prerequisite for determining the vertebrate nervous system global wiring diagram. With comprehensive lineage and phylogenetic information unavailable, a general ontology based on structure-function taxonomy is proposed and implemented in a knowledge management system, and a prototype analysis of select regions (including retina, cerebellum, and hypothalamus) presented. The supporting Brain Architecture Knowledge Management System (BAMS) Neuron ontology is online and its user interface allows queries about terms and their definitions, classification criteria based on the original literature and “Petilla Convention” guidelines, hierarchies, and relations—with annotations documenting each ontology entry. Combined with three BAMS modules for neural regions, connections between regions and neuron types, and molecules, the Neuron ontology provides a general framework for physical descriptions and computational modeling of neural systems. The knowledge management system interacts with other web resources, is accessible in both XML and RDF/OWL, is extendible to the whole body, and awaits large-scale data population requiring community participation for timely implementation. PMID:17582506

Classification of pregnancy and labor contractions using a graph theory based analysis.

PubMed

Nader, N; Hassan, M; Falou, W; Diab, A; Al-Omar, S; Khalil, M; Marque, C

2015-08-01

In this paper, we propose a new framework to characterize the electrohysterographic (EHG) signals recorded during pregnancy and labor. The approach is based on the analysis of the propagation of the uterine electrical activity. The processing pipeline includes i) the estimation of the statistical dependencies between the different recorded EHG signals, ii) the characterization of the obtained connectivity matrices using network measures and iii) the use of these measures in clinical application: the classification between pregnancy and labor. Due to its robustness to volume conductor, we used the imaginary part of coherence in order to produce the connectivity matrix which is then transformed into a graph. We evaluate the performance of several graph measures. We also compare the results with the parameter mostly used in the literature: the peak frequency combined with the propagation velocity (PV +PF). Our results show that the use of the network measures is a promising tool to classify labor and pregnancy contractions with a small superiority of the graph strength over PV+PF.

Phylogeny of the Gadidae (sensu Svetovidov, 1948) based on their morphology and two mitochondrial genes.

PubMed

Teletchea, Fabrice; Laudet, Vincent; Hänni, Catherine

2006-01-01

Although Codfishes are probably one of the most studied groups of all teleost fishes worldwide owing to their great importance to fisheries, their phylogeny and classification are still far from being firmly established. In this study, we present phylogenetic relationships of 19 out of 22 genera traditionally included in the Gadidae based on the analysis of entire cytochrome b and partial cytochrome oxidase I genes (1530 bp). Maximum Parsimony, Maximum Likelihood, and Bayesian analyses all recovered five main clades that correspond to traditionally recognized groupings within Gadoids. The same clades were recovered with MP analysis based on 30 morphological characters (collected from the literature). Given these findings, we propose a revised provisional classification of Gadoids: one suborder Gadoidei containing two families, the Merlucciidae (1 genus) and the Gadidae (21 genera) distributed into four subfamilies: the Gadinae (12 genera), the Lotinae (3 genera), the Gaidropsarinae (3 genera), and the Phycinae (3 genera). Lastly, nuclear inserts of mitochondrial DNA (Numts) were identified in two species, i.e., Gadiculus argenteus and Melanogrammus aeglefinus.

Symmetrical compression distance for arrhythmia discrimination in cloud-based big-data services.

PubMed

Lillo-Castellano, J M; Mora-Jiménez, I; Santiago-Mozos, R; Chavarría-Asso, F; Cano-González, A; García-Alberola, A; Rojo-Álvarez, J L

2015-07-01

The current development of cloud computing is completely changing the paradigm of data knowledge extraction in huge databases. An example of this technology in the cardiac arrhythmia field is the SCOOP platform, a national-level scientific cloud-based big data service for implantable cardioverter defibrillators. In this scenario, we here propose a new methodology for automatic classification of intracardiac electrograms (EGMs) in a cloud computing system, designed for minimal signal preprocessing. A new compression-based similarity measure (CSM) is created for low computational burden, so-called weighted fast compression distance, which provides better performance when compared with other CSMs in the literature. Using simple machine learning techniques, a set of 6848 EGMs extracted from SCOOP platform were classified into seven cardiac arrhythmia classes and one noise class, reaching near to 90% accuracy when previous patient arrhythmia information was available and 63% otherwise, hence overcoming in all cases the classification provided by the majority class. Results show that this methodology can be used as a high-quality service of cloud computing, providing support to physicians for improving the knowledge on patient diagnosis.

A pathway-based view of human diseases and disease relationships.

PubMed

Li, Yong; Agarwal, Pankaj

2009-01-01

It is increasingly evident that human diseases are not isolated from each other. Understanding how different diseases are related to each other based on the underlying biology could provide new insights into disease etiology, classification, and shared biological mechanisms. We have taken a computational approach to studying disease relationships through 1) systematic identification of disease associated genes by literature mining, 2) associating diseases to biological pathways where disease genes are enriched, and 3) linking diseases together based on shared pathways. We identified 4,195 candidate disease associated genes for 1028 diseases. On average, about 50% of disease associated genes of a disease are statistically mapped to pathways. We generated a disease network which consists of 591 diseases and 6,931 disease relationships. We examined properties of this network and provided examples of novel disease relationships which cannot be readily captured through simple literature search or gene overlap analysis. Our results could potentially provide insights into the design of novel, pathway-guided therapeutic interventions for diseases.

Hippocampome.org: a knowledge base of neuron types in the rodent hippocampus.

PubMed

Wheeler, Diek W; White, Charise M; Rees, Christopher L; Komendantov, Alexander O; Hamilton, David J; Ascoli, Giorgio A

2015-09-24

Hippocampome.org is a comprehensive knowledge base of neuron types in the rodent hippocampal formation (dentate gyrus, CA3, CA2, CA1, subiculum, and entorhinal cortex). Although the hippocampal literature is remarkably information-rich, neuron properties are often reported with incompletely defined and notoriously inconsistent terminology, creating a formidable challenge for data integration. Our extensive literature mining and data reconciliation identified 122 neuron types based on neurotransmitter, axonal and dendritic patterns, synaptic specificity, electrophysiology, and molecular biomarkers. All ∼3700 annotated properties are individually supported by specific evidence (∼14,000 pieces) in peer-reviewed publications. Systematic analysis of this unprecedented amount of machine-readable information reveals novel correlations among neuron types and properties, the potential connectivity of the full hippocampal circuitry, and outstanding knowledge gaps. User-friendly browsing and online querying of Hippocampome.org may aid design and interpretation of both experiments and simulations. This powerful, simple, and extensible neuron classification endeavor is unique in its detail, utility, and completeness.

Knowledge Discovery in Literature Data Bases

NASA Astrophysics Data System (ADS)

Albrecht, Rudolf; Merkl, Dieter

The concept of knowledge discovery as defined through ``establishing previously unknown and unsuspected relations of features in a data base'' is, cum grano salis, relatively easy to implement for data bases containing numerical data. Increasingly we find at our disposal data bases containing scientific literature. Computer assisted detection of unknown relations of features in such data bases would be extremely valuable and would lead to new scientific insights. However, the current representation of scientific knowledge in such data bases is not conducive to computer processing. Any correlation of features still has to be done by the human reader, a process which is plagued by ineffectiveness and incompleteness. On the other hand we note that considerable progress is being made in an area where reading all available material is totally prohibitive: the World Wide Web. Robots and Web crawlers mine the Web continuously and construct data bases which allow the identification of pages of interest in near real time. An obvious step is to categorize and classify the documents in the text data base. This can be used to identify papers worth reading, or which are of unexpected cross-relevance. We show the results of first experiments using unsupervised classification based on neural networks.

Measures and metrics for software development

NASA Technical Reports Server (NTRS)

1984-01-01

The evaluations of and recommendations for the use of software development measures based on the practical and analytical experience of the Software Engineering Laboratory are discussed. The basic concepts of measurement and system of classification for measures are described. The principal classes of measures defined are explicit, analytic, and subjective. Some of the major software measurement schemes appearing in the literature are derived. The applications of specific measures in a production environment are explained. These applications include prediction and planning, review and assessment, and evaluation and selection.

Intellectual developmental disorders: towards a new name, definition and framework for "mental retardation/intellectual disability" in ICD-11.

PubMed

Salvador-Carulla, Luis; Reed, Geoffrey M; Vaez-Azizi, Leila M; Cooper, Sally-Ann; Martinez-Leal, Rafael; Bertelli, Marco; Adnams, Colleen; Cooray, Sherva; Deb, Shoumitro; Akoury-Dirani, Leyla; Girimaji, Satish Chandra; Katz, Gregorio; Kwok, Henry; Luckasson, Ruth; Simeonsson, Rune; Walsh, Carolyn; Munir, Kemir; Saxena, Shekhar

2011-10-01

Although "intellectual disability" has widely replaced the term "mental retardation", the debate as to whether this entity should be conceptualized as a health condition or as a disability has intensified as the revision of the World Health Organization (WHO)'s International Classification of Diseases (ICD) advances. Defining intellectual disability as a health condition is central to retaining it in ICD, with significant implications for health policy and access to health services. This paper presents the consensus reached to date by the WHO ICD Working Group on the Classification of Intellectual Disabilities. Literature reviews were conducted and a mixed qualitative approach was followed in a series of meetings to produce consensus-based recommendations combining prior expert knowledge and available evidence. The Working Group proposes replacing mental retardation with intellectual developmental disorders, defined as "a group of developmental conditions characterized by significant impairment of cognitive functions, which are associated with limitations of learning, adaptive behaviour and skills". The Working Group further advises that intellectual developmental disorders be incorporated in the larger grouping (parent category) of neurodevelopmental disorders, that current subcategories based on clinical severity (i.e., mild, moderate, severe, profound) be continued, and that problem behaviours be removed from the core classification structure of intellectual developmental disorders and instead described as associated features.

High-density force myography: A possible alternative for upper-limb prosthetic control.

PubMed

Radmand, Ashkan; Scheme, Erik; Englehart, Kevin

2016-01-01

Several multiple degree-of-freedom upper-limb prostheses that have the promise of highly dexterous control have recently been developed. Inadequate controllability, however, has limited adoption of these devices. Introducing more robust control methods will likely result in higher acceptance rates. This work investigates the suitability of using high-density force myography (HD-FMG) for prosthetic control. HD-FMG uses a high-density array of pressure sensors to detect changes in the pressure patterns between the residual limb and socket caused by the contraction of the forearm muscles. In this work, HD-FMG outperforms the standard electromyography (EMG)-based system in detecting different wrist and hand gestures. With the arm in a fixed, static position, eight hand and wrist motions were classified with 0.33% error using the HD-FMG technique. Comparatively, classification errors in the range of 2.2%-11.3% have been reported in the literature for multichannel EMG-based approaches. As with EMG, position variation in HD-FMG can introduce classification error, but incorporating position variation into the training protocol reduces this effect. Channel reduction was also applied to the HD-FMG technique to decrease the dimensionality of the problem as well as the size of the sensorized area. We found that with informed, symmetric channel reduction, classification error could be decreased to 0.02%.

Epileptic Seizure Detection Based on Time-Frequency Images of EEG Signals using Gaussian Mixture Model and Gray Level Co-Occurrence Matrix Features.

PubMed

Li, Yang; Cui, Weigang; Luo, Meilin; Li, Ke; Wang, Lina

2018-01-25

The electroencephalogram (EEG) signal analysis is a valuable tool in the evaluation of neurological disorders, which is commonly used for the diagnosis of epileptic seizures. This paper presents a novel automatic EEG signal classification method for epileptic seizure detection. The proposed method first employs a continuous wavelet transform (CWT) method for obtaining the time-frequency images (TFI) of EEG signals. The processed EEG signals are then decomposed into five sub-band frequency components of clinical interest since these sub-band frequency components indicate much better discriminative characteristics. Both Gaussian Mixture Model (GMM) features and Gray Level Co-occurrence Matrix (GLCM) descriptors are then extracted from these sub-band TFI. Additionally, in order to improve classification accuracy, a compact feature selection method by combining the ReliefF and the support vector machine-based recursive feature elimination (RFE-SVM) algorithm is adopted to select the most discriminative feature subset, which is an input to the SVM with the radial basis function (RBF) for classifying epileptic seizure EEG signals. The experimental results from a publicly available benchmark database demonstrate that the proposed approach provides better classification accuracy than the recently proposed methods in the literature, indicating the effectiveness of the proposed method in the detection of epileptic seizures.

The Variability in Surgical Margin Reporting in Limb Salvage Surgery for Sarcoma

PubMed Central

Hoang, Kevin; Gao, Yubo; Miller, Benjamin J.

2015-01-01

Background Surgical margins are a standard reported measurement in tumor surgery that has implications for functional outcome, local control, and overall survival. There is no single accepted classification, and it is unclear what form or margin reporting predominates in the sarcoma literature. Methods We performed a PubMed literature search to identify articles that reported surgical margins and oncologic outcomes in limb salvage surgery for sarcoma from 1980 to 2013. We recorded the margin classification, specialty of the journal, specialty of the author, and location of the authors' institution. Results We found that 159/448 (35%) of articles included in the study did not report surgical margins. Of the 289 papers that did include data on margins, 160 (55%) of articles used Enneking's classification. There has been an increase over time in the proportion of articles reporting surgical margins by the residual tumor (R) classification and the proportion of articles reporting margins dichotomously as “positive” or “negative.” Conclusions We did not find a common method for reporting margins in the limb salvage sarcoma literature. Of most concern was over 1/3 of clinical reports of oncologic outcomes did not include margin status, which substantially compromises any conclusions that readers may infer about treatment success, local recurrence, or survival. We believe there should be renewed efforts to encourage use of a common surgical margin reporting system that is simple, reproducible, and prognostic. PMID:26361463

Categories for Names or Names of Categories? The Interplay Between Domain-Specific Conceptual Structure and Language.

ERIC Educational Resources Information Center

Diesendruck, Gil

2003-01-01

Drawing on the notion of the domain-specificity of recognition, reviews evidence on the effect of language in classification of and reasoning about categories from different domains. Looks at anthropological infant classification, and preschool categorization literature. Suggests the causal nature and indicative power of animal categories seem to…

Using Patent Classification to Discover Chemical Information in a Free Patent Database: Challenges and Opportunities

ERIC Educational Resources Information Center

Ha¨rtinger, Stefan; Clarke, Nigel

2016-01-01

Developing skills for searching the patent literature is an essential element of chemical information literacy programs at the university level. The present article creates awareness of patents as a rich source of chemical information. Patent classification is introduced as a key-component in comprehensive search strategies. The free Espacenet…

Child development in the NANDA-I and International Classification for Nursing Practices Nursing Classifications*.

PubMed

de Souza, Juliana Martins; Veríssimo, Maria De La Ó Ramallo

2013-02-01

Identify and analyze the NANDA-I diagnoses and the focus terms of the International Classification for Nursing Practices (ICNP) related to child development. Literature, reflections about clinical experience, and a model case. DATA SYNTHESE: The current diagnoses proposed by NANDA-I and the ICNP focus terms do not encompass the extent of the child development phenomenon. It is necessary studying the child development concept to improve the definition of the ICNP focus terms and the accuracy of NANDA-I diagnoses. Discussing the nursing classifications can improve their understanding and use. © 2012, The Authors. International Journal of Nursing Knowledge © 2012, NANDA International.

Landcover classification in MRF context using Dempster-Shafer fusion for multisensor imagery.

PubMed

Sarkar, Anjan; Banerjee, Anjan; Banerjee, Nilanjan; Brahma, Siddhartha; Kartikeyan, B; Chakraborty, Manab; Majumder, K L

2005-05-01

This work deals with multisensor data fusion to obtain landcover classification. The role of feature-level fusion using the Dempster-Shafer rule and that of data-level fusion in the MRF context is studied in this paper to obtain an optimally segmented image. Subsequently, segments are validated and classification accuracy for the test data is evaluated. Two examples of data fusion of optical images and a synthetic aperture radar image are presented, each set having been acquired on different dates. Classification accuracies of the technique proposed are compared with those of some recent techniques in literature for the same image data.

A survey on the geographic scope of textual documents

NASA Astrophysics Data System (ADS)

Monteiro, Bruno R.; Davis, Clodoveu A.; Fonseca, Fred

2016-11-01

Recognizing references to places in texts is needed in many applications, such as search engines, location-based social media and document classification. In this paper we present a survey of methods and techniques for the recognition and identification of places referenced in texts. We discuss concepts and terminology, and propose a classification of the solutions given in the literature. We introduce a definition of the Geographic Scope Resolution (GSR) problem, dividing it in three steps: geoparsing, reference resolution, and grounding references. Solutions to the first two steps are organized according to the method used, and solutions to the third step are organized according to the type of output produced. We found that it is difficult to compare existing solutions directly to one another, because they often create their own benchmarking data, targeted to their own problem.

Nursing diagnoses in pemphigus vulgaris: a case study.

PubMed

Pena, Silvana B; Guimarães, Heloísa C Q C P; Bassoli, Sidinéia R B; Casarin, Santina N A; Herdman, Trace Heather; de Barros, Alba L B L

2013-10-01

This case study illustrates the use of the nursing process based upon the standardized nursing diagnoses approved by NANDA International (NANDA-I), and using the Nursing Outcomes Classification (NOC) and the Nursing Interventions Classification (NIC) in the care of a patient with pemphigus vulgaris (PV). The published literature on PV and the experience and expertise of the authors in working with people with impaired skin integrity and PV were used to develop this case study. The accuracy of nursing diagnoses and appropriateness of the nursing interventions were supported by the positive health outcomes of the patient. Impaired skin integrity is a human response diagnosed by nurses, and early treatment is important due to the vulnerability of these patients. The case study contributes to nursing knowledge for professionals who care for patients with PV. © 2013 NANDA International.

Pornography classification: The hidden clues in video space-time.

PubMed

Moreira, Daniel; Avila, Sandra; Perez, Mauricio; Moraes, Daniel; Testoni, Vanessa; Valle, Eduardo; Goldenstein, Siome; Rocha, Anderson

2016-11-01

As web technologies and social networks become part of the general public's life, the problem of automatically detecting pornography is into every parent's mind - nobody feels completely safe when their children go online. In this paper, we focus on video-pornography classification, a hard problem in which traditional methods often employ still-image techniques - labeling frames individually prior to a global decision. Frame-based approaches, however, ignore significant cogent information brought by motion. Here, we introduce a space-temporal interest point detector and descriptor called Temporal Robust Features (TRoF). TRoF was custom-tailored for efficient (low processing time and memory footprint) and effective (high classification accuracy and low false negative rate) motion description, particularly suited to the task at hand. We aggregate local information extracted by TRoF into a mid-level representation using Fisher Vectors, the state-of-the-art model of Bags of Visual Words (BoVW). We evaluate our original strategy, contrasting it both to commercial pornography detection solutions, and to BoVW solutions based upon other space-temporal features from the scientific literature. The performance is assessed using the Pornography-2k dataset, a new challenging pornographic benchmark, comprising 2000 web videos and 140h of video footage. The dataset is also a contribution of this work and is very assorted, including both professional and amateur content, and it depicts several genres of pornography, from cartoon to live action, with diverse behavior and ethnicity. The best approach, based on a dense application of TRoF, yields a classification error reduction of almost 79% when compared to the best commercial classifier. A sparse description relying on TRoF detector is also noteworthy, for yielding a classification error reduction of over 69%, with 19× less memory footprint than the dense solution, and yet can also be implemented to meet real-time requirements. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Summary of the National Institute of Child Health and Human Development-best pharmaceuticals for Children Act Pediatric Formulation Initiatives Workshop-Pediatric Biopharmaceutics Classification System Working Group.

PubMed

Abdel-Rahman, Susan M; Amidon, Gordon L; Kaul, Ajay; Lukacova, Viera; Vinks, Alexander A; Knipp, Gregory T

2012-11-01

The Biopharmaceutics Classification System (BCS) allows compounds to be classified based on their in vitro solubility and intestinal permeability. The BCS has found widespread use in the pharmaceutical community to be an enabling guide for the rational selection of compounds, formulation for clinical advancement, and generic biowaivers. The Pediatric Biopharmaceutics Classification System (PBCS) Working Group was convened to consider the possibility of developing an analogous pediatric-based classification system. Because there are distinct developmental differences that can alter intestinal contents, volumes, permeability, and potentially biorelevant solubilities at different ages, the PBCS Working Group focused on identifying age-specific issues that need to be considered in establishing a flexible, yet rigorous PBCS. We summarized the findings of the PBCS Working Group and provided insights into considerations required for the development of a PBCS. Through several meetings conducted both at The Eunice Kennedy Shriver National Institute of Child Health, Human Development-US Pediatric Formulation Initiative Workshop (November 2011) and via teleconferences, the PBCS Working Group considered several high-level questions that were raised to frame the classification system. In addition, the PBCS Working Group identified a number of knowledge gaps that need to be addressed to develop a rigorous PBCS. It was determined that for a PBCS to be truly meaningful, it needs to be broken down into several different age groups that account for developmental changes in intestinal permeability, luminal contents, and gastrointestinal (GI) transit. Several critical knowledge gaps were identified, including (1) a lack of fully understanding the ontogeny of drug metabolizing enzymes and transporters along the GI tract, in the liver, and in the kidney; (2) an incomplete understanding of age-based changes in the GI, liver, and kidney physiology; (3) a clear need to better understand age-based intestinal permeability and fraction absorbed required to develop the PBCS; (4) a clear need for the development and organization of pediatric tissue biobanks to serve as a source for ontogenic research; and (5) a lack of literature published in age-based pediatric pharmacokinetics to build physiologically- and population-based pharmacokinetic (PBPK) databases. To begin the process of establishing a PBPK model, 10 pediatric therapeutic agents were selected (based on their adult BCS classifications). These agents should be targeted for additional research in the future. The PBCS Working Group also identified several areas where greater emphasis on research was needed to enable the development of a PBCS. Copyright © 2012 Elsevier HS Journals, Inc. All rights reserved.

The Value of Ensari's Proposal in Evaluating the Mucosal Pathology of Childhood Celiac Disease: Old Classification versus New Version.

PubMed

Güreşci, Servet; Hızlı, Samil; Simşek, Gülçin Güler

2012-09-01

Small intestinal biopsy remains the gold standard in diagnosing celiac disease (CD); however, the wide spectrum of histopathological states and differential diagnosis of CD is still a diagnostic problem for pathologists. Recently, Ensari reviewed the literature and proposed an update of the histopathological diagnosis and classification for CD. In this study, the histopathological materials of 54 children in whom CD was diagnosed at our hospital were reviewed to compare the previous Marsh and Modified Marsh-Oberhuber classifications with this new proposal. In this study, we show that the Ensari classification is as accurate as the Marsh and Modified Marsh classifications in describing the consecutive states of mucosal damage seen in CD. Ensari's classification is simple, practical and facilitative in diagnosing and subtyping of mucosal pathology of CD.

Telemedicine for Developing Countries. A Survey and Some Design Issues.

PubMed

Combi, Carlo; Pozzani, Gabriele; Pozzi, Giuseppe

2016-11-02

Developing countries need telemedicine applications that help in many situations, when physicians are a small number with respect to the population, when specialized physicians are not available, when patients and physicians in rural villages need assistance in the delivery of health care. Moreover, the requirements of telemedicine applications for developing countries are somewhat more demanding than for developed countries. Indeed, further social, organizational, and technical aspects need to be considered for successful telemedicine applications in developing countries. We consider all the major projects in telemedicine, devoted to developing countries, as described by the proper scientific literature. On the basis of such literature, we want to define a specific taxonomy that allows a proper classification and a fast overview of telemedicine projects in developing countries. Moreover, by considering both the literature and some recent direct experiences, we want to complete such overview by discussing some design issues to be taken into consideration when developing telemedicine software systems. We considered and reviewed the major conferences and journals in depth, and looked for reports on the telemedicine projects. We provide the reader with a survey of the main projects and systems, from which we derived a taxonomy of features of telemedicine systems for developing countries. We also propose and discuss some classification criteria for design issues, based on the lessons learned in this research area. We highlight some challenges and recommendations to be considered when designing a telemedicine system for developing countries.

Telemedicine for Developing Countries

PubMed Central

Combi, Carlo; Pozzani, Gabriele

2016-01-01

Summary Background Developing countries need telemedicine applications that help in many situations, when physicians are a small number with respect to the population, when specialized physicians are not available, when patients and physicians in rural villages need assistance in the delivery of health care. Moreover, the requirements of telemedicine applications for developing countries are somewhat more demanding than for developed countries. Indeed, further social, organizational, and technical aspects need to be considered for successful telemedicine applications in developing countries. Objective We consider all the major projects in telemedicine, devoted to developing countries, as described by the proper scientific literature. On the basis of such literature, we want to define a specific taxonomy that allows a proper classification and a fast overview of telemedicine projects in developing countries. Moreover, by considering both the literature and some recent direct experiences, we want to complete such overview by discussing some design issues to be taken into consideration when developing telemedicine software systems. Methods We considered and reviewed the major conferences and journals in depth, and looked for reports on the telemedicine projects. Results We provide the reader with a survey of the main projects and systems, from which we derived a taxonomy of features of telemedicine systems for developing countries. We also propose and discuss some classification criteria for design issues, based on the lessons learned in this research area. Conclusions We highlight some challenges and recommendations to be considered when designing a telemedicine system for developing countries. PMID:27803948

Multifocal humeral fractures.

PubMed

Maresca, A; Pascarella, R; Bettuzzi, C; Amendola, L; Politano, R; Fantasia, R; Del Torto, M

2014-02-01

Multifocal humeral fractures are extremely rare. These may affect the neck and the shaft, the shaft alone, or the diaphysis and the distal humerus. There is no classification of these fractures in the literature. From 2004 to 2010, 717 patients with humeral fracture were treated surgically at our department. Thirty-five patients presented with an associated fracture of the proximal and diaphyseal humerus: synthesis was performed with plate and screws in 34 patients, and the remaining patient had an open fracture that was treated with an external fixator. Mean follow-up was 3 years and 3 months. A classification is proposed in which type A fractures are those affecting the proximal and the humeral shaft, type B the diaphysis alone, and type C the diaphysis in association with the distal humerus. Type A fractures are then divided into three subgroups: A-I, undisplaced fracture of the proximal humerus and displaced shaft fracture; A-II: displaced fracture of the proximal and humeral shaft; and A-III: multifragmentary fracture affecting the proximal humerus and extending to the diaphysis. Multifocal humeral fractures are very rare and little described in the literature, both for classification and treatment. The AO classification describes bifocal fracture of the humeral diaphysis, type B and C. The classification suggested in this article mainly concerns fractures involving the proximal and humeral shaft. A simple classification of multifocal fractures is suggested to help the surgeon choose the most suitable type of synthesis for surgical treatment. Copyright © 2013 Elsevier Ltd. All rights reserved.

The Human Skeletal Muscle Proteome Project: a reappraisal of the current literature

PubMed Central

Gonzalez‐Freire, Marta; Semba, Richard D.; Ubaida‐Mohien, Ceereena; Fabbri, Elisa; Scalzo, Paul; Højlund, Kurt; Dufresne, Craig; Lyashkov, Alexey

2016-01-01

Abstract Skeletal muscle is a large organ that accounts for up to half the total mass of the human body. A progressive decline in muscle mass and strength occurs with ageing and in some individuals configures the syndrome of ‘sarcopenia’, a condition that impairs mobility, challenges autonomy, and is a risk factor for mortality. The mechanisms leading to sarcopenia as well as myopathies are still little understood. The Human Skeletal Muscle Proteome Project was initiated with the aim to characterize muscle proteins and how they change with ageing and disease. We conducted an extensive review of the literature and analysed publically available protein databases. A systematic search of peer‐reviewed studies was performed using PubMed. Search terms included ‘human’, ‘skeletal muscle’, ‘proteome’, ‘proteomic(s)’, and ‘mass spectrometry’, ‘liquid chromatography‐mass spectrometry (LC‐MS/MS)’. A catalogue of 5431 non‐redundant muscle proteins identified by mass spectrometry‐based proteomics from 38 peer‐reviewed scientific publications from 2002 to November 2015 was created. We also developed a nosology system for the classification of muscle proteins based on localization and function. Such inventory of proteins should serve as a useful background reference for future research on changes in muscle proteome assessed by quantitative mass spectrometry‐based proteomic approaches that occur with ageing and diseases. This classification and compilation of the human skeletal muscle proteome can be used for the identification and quantification of proteins in skeletal muscle to discover new mechanisms for sarcopenia and specific muscle diseases that can be targeted for the prevention and treatment. PMID:27897395

Consensus or controversy? The classification and treatment decision-making by 491 maxillofacial surgeons from around the world in three cases of a unilateral mandibular condyle fracture.

PubMed

Kommers, Sofie C; Boffano, Paolo; Forouzanfar, Tymour

2015-12-01

Many studies are available in the literature on both classification and treatment of unilateral mandibular condyle fractures. To date however, controversy regarding the best treatment for unilateral mandibular condyle fractures remains. In this study, an attempt was made to quantify the level of agreement between a sample of maxillofacial surgeons worldwide, on the classification and treatment decisions in three different unilateral mandibular condyle fracture cases. In total, 491 of 3044 participants responded. In all three mandibular condyle fracture cases, a fairly high level of disagreement was found. Only in the case of a subcondylar fracture, assuming dysocclusion was present, more than 81% of surgeons agreed that the best treatment would be open reduction and internal fixation. Based on the study results, there is considerable variation among surgeons worldwide with regard to treatment of unilateral mandibular condyle fracture. 3D imaging in higher fractures tends to lead to more invasive treatment decisions. Copyright © 2015 European Association for Cranio-Maxillo-Facial Surgery. Published by Elsevier Ltd. All rights reserved.

An incremental approach to genetic-algorithms-based classification.

PubMed

Guan, Sheng-Uei; Zhu, Fangming

2005-04-01

Incremental learning has been widely addressed in the machine learning literature to cope with learning tasks where the learning environment is ever changing or training samples become available over time. However, most research work explores incremental learning with statistical algorithms or neural networks, rather than evolutionary algorithms. The work in this paper employs genetic algorithms (GAs) as basic learning algorithms for incremental learning within one or more classifier agents in a multiagent environment. Four new approaches with different initialization schemes are proposed. They keep the old solutions and use an "integration" operation to integrate them with new elements to accommodate new attributes, while biased mutation and crossover operations are adopted to further evolve a reinforced solution. The simulation results on benchmark classification data sets show that the proposed approaches can deal with the arrival of new input attributes and integrate them with the original input space. It is also shown that the proposed approaches can be successfully used for incremental learning and improve classification rates as compared to the retraining GA. Possible applications for continuous incremental training and feature selection are also discussed.

TogoDoc server/client system: smart recommendation and efficient management of life science literature.

PubMed

Iwasaki, Wataru; Yamamoto, Yasunori; Takagi, Toshihisa

2010-12-13

In this paper, we describe a server/client literature management system specialized for the life science domain, the TogoDoc system (Togo, pronounced Toe-Go, is a romanization of a Japanese word for integration). The server and the client program cooperate closely over the Internet to provide life scientists with an effective literature recommendation service and efficient literature management. The content-based and personalized literature recommendation helps researchers to isolate interesting papers from the "tsunami" of literature, in which, on average, more than one biomedical paper is added to MEDLINE every minute. Because researchers these days need to cover updates of much wider topics to generate hypotheses using massive datasets obtained from public databases or omics experiments, the importance of having an effective literature recommendation service is rising. The automatic recommendation is based on the content of personal literature libraries of electronic PDF papers. The client program automatically analyzes these files, which are sometimes deeply buried in storage disks of researchers' personal computers. Just saving PDF papers to the designated folders makes the client program automatically analyze and retrieve metadata, rename file names, synchronize the data to the server, and receive the recommendation lists of newly published papers, thus accomplishing effortless literature management. In addition, the tag suggestion and associative search functions are provided for easy classification of and access to past papers (researchers who read many papers sometimes only vaguely remember or completely forget what they read in the past). The TogoDoc system is available for both Windows and Mac OS X and is free. The TogoDoc Client software is available at http://tdc.cb.k.u-tokyo.ac.jp/, and the TogoDoc server is available at https://docman.dbcls.jp/pubmed_recom.

TogoDoc Server/Client System: Smart Recommendation and Efficient Management of Life Science Literature

PubMed Central

Takagi, Toshihisa

2010-01-01

In this paper, we describe a server/client literature management system specialized for the life science domain, the TogoDoc system (Togo, pronounced Toe-Go, is a romanization of a Japanese word for integration). The server and the client program cooperate closely over the Internet to provide life scientists with an effective literature recommendation service and efficient literature management. The content-based and personalized literature recommendation helps researchers to isolate interesting papers from the “tsunami” of literature, in which, on average, more than one biomedical paper is added to MEDLINE every minute. Because researchers these days need to cover updates of much wider topics to generate hypotheses using massive datasets obtained from public databases or omics experiments, the importance of having an effective literature recommendation service is rising. The automatic recommendation is based on the content of personal literature libraries of electronic PDF papers. The client program automatically analyzes these files, which are sometimes deeply buried in storage disks of researchers' personal computers. Just saving PDF papers to the designated folders makes the client program automatically analyze and retrieve metadata, rename file names, synchronize the data to the server, and receive the recommendation lists of newly published papers, thus accomplishing effortless literature management. In addition, the tag suggestion and associative search functions are provided for easy classification of and access to past papers (researchers who read many papers sometimes only vaguely remember or completely forget what they read in the past). The TogoDoc system is available for both Windows and Mac OS X and is free. The TogoDoc Client software is available at http://tdc.cb.k.u-tokyo.ac.jp/, and the TogoDoc server is available at https://docman.dbcls.jp/pubmed_recom. PMID:21179453

Energy-Based Metrics for Arthroscopic Skills Assessment.

PubMed

Poursartip, Behnaz; LeBel, Marie-Eve; McCracken, Laura C; Escoto, Abelardo; Patel, Rajni V; Naish, Michael D; Trejos, Ana Luisa

2017-08-05

Minimally invasive skills assessment methods are essential in developing efficient surgical simulators and implementing consistent skills evaluation. Although numerous methods have been investigated in the literature, there is still a need to further improve the accuracy of surgical skills assessment. Energy expenditure can be an indication of motor skills proficiency. The goals of this study are to develop objective metrics based on energy expenditure, normalize these metrics, and investigate classifying trainees using these metrics. To this end, different forms of energy consisting of mechanical energy and work were considered and their values were divided by the related value of an ideal performance to develop normalized metrics. These metrics were used as inputs for various machine learning algorithms including support vector machines (SVM) and neural networks (NNs) for classification. The accuracy of the combination of the normalized energy-based metrics with these classifiers was evaluated through a leave-one-subject-out cross-validation. The proposed method was validated using 26 subjects at two experience levels (novices and experts) in three arthroscopic tasks. The results showed that there are statistically significant differences between novices and experts for almost all of the normalized energy-based metrics. The accuracy of classification using SVM and NN methods was between 70% and 95% for the various tasks. The results show that the normalized energy-based metrics and their combination with SVM and NN classifiers are capable of providing accurate classification of trainees. The assessment method proposed in this study can enhance surgical training by providing appropriate feedback to trainees about their level of expertise and can be used in the evaluation of proficiency.

Cardiovascular, diabetes, and cancer strips: evidences, mechanisms, and classifications

PubMed Central

Wu, Qing-Hua; Hu, Da-Yi

2014-01-01

Objectives To report and name firstly that there are cardiovascular disease (CVD), diabetes mellitus (DM) and cancers (CDC) strips; and disclose their mechanisms, classifications, and clinical significances. Study design Narrative and systematic review study and interpretive analysis. Methods Data sources and study selection: to collect and present related evidences on CDC strips from evidence-based, open-access, both Chinese- and English-language literatures in recent 10 years on clinical trials from PubMed according to keywords “CVD, DM and cancers” as well as authors’ extensive clinical experience with the treatment of more than fifty thousands of patients with CVD, diabetes and cancers over the past decades, and analyze their related mechanisms and categories which based on authors’ previous works. Data extraction: data were mainly extracted from 48 articles which are listed in the reference section of this review. Qualitative, quantitative and mixed data were included, narratively and systematically reviewed. Results With several conceptual and technical breakthrough, authors present related evidences on CDC strips, these are, CVD and DM, DM and cancers, cancers and CVD linked, respectively; And “Bad SEED” +/– “bad soil” theory or doctrine may explain this phenomenon due to “internal environmental injure, abnormal or unbalance” in human body resulting from the role of risk factors (RFs) related multi-pathways and multi-targets, which including organ & tissue (e.g., vascular-specific), cell and gene-based mechanisms. Their classifications include main strips/type B, and Branches/type A as showed by tables and figures in this article. Conclusions There are CDC strips and related mechanisms and classifications. CDC strips may help us to understand, prevent, and control related common non-communicable diseases (NCDs) as well as these high risk strips. PMID:25276377

Prospective identification of adolescent suicide ideation using classification tree analysis: Models for community-based screening.

PubMed

Hill, Ryan M; Oosterhoff, Benjamin; Kaplow, Julie B

2017-07-01

Although a large number of risk markers for suicide ideation have been identified, little guidance has been provided to prospectively identify adolescents at risk for suicide ideation within community settings. The current study addressed this gap in the literature by utilizing classification tree analysis (CTA) to provide a decision-making model for screening adolescents at risk for suicide ideation. Participants were N = 4,799 youth (Mage = 16.15 years, SD = 1.63) who completed both Waves 1 and 2 of the National Longitudinal Study of Adolescent to Adult Health. CTA was used to generate a series of decision rules for identifying adolescents at risk for reporting suicide ideation at Wave 2. Findings revealed 3 distinct solutions with varying sensitivity and specificity for identifying adolescents who reported suicide ideation. Sensitivity of the classification trees ranged from 44.6% to 77.6%. The tree with greatest specificity and lowest sensitivity was based on a history of suicide ideation. The tree with moderate sensitivity and high specificity was based on depressive symptoms, suicide attempts or suicide among family and friends, and social support. The most sensitive but least specific tree utilized these factors and gender, ethnicity, hours of sleep, school-related factors, and future orientation. These classification trees offer community organizations options for instituting large-scale screenings for suicide ideation risk depending on the available resources and modality of services to be provided. This study provides a theoretically and empirically driven model for prospectively identifying adolescents at risk for suicide ideation and has implications for preventive interventions among at-risk youth. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Managing the Sick Child in the Era of Declining Malaria Transmission: Development of ALMANACH, an Electronic Algorithm for Appropriate Use of Antimicrobials.

PubMed

Rambaud-Althaus, Clotilde; Shao, Amani Flexson; Kahama-Maro, Judith; Genton, Blaise; d'Acremont, Valérie

2015-01-01

To review the available knowledge on epidemiology and diagnoses of acute infections in children aged 2 to 59 months in primary care setting and develop an electronic algorithm for the Integrated Management of Childhood Illness to reach optimal clinical outcome and rational use of medicines. A structured literature review in Medline, Embase and the Cochrane Database of Systematic Review (CDRS) looked for available estimations of diseases prevalence in outpatients aged 2-59 months, and for available evidence on i) accuracy of clinical predictors, and ii) performance of point-of-care tests for targeted diseases. A new algorithm for the management of childhood illness (ALMANACH) was designed based on evidence retrieved and results of a study on etiologies of fever in Tanzanian children outpatients. The major changes in ALMANACH compared to IMCI (2008 version) are the following: i) assessment of 10 danger signs, ii) classification of non-severe children into febrile and non-febrile illness, the latter receiving no antibiotics, iii) classification of pneumonia based on a respiratory rate threshold of 50 assessed twice for febrile children 12-59 months; iv) malaria rapid diagnostic test performed for all febrile children. In the absence of identified source of fever at the end of the assessment, v) urine dipstick performed for febrile children <2 years to consider urinary tract infection, vi) classification of 'possible typhoid' for febrile children >2 years with abdominal tenderness; and lastly vii) classification of 'likely viral infection' in case of negative results. This smartphone-run algorithm based on new evidence and two point-of-care tests should improve the quality of care of <5 year children and lead to more rational use of antimicrobials.

Managing the Sick Child in the Era of Declining Malaria Transmission: Development of ALMANACH, an Electronic Algorithm for Appropriate Use of Antimicrobials

PubMed Central

Rambaud-Althaus, Clotilde; Shao, Amani Flexson; Genton, Blaise; d’Acremont, Valérie

2015-01-01

Objective To review the available knowledge on epidemiology and diagnoses of acute infections in children aged 2 to 59 months in primary care setting and develop an electronic algorithm for the Integrated Management of Childhood Illness to reach optimal clinical outcome and rational use of medicines. Methods A structured literature review in Medline, Embase and the Cochrane Database of Systematic Review (CDRS) looked for available estimations of diseases prevalence in outpatients aged 2-59 months, and for available evidence on i) accuracy of clinical predictors, and ii) performance of point-of-care tests for targeted diseases. A new algorithm for the management of childhood illness (ALMANACH) was designed based on evidence retrieved and results of a study on etiologies of fever in Tanzanian children outpatients. Findings The major changes in ALMANACH compared to IMCI (2008 version) are the following: i) assessment of 10 danger signs, ii) classification of non-severe children into febrile and non-febrile illness, the latter receiving no antibiotics, iii) classification of pneumonia based on a respiratory rate threshold of 50 assessed twice for febrile children 12-59 months; iv) malaria rapid diagnostic test performed for all febrile children. In the absence of identified source of fever at the end of the assessment, v) urine dipstick performed for febrile children <2years to consider urinary tract infection, vi) classification of ‘possible typhoid’ for febrile children >2 years with abdominal tenderness; and lastly vii) classification of ‘likely viral infection’ in case of negative results. Conclusion This smartphone-run algorithm based on new evidence and two point-of-care tests should improve the quality of care of <5 year children and lead to more rational use of antimicrobials. PMID:26161753

Geometric classification of scalp hair for valid drug testing, 6 more reliable than 8 hair curl groups.

PubMed

Mkentane, K; Van Wyk, J C; Sishi, N; Gumedze, F; Ngoepe, M; Davids, L M; Khumalo, N P

2017-01-01

Curly hair is reported to contain higher lipid content than straight hair, which may influence incorporation of lipid soluble drugs. The use of race to describe hair curl variation (Asian, Caucasian and African) is unscientific yet common in medical literature (including reports of drug levels in hair). This study investigated the reliability of a geometric classification of hair (based on 3 measurements: the curve diameter, curl index and number of waves). After ethical approval and informed consent, proximal virgin (6cm) hair sampled from the vertex of scalp in 48 healthy volunteers were evaluated. Three raters each scored hairs from 48 volunteers at two occasions each for the 8 and 6-group classifications. One rater applied the 6-group classification to 80 additional volunteers in order to further confirm the reliability of this system. The Kappa statistic was used to assess intra and inter rater agreement. Each rater classified 480 hairs on each occasion. No rater classified any volunteer's 10 hairs into the same group; the most frequently occurring group was used for analysis. The inter-rater agreement was poor for the 8-groups (k = 0.418) but improved for the 6-groups (k = 0.671). The intra-rater agreement also improved (k = 0.444 to 0.648 versus 0.599 to 0.836) for 6-groups; that for the one evaluator for all volunteers was good (k = 0.754). Although small, this is the first study to test the reliability of a geometric classification. The 6-group method is more reliable. However, a digital classification system is likely to reduce operator error. A reliable objective classification of human hair curl is long overdue, particularly with the increasing use of hair as a testing substrate for treatment compliance in Medicine.

Comparing the predictive value of the pelvic ring injury classification systems by Tile and by Young and Burgess.

PubMed

Osterhoff, Georg; Scheyerer, Max J; Fritz, Yannick; Bouaicha, Samy; Wanner, Guido A; Simmen, Hans-Peter; Werner, Clément M L

2014-04-01

Radiology-based classifications of pelvic ring injuries and their relevance for the prognosis of morbidity and mortality are disputed in the literature. The purpose of this study was to evaluate potential differences between the pelvic ring injury classification systems by Tile and by Young and Burgess with regard to their predictive value on mortality, transfusion/infusion requirement and concomitant injuries. Two-hundred-and-eighty-five consecutive patients with pelvic ring fractures were analyzed for mortality within 30 days after admission, number of blood units and total volume of fluid infused during the first 24h after trauma, the Abbreviated Injury Severity (AIS) scores for head, chest, spine, abdomen and extremities as a function of the Tile and the Young-Burgess classifications. There was no significant relationship between occurrence of death and fracture pattern but a significant relationship between fracture pattern and need for blood units/total fluid volume for Tile (p<.001/p<.001) and Young-Burgess (p<.001/p<.001). In both classifications, open book fractures were associated with more fluid requirement and more severe injuries of the abdomen, spine and extremities (p<.05). When divided into the larger subgroups "partially stable" and "unstable", unstable fractures were associated with a higher mortality rate in the Young-Burgess system (p=.036). In both classifications, patients with unstable fractures required significantly more blood transfusions (p<.001) and total fluid infusion (p<.001) and higher AIS scores. In this first direct comparison of both classifications, we found no clinical relevant differences with regard to their predictive value on mortality, transfusion/infusion requirement and concomitant injuries. Copyright © 2013 Elsevier Ltd. All rights reserved.

Automatic evidence quality prediction to support evidence-based decision making.

PubMed

Sarker, Abeed; Mollá, Diego; Paris, Cécile

2015-06-01

Evidence-based medicine practice requires practitioners to obtain the best available medical evidence, and appraise the quality of the evidence when making clinical decisions. Primarily due to the plethora of electronically available data from the medical literature, the manual appraisal of the quality of evidence is a time-consuming process. We present a fully automatic approach for predicting the quality of medical evidence in order to aid practitioners at point-of-care. Our approach extracts relevant information from medical article abstracts and utilises data from a specialised corpus to apply supervised machine learning for the prediction of the quality grades. Following an in-depth analysis of the usefulness of features (e.g., publication types of articles), they are extracted from the text via rule-based approaches and from the meta-data associated with the articles, and then applied in the supervised classification model. We propose the use of a highly scalable and portable approach using a sequence of high precision classifiers, and introduce a simple evaluation metric called average error distance (AED) that simplifies the comparison of systems. We also perform elaborate human evaluations to compare the performance of our system against human judgments. We test and evaluate our approaches on a publicly available, specialised, annotated corpus containing 1132 evidence-based recommendations. Our rule-based approach performs exceptionally well at the automatic extraction of publication types of articles, with F-scores of up to 0.99 for high-quality publication types. For evidence quality classification, our approach obtains an accuracy of 63.84% and an AED of 0.271. The human evaluations show that the performance of our system, in terms of AED and accuracy, is comparable to the performance of humans on the same data. The experiments suggest that our structured text classification framework achieves evaluation results comparable to those of human performance. Our overall classification approach and evaluation technique are also highly portable and can be used for various evidence grading scales. Copyright © 2015 Elsevier B.V. All rights reserved.

Classification of Partial Discharge Measured under Different Levels of Noise Contamination.

PubMed

Jee Keen Raymond, Wong; Illias, Hazlee Azil; Abu Bakar, Ab Halim

2017-01-01

Cable joint insulation breakdown may cause a huge loss to power companies. Therefore, it is vital to diagnose the insulation quality to detect early signs of insulation failure. It is well known that there is a correlation between Partial discharge (PD) and the insulation quality. Although many works have been done on PD pattern recognition, it is usually performed in a noise free environment. Also, works on PD pattern recognition in actual cable joint are less likely to be found in literature. Therefore, in this work, classifications of actual cable joint defect types from partial discharge data contaminated by noise were performed. Five cross-linked polyethylene (XLPE) cable joints with artificially created defects were prepared based on the defects commonly encountered on site. Three different types of input feature were extracted from the PD pattern under artificially created noisy environment. These include statistical features, fractal features and principal component analysis (PCA) features. These input features were used to train the classifiers to classify each PD defect types. Classifications were performed using three different artificial intelligence classifiers, which include Artificial Neural Networks (ANN), Adaptive Neuro-Fuzzy Inference System (ANFIS) and Support Vector Machine (SVM). It was found that the classification accuracy decreases with higher noise level but PCA features used in SVM and ANN showed the strongest tolerance against noise contamination.

A CRITICAL REVIEW OF A PORTION OF THE LITERATURE ON TEACHING DEVICES.

ERIC Educational Resources Information Center

PORTER, DOUGLAS

A PORTION OF THE LITERATURE CONCERNING MECHANICAL TEACHING MACHINES OR DEVICES, WHICH ALLEGEDLY INCREASE THE EFFICIENCY AND EFFECTIVENESS OF TEACHING OPERATIONS BY MAKING USE OF CERTAIN PSYCHOLOGICAL PRINCIPLES AND TEACHER LABORSAVING FEATURES, IS REVIEWED. A CLASSIFICATION IS MADE OF MECHANICAL TEACHING AIDS AND DEVICES, SUGGESTING THAT THE…

Safety classification of herbal medicines used among pregnant women in Asian countries: a systematic review.

PubMed

Ahmed, Mansoor; Hwang, Jung Hye; Choi, Soojeung; Han, Dongwoon

2017-11-14

High prevalence of herbal medicines used in pregnancy and the lack of information on their safety is a public concern. Despite this, no significant research has been done regarding potential adverse effects of using herbal medicines during pregnancy, especially among developing Asian countries. Cross-sectional studies were searched up to year 2016 on PubMed/Medline and EMBASE, the data were extracted and quality of studies was assessed using the quality appraisal tool. The findings are reported in accordance to the PRISMA checklist (Preferred Reporting Items for Systematic Reviews and Meta-Analyses). Classification on safety of identified herbal medicines was done based on current scientific literature. This study included eight cross-sectional studies (2729 participants) from seven different Asian countries, of which 1283 (47.01%) women used one or more herbal medicines during pregnancy. Peppermint (22.8%), aniseed (14.7%), olibanum (12.9%), flixweed seed (12.2%) and ginger (11.5%) were the most frequently used herbal medicines. Out of the 33 identified herbal medicines, 13 were classified as safe to use, five as use with caution, eight were potentially harmful to use in pregnancy and information on seven herbal medicines was not available in the current literature. Several herbal medicines identified in this review were classified to be potentially harmful or the information regarding safety in pregnancy was missing. It is recommended that contraindicated herbal medicines should be avoided and other herbals should be taken under supervision of a qualified health care practitioner. The classification regarding safety of herbal medicines in pregnancy can be utilized to create awareness on prevention of adverse effects.

Magnetic Nanomaterials for Hyperthermia-based Therapy and Controlled Drug Delivery

PubMed Central

Kumar, Challa S. S. R.; Mohammad, Faruq

2011-01-01

Previous attempts to review the literature on magnetic nanomaterials for hyperthermia-based therapy focused primarily on magnetic fluid hyperthermia (MFH) using mono metallic/metal oxide nanoparticles. The term “Hyperthermia” in the literature was also confined only to include use of heat for therapeutic applications. Recently, there have been a number of publications demonstrating magnetic nanoparticle-based hyperthermia to generate local heat resulting in the release of drugs either bound to the magnetic nanoparticle or encapsulated within polymeric matrices. In this review article, we present a case for broadening the meaning of the term “hyperthermia” by including thermotherapy as well as magnetically modulated controlled drug delivery. We provide a classification for controlled drug delivery using hyperthermia: Hyperthermia-based controlled Drug delivery through Bond Breaking (DBB) and Hyperthermia-based controlled Drug delivery through Enhanced Permeability (DEP). The review also covers, for the first time, core-shell type magnetic nanomaterials, especially nanoshells prepared using layer-by-layer self-assembly, for the application of hyperthermia-based therapy and controlled drug delivery. The highlight of the review article is to portray potential opportunities in the combination of hyperthermia-based therapy and controlled drug release paradigms for successful application in personalized medicine. PMID:21447363

Conjuring a New Category of Disability from Prenatal Cocaine Exposure: Are the Infants Unique Biological or Caretaking Casualties?

ERIC Educational Resources Information Center

Schutter, Linda S.; Brinker, Richard P.

1992-01-01

A review of the literature on biological and environmental effects of cocaine use suggests that the classification of infants and young children as prenatally cocaine exposed is neither descriptive nor predictive of behavior. The classification of behavior rather than labeling of the child is encouraged, as are partnerships with families of…

Capturing the psychologic-personal perspective in spinal cord injury.

PubMed

Geyh, Szilvia; Müller, Rachel; Peter, Claudio; Bickenbach, Jerome E; Post, Marcel W M; Stucki, Gerold; Cieza, Alarcos

2011-11-01

The overall objective of this study was to illustrate a systematic approach for capturing the psychologic-personal perspective in International Classification of Functioning, Disability and Health-based comprehensive research on spinal cord injury (SCI) in terms of what and how to measure. The specific aims were to identify (1) relevant areas of research for capturing the psychologic-personal factors in a study that is planned and conceptualized according to the comprehensive context of the International Classification of Functioning, Disability and Health, using SCI as a case in point; (2) a set of domains relevant for SCI research from a psychologic-personal perspective; and (3) suitable measurement instruments that can be considered for the assessment of those identified domains based on a set of predefined guiding principles. The psychologic-personal factor structure was developed based on an item pool of 1246 entries from secondary analyses of available data from SCI studies. The domain set for psychologic-personal factors was identified through reviewing the scientific literature in PubMed and PsycInfo. The set of measurement instruments was collected using available measurement reviews, searches in the literature, instrument databases, and further sources and was selected using guiding principles. Forty specific psychologic-personal factors, subdivided into seven areas of research, were identified: (1) sociodemographic personal characteristics, (2) the position in the immediate social and physical context, (3) personal history and biography, (4) feelings, (5) thoughts and beliefs, (6) motives, and (7) patterns of experience and behavior. The psychologic-personal factors domain set contains both cross-cutting outcome domains, namely quality-of-life, life satisfaction, subjective well-being, and sociodemographic personal characteristics, life events, positive and negative affect, perceived stress, locus of control, self-efficacy, purpose in life, coping, lifestyle, and personality. For each of the identified domains, a pool of measurement instruments was listed, and the application of predefined guiding principles for measurement instrument selection was exemplified for self-efficacy. It resulted in the selection of the General Self-Efficacy Scale by Schwarzer and Jerusalem (Measures in Health Psychology: A User's Portfolio. Causal and Control Beliefs. pp. 35-37; 1995). The results of the current article contributed to creating a transparent protocol for the Swiss Spinal Cord Injury Cohort study, coordinated by the Swiss Paraplegic Research in Nottwil, Switzerland. This article also stresses the relevance of the comprehensive approach to SCI and the consideration of the psychologic-personal perspective in this approach. The study, therefore, hopes to encourage scientists to use the International Classification of Functioning, Disability and Health and the psychologic-personal perspective as a frame of reference for their research. Furthermore, the research reported in this article can inform the World Health Organization's future development of the personal factors classification in the International Classification of Functioning, Disability and Health.

[Which definition and taxonomy of incident to use for a French reporting system in primary care settings?].

PubMed

Keriel-Gascou, M; Brami, J; Chanelière, M; Haeringer-Cholet, A; Larrieu, C; Villebrun, F; Robert, T; Michel, P

2014-02-01

There is no widely accepted definition of incident for primary care doctors in France and no taxonomic classification system for epidemiological use. In preparation for a future epidemiological study on primary care incidents in France (the ESPRIT study), this work was designed to identify the definitions and taxonomic classifications used internationally along with the usual methods and results in terms of frequency in the literature. The goal was to determine a French definition and taxonomy. Systematic review of the literature and consensus methods. An exhaustive search of epidemiological surveys was performed. A structured grid was used. After having identified the definitions used in the literature, a definition was chosen using the focus groups method. Taxonomies identified in the literature were classified by relationship, architecture, code number, and number of studies published. Subsequently, a consensus among experts, who independently tested these taxonomies on six incidents, was reached for choosing the most appropriate for epidemiological data collection (little information on a large number of cases). Twenty-four papers reporting 17 studies were selected among 139 articles. Five definitions and eight taxonomies were found. The chosen definition of incident was based on the WHO definition "A patient safety incident is an event or circumstance that could have resulted, or did result, in harm to a patient, and whose wish it is not repeated again". The test of incidents resulted in the choice of the TAPS version of the International Taxonomy of Medical Error in Primary Care for a reproducible and internationally recognized codification and the tempos method for its current use in French general practice. The definitions, taxonomies, data collection characteristics and frequency of incidents results in the international literature on incidents in primary care are key components for the preparation of an epidemiological survey on incidents in primary care. Copyright © 2014. Published by Elsevier Masson SAS.

Congenital zygomatico-mandibular fusion (pseudo-syngnathia?) in conjunction with unilateral anophthalmia: review of terminology and classification.

PubMed

Tauro, David P; Kallappanavar, N K; Kiran, H Y; Girhe, Vijaykumar J

2012-09-01

Syngnathia per se is a rare congenital disorder. A literature survey reveals a total of 26 cases of syngnathia in the English literature since 1936, of which only seven cases involved fusion of the ascending ramus of the mandible to the posterior portion of the maxilla and zygomatic complex. The remaining 19 involved fusion of the alveolar ridges of the maxilla and mandible. This is a unique case of fusion of the mandible to the zygomatic complex presenting with a unilateral anophthalmic orbit in an 18-day-old neonate. The use of the term syngnathia has been reviewed and a modification in classification has been suggested.

A compendium of fossil marine animal families, 2nd edition

NASA Technical Reports Server (NTRS)

Sepkoski, J. J. Jr; Sepkoski JJ, J. r. (Principal Investigator)

1992-01-01

A comprehensive listing of 4075 taxonomic families of marine animals known from the fossil record is presented. This listing covers invertebrates, vertebrates, and animal-like protists, gives time intervals of apparent origination and extinction, and provides literature sources for these data. The time intervals are mostly 81 internationally recognized stratigraphic stages; more than half of the data are resolved to one of 145 substage divisions, providing more highly resolved data for studies of taxic macroevolution. Families are classified by order, class, and phylum, reflecting current classifications in the published literature. This compendium is a new edition of the 1982 publication, correcting errors and presenting greater stratigraphic resolution and more current ideas about acceptable families and their classification.

Algal Attributes: An Autecological Classification of Algal Taxa Collected by the National Water-Quality Assessment Program

USGS Publications Warehouse

Porter, Stephen D.

2008-01-01

Algae are excellent indicators of water-quality conditions, notably nutrient and organic enrichment, and also are indicators of major ion, dissolved oxygen, and pH concentrations and stream microhabitat conditions. The autecology, or physiological optima and tolerance, of algal species for various water-quality contaminants and conditions is relatively well understood for certain groups of freshwater algae, notably diatoms. However, applications of autecological information for water-quality assessments have been limited because of challenges associated with compiling autecological literature from disparate sources, tracking name changes for a large number of algal species, and creating an autecological data base from which algal-indicator metrics can be calculated. A comprehensive summary of algal autecological attributes for North American streams and rivers does not exist. This report describes a large, digital data file containing 28,182 records for 5,939 algal taxa, generally species or variety, collected by the U.S. Geological Survey?s National Water-Quality Assessment (NAWQA) Program. The data file includes 37 algal attributes classified by over 100 algal-indicator codes or metrics that can be calculated easily with readily available software. Algal attributes include qualitative classifications based on European and North American autecological literature, and semi-quantitative, weighted-average regression approaches for estimating optima using regional and national NAWQA data. Applications of algal metrics in water-quality assessments are discussed and national quartile distributions of metric scores are shown for selected indicator metrics.

A Distributed Fuzzy Associative Classifier for Big Data.

PubMed

Segatori, Armando; Bechini, Alessio; Ducange, Pietro; Marcelloni, Francesco

2017-09-19

Fuzzy associative classification has not been widely analyzed in the literature, although associative classifiers (ACs) have proved to be very effective in different real domain applications. The main reason is that learning fuzzy ACs is a very heavy task, especially when dealing with large datasets. To overcome this drawback, in this paper, we propose an efficient distributed fuzzy associative classification approach based on the MapReduce paradigm. The approach exploits a novel distributed discretizer based on fuzzy entropy for efficiently generating fuzzy partitions of the attributes. Then, a set of candidate fuzzy association rules is generated by employing a distributed fuzzy extension of the well-known FP-Growth algorithm. Finally, this set is pruned by using three purposely adapted types of pruning. We implemented our approach on the popular Hadoop framework. Hadoop allows distributing storage and processing of very large data sets on computer clusters built from commodity hardware. We have performed an extensive experimentation and a detailed analysis of the results using six very large datasets with up to 11,000,000 instances. We have also experimented different types of reasoning methods. Focusing on accuracy, model complexity, computation time, and scalability, we compare the results achieved by our approach with those obtained by two distributed nonfuzzy ACs recently proposed in the literature. We highlight that, although the accuracies result to be comparable, the complexity, evaluated in terms of number of rules, of the classifiers generated by the fuzzy distributed approach is lower than the one of the nonfuzzy classifiers.

The Value of Ensari’s Proposal in Evaluating the Mucosal Pathology of Childhood Celiac Disease: Old Classification versus New Version

PubMed Central

Güreşci, Servet; Hızlı, Şamil; Şimşek, Gülçin Güler

2012-01-01

Objective: Small intestinal biopsy remains the gold standard in diagnosing celiac disease (CD); however, the wide spectrum of histopathological states and differential diagnosis of CD is still a diagnostic problem for pathologists. Recently, Ensari reviewed the literature and proposed an update of the histopathological diagnosis and classification for CD. Materials and Methods: In this study, the histopathological materials of 54 children in whom CD was diagnosed at our hospital were reviewed to compare the previous Marsh and Modified Marsh-Oberhuber classifications with this new proposal. Results: In this study, we show that the Ensari classification is as accurate as the Marsh and Modified Marsh classifications in describing the consecutive states of mucosal damage seen in CD. Conclusions: Ensari’s classification is simple, practical and facilitative in diagnosing and subtyping of mucosal pathology of CD. PMID:25207015

Harnessing user generated multimedia content in the creation of collaborative classification structures and retrieval learning games

NASA Astrophysics Data System (ADS)

Borchert, Otto Jerome

This paper describes a software tool to assist groups of people in the classification and identification of real world objects called the Classification, Identification, and Retrieval-based Collaborative Learning Environment (CIRCLE). A thorough literature review identified current pedagogical theories that were synthesized into a series of five tasks: gathering, elaboration, classification, identification, and reinforcement through game play. This approach is detailed as part of an included peer reviewed paper. Motivation is increased through the use of formative and summative gamification; getting points completing important portions of the tasks and playing retrieval learning based games, respectively, which is also included as a peer-reviewed conference proceedings paper. Collaboration is integrated into the experience through specific tasks and communication mediums. Implementation focused on a REST-based client-server architecture. The client is a series of web-based interfaces to complete each of the tasks, support formal classroom interaction through faculty accounts and student tracking, and a module for peers to help each other. The server, developed using an in-house JavaMOO platform, stores relevant project data and serves data through a series of messages implemented as a JavaScript Object Notation Application Programming Interface (JSON API). Through a series of two beta tests and two experiments, it was discovered the second, elaboration, task requires considerable support. While students were able to properly suggest experiments and make observations, the subtask involving cleaning the data for use in CIRCLE required extra support. When supplied with more structured data, students were enthusiastic about the classification and identification tasks, showing marked improvement in usability scores and in open ended survey responses. CIRCLE tracks a variety of educationally relevant variables, facilitating support for instructors and researchers. Future work will revolve around material development, software refinement, and theory building. Curricula, lesson plans, instructional materials need to be created to seamlessly integrate CIRCLE in a variety of courses. Further refinement of the software will focus on improving the elaboration interface and developing further game templates to add to the motivation and retrieval learning aspects of the software. Data gathered from CIRCLE experiments can be used to develop and strengthen theories on teaching and learning.

Automated identification of sleep states from EEG signals by means of ensemble empirical mode decomposition and random under sampling boosting.

PubMed

Hassan, Ahnaf Rashik; Bhuiyan, Mohammed Imamul Hassan

2017-03-01

Automatic sleep staging is essential for alleviating the burden of the physicians of analyzing a large volume of data by visual inspection. It is also a precondition for making an automated sleep monitoring system feasible. Further, computerized sleep scoring will expedite large-scale data analysis in sleep research. Nevertheless, most of the existing works on sleep staging are either multichannel or multiple physiological signal based which are uncomfortable for the user and hinder the feasibility of an in-home sleep monitoring device. So, a successful and reliable computer-assisted sleep staging scheme is yet to emerge. In this work, we propose a single channel EEG based algorithm for computerized sleep scoring. In the proposed algorithm, we decompose EEG signal segments using Ensemble Empirical Mode Decomposition (EEMD) and extract various statistical moment based features. The effectiveness of EEMD and statistical features are investigated. Statistical analysis is performed for feature selection. A newly proposed classification technique, namely - Random under sampling boosting (RUSBoost) is introduced for sleep stage classification. This is the first implementation of EEMD in conjunction with RUSBoost to the best of the authors' knowledge. The proposed feature extraction scheme's performance is investigated for various choices of classification models. The algorithmic performance of our scheme is evaluated against contemporary works in the literature. The performance of the proposed method is comparable or better than that of the state-of-the-art ones. The proposed algorithm gives 88.07%, 83.49%, 92.66%, 94.23%, and 98.15% for 6-state to 2-state classification of sleep stages on Sleep-EDF database. Our experimental outcomes reveal that RUSBoost outperforms other classification models for the feature extraction framework presented in this work. Besides, the algorithm proposed in this work demonstrates high detection accuracy for the sleep states S1 and REM. Statistical moment based features in the EEMD domain distinguish the sleep states successfully and efficaciously. The automated sleep scoring scheme propounded herein can eradicate the onus of the clinicians, contribute to the device implementation of a sleep monitoring system, and benefit sleep research. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Health care needs in end-stage COPD: a structured literature review.

PubMed

Habraken, Jolanda M; Willems, Dick L; de Kort, Susanne J; Bindels, Patrick J E

2007-10-01

To give an overview of relevant literature regarding health care needs in end-stage COPD and to identify specific areas where knowledge about needs is still lacking. We conducted a structured literature review. We used Bradshaw's classification system. Seventy-seven publications were found. Ten publications were included in the review. The results reported cover a wide range of subjects, all regarded as health care needs. Most reported on 'felt need', i.e. needs that are mentioned by patients themselves. Results on 'normative need' (based on expert judgement) were lacking. The literature about the health care needs of patients in the end-stage of COPD is sparse, and there is no commonly accepted definition of health care needs. Looking at the increasing demand for end of life care for COPD patients, there is a clear need for further research on this subject. We especially need to focus on agreement between experts and professionals so that guidelines can be developed. To attend to the unfulfilled needs of end-stage COPD patients, the delivery of health care should be re-examined carefully.

Stress and Coping with Discrimination and Stigmatization

PubMed Central

Berjot, Sophie; Gillet, Nicolas

2011-01-01

The aim of this article is to briefly review the literature on stigmatization and more generally identity threats, to focus more specifically of the way people appraise and cope with those threatening situations. Based on the transactional model of stress and coping of Lazarus and Folkman (1984), we propose a model of coping with identity threats that takes into accounts the principle characteristic of stigma, its devaluing aspect. We present a model with specific antecedents, a refined appraisal phase and a new classification of coping strategies based on the motives that may be elicited by the threatening situation, those of protecting and/or enhancing the personal and/or social identity. PMID:21713247

Support Vector Machine-based classification of protein folds using the structural properties of amino acid residues and amino acid residue pairs.

PubMed

Shamim, Mohammad Tabrez Anwar; Anwaruddin, Mohammad; Nagarajaram, H A

2007-12-15

Fold recognition is a key step in the protein structure discovery process, especially when traditional sequence comparison methods fail to yield convincing structural homologies. Although many methods have been developed for protein fold recognition, their accuracies remain low. This can be attributed to insufficient exploitation of fold discriminatory features. We have developed a new method for protein fold recognition using structural information of amino acid residues and amino acid residue pairs. Since protein fold recognition can be treated as a protein fold classification problem, we have developed a Support Vector Machine (SVM) based classifier approach that uses secondary structural state and solvent accessibility state frequencies of amino acids and amino acid pairs as feature vectors. Among the individual properties examined secondary structural state frequencies of amino acids gave an overall accuracy of 65.2% for fold discrimination, which is better than the accuracy by any method reported so far in the literature. Combination of secondary structural state frequencies with solvent accessibility state frequencies of amino acids and amino acid pairs further improved the fold discrimination accuracy to more than 70%, which is approximately 8% higher than the best available method. In this study we have also tested, for the first time, an all-together multi-class method known as Crammer and Singer method for protein fold classification. Our studies reveal that the three multi-class classification methods, namely one versus all, one versus one and Crammer and Singer method, yield similar predictions. Dataset and stand-alone program are available upon request.

[Galaxy/quasar classification based on nearest neighbor method].

PubMed

Li, Xiang-Ru; Lu, Yu; Zhou, Jian-Ming; Wang, Yong-Jun

2011-09-01

With the wide application of high-quality CCD in celestial spectrum imagery and the implementation of many large sky survey programs (e. g., Sloan Digital Sky Survey (SDSS), Two-degree-Field Galaxy Redshift Survey (2dF), Spectroscopic Survey Telescope (SST), Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) program and Large Synoptic Survey Telescope (LSST) program, etc.), celestial observational data are coming into the world like torrential rain. Therefore, to utilize them effectively and fully, research on automated processing methods for celestial data is imperative. In the present work, we investigated how to recognizing galaxies and quasars from spectra based on nearest neighbor method. Galaxies and quasars are extragalactic objects, they are far away from earth, and their spectra are usually contaminated by various noise. Therefore, it is a typical problem to recognize these two types of spectra in automatic spectra classification. Furthermore, the utilized method, nearest neighbor, is one of the most typical, classic, mature algorithms in pattern recognition and data mining, and often is used as a benchmark in developing novel algorithm. For applicability in practice, it is shown that the recognition ratio of nearest neighbor method (NN) is comparable to the best results reported in the literature based on more complicated methods, and the superiority of NN is that this method does not need to be trained, which is useful in incremental learning and parallel computation in mass spectral data processing. In conclusion, the results in this work are helpful for studying galaxies and quasars spectra classification.

Cardiac arrhythmia beat classification using DOST and PSO tuned SVM.

PubMed

Raj, Sandeep; Ray, Kailash Chandra; Shankar, Om

2016-11-01

The increase in the number of deaths due to cardiovascular diseases (CVDs) has gained significant attention from the study of electrocardiogram (ECG) signals. These ECG signals are studied by the experienced cardiologist for accurate and proper diagnosis, but it becomes difficult and time-consuming for long-term recordings. Various signal processing techniques are studied to analyze the ECG signal, but they bear limitations due to the non-stationary behavior of ECG signals. Hence, this study aims to improve the classification accuracy rate and provide an automated diagnostic solution for the detection of cardiac arrhythmias. The proposed methodology consists of four stages, i.e. filtering, R-peak detection, feature extraction and classification stages. In this study, Wavelet based approach is used to filter the raw ECG signal, whereas Pan-Tompkins algorithm is used for detecting the R-peak inside the ECG signal. In the feature extraction stage, discrete orthogonal Stockwell transform (DOST) approach is presented for an efficient time-frequency representation (i.e. morphological descriptors) of a time domain signal and retains the absolute phase information to distinguish the various non-stationary behavior ECG signals. Moreover, these morphological descriptors are further reduced in lower dimensional space by using principal component analysis and combined with the dynamic features (i.e based on RR-interval of the ECG signals) of the input signal. This combination of two different kinds of descriptors represents each feature set of an input signal that is utilized for classification into subsequent categories by employing PSO tuned support vector machines (SVM). The proposed methodology is validated on the baseline MIT-BIH arrhythmia database and evaluated under two assessment schemes, yielding an improved overall accuracy of 99.18% for sixteen classes in the category-based and 89.10% for five classes (mapped according to AAMI standard) in the patient-based assessment scheme respectively to the state-of-art diagnosis. The results reported are further compared to the existing methodologies in literature. The proposed feature representation of cardiac signals based on symmetrical features along with PSO based optimization technique for the SVM classifier reported an improved classification accuracy in both the assessment schemes evaluated on the benchmark MIT-BIH arrhythmia database and hence can be utilized for automated computer-aided diagnosis of cardiac arrhythmia beats. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

A systematic literature review of the situation of the International Classification of Functioning, Disability, and Health and the International Classification of Functioning, Disability, and Health-Children and Youth version in education: a useful tool or a flight of fancy?

PubMed

Moretti, Marta; Alves, Ines; Maxwell, Gregor

2012-02-01

This article presents the outcome of a systematic literature review exploring the applicability of the International Classification of Functioning, Disability, and Health (ICF) and its Children and Youth version (ICF-CY) at various levels and in processes within the education systems in different countries. A systematic database search using selected search terms has been used. The selection of studies was then refined further using four protocols: inclusion and exclusion protocols at abstract and full text and extraction levels along with a quality protocol. Studies exploring the direct relationship between education and the ICF/ICF-CY were sought.As expected, the results show a strong presence of studies from English-speaking countries, namely from Europe and North America. The articles were mainly published in noneducational journals. The most used ICF/ICF-CY components are activity and participation, participation, and environmental factors. From the analysis of the papers included, the results show that the ICF/ICF-CY is currently used as a research tool, theoretical framework, and tool for implementing educational processes. The ICF/ICF-CY can provide a useful language to the education field where there is currently a lot of disparity in theoretical, praxis, and research issues. Although the systematic literature review does not report a high incidence of the use of the ICF/ICF-CY in education, the results show that the ICF/ICF-CY model and classification have potential to be applied in education systems.

One Step beyond What the Literature Says on Institutional Effectiveness of Community, Junior, and Technical Colleges.

ERIC Educational Resources Information Center

Welker, William F.; Morgan, Samuel D.

1991-01-01

Analyzes the content of the literature on community, junior, and technical colleges, utilizing a matrix with seven major classifications (i.e., governance, organization, staffing, clientele, curriculum, finance, and evaluation) and three dimensions (i.e., structure/form, function/role, and process/operations). Offers observations on effectiveness…

Comparison of Random Forest and Support Vector Machine classifiers using UAV remote sensing imagery

NASA Astrophysics Data System (ADS)

Piragnolo, Marco; Masiero, Andrea; Pirotti, Francesco

2017-04-01

Since recent years surveying with unmanned aerial vehicles (UAV) is getting a great amount of attention due to decreasing costs, higher precision and flexibility of usage. UAVs have been applied for geomorphological investigations, forestry, precision agriculture, cultural heritage assessment and for archaeological purposes. It can be used for land use and land cover classification (LULC). In literature, there are two main types of approaches for classification of remote sensing imagery: pixel-based and object-based. On one hand, pixel-based approach mostly uses training areas to define classes and respective spectral signatures. On the other hand, object-based classification considers pixels, scale, spatial information and texture information for creating homogeneous objects. Machine learning methods have been applied successfully for classification, and their use is increasing due to the availability of faster computing capabilities. The methods learn and train the model from previous computation. Two machine learning methods which have given good results in previous investigations are Random Forest (RF) and Support Vector Machine (SVM). The goal of this work is to compare RF and SVM methods for classifying LULC using images collected with a fixed wing UAV. The processing chain regarding classification uses packages in R, an open source scripting language for data analysis, which provides all necessary algorithms. The imagery was acquired and processed in November 2015 with cameras providing information over the red, blue, green and near infrared wavelength reflectivity over a testing area in the campus of Agripolis, in Italy. Images were elaborated and ortho-rectified through Agisoft Photoscan. The ortho-rectified image is the full data set, and the test set is derived from partial sub-setting of the full data set. Different tests have been carried out, using a percentage from 2 % to 20 % of the total. Ten training sets and ten validation sets are obtained from each test set. The control dataset consist of an independent visual classification done by an expert over the whole area. The classes are (i) broadleaf, (ii) building, (iii) grass, (iv) headland access path, (v) road, (vi) sowed land, (vii) vegetable. The RF and SVM are applied to the test set. The performances of the methods are evaluated using the three following accuracy metrics: Kappa index, Classification accuracy and Classification Error. All three are calculated in three different ways: with K-fold cross validation, using the validation test set and using the full test set. The analysis indicates that SVM gets better results in terms of good scores using K-fold cross or validation test set. Using the full test set, RF achieves a better result in comparison to SVM. It also seems that SVM performs better with smaller training sets, whereas RF performs better as training sets get larger.

Ethical aspects of personality disorders.

PubMed

Bendelow, Gillian

2010-11-01

To review recent literature around the controversial diagnosis of personality disorder, and to assess the ethical aspects of its status as a medical disorder. The diagnostic currency of personality disorder as a psychiatric/medical disorder has a longstanding history of ethical and social challenges through critiques of the medicalization of deviance. More recently controversies by reflexive physicians around the inclusion of the category in the forthcoming revisions of International Classification of Diseases and Diagnostic and Statistical Manual of Mental Disorders classifications reflect the problems of value-laden criteria, with the diagnostic category being severely challenged from within psychiatry as well as from without. The clinical diagnostic criteria for extremely value-laden psychiatric conditions such as personality disorder need to be analyzed through the lens of values-based medicine, as well as through clinical evidence, as the propensity for political and sociolegal appropriation of the categories can render their clinical and diagnostic value meaningless.

Coal-cleaning plant refuse characterization

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cavalet, J.R.; Torak, E.R.

1985-06-01

This report describes a study performed for the Electric Power Research Institute's Coal Cleaning Test Facility in Homer City, Pennsylvania. The purpose of the study was to design a standard methods for chemically and physically classifying refuse generated by physical coal cleaning and to construct a matrix that will accurately predict how a particular refuse will react to particular disposal methods - based solely on raw-coal characteristics and the process used to clean the coal. The value of such a classification system (which has not existed to this point) is the ability to design efficient and economical systems for disposingmore » of specific coal cleaning refuse. The report describes the project's literature search and a four-tier classification system. It also provides designs for test piles, sampling procedures, and guidelines for a series of experiments to test the classfication system and create an accurate, reliable predictive matrix. 38 refs., 39 figs., 35 tabs.« less

Complex versus simple models: ion-channel cardiac toxicity prediction.

PubMed

Mistry, Hitesh B

2018-01-01

There is growing interest in applying detailed mathematical models of the heart for ion-channel related cardiac toxicity prediction. However, a debate as to whether such complex models are required exists. Here an assessment in the predictive performance between two established large-scale biophysical cardiac models and a simple linear model B net was conducted. Three ion-channel data-sets were extracted from literature. Each compound was designated a cardiac risk category using two different classification schemes based on information within CredibleMeds. The predictive performance of each model within each data-set for each classification scheme was assessed via a leave-one-out cross validation. Overall the B net model performed equally as well as the leading cardiac models in two of the data-sets and outperformed both cardiac models on the latest. These results highlight the importance of benchmarking complex versus simple models but also encourage the development of simple models.

Improved biliary detection and diagnosis through intelligent machine analysis.

PubMed

Logeswaran, Rajasvaran

2012-09-01

This paper reports on work undertaken to improve automated detection of bile ducts in magnetic resonance cholangiopancreatography (MRCP) images, with the objective of conducting preliminary classification of the images for diagnosis. The proposed I-BDeDIMA (Improved Biliary Detection and Diagnosis through Intelligent Machine Analysis) scheme is a multi-stage framework consisting of successive phases of image normalization, denoising, structure identification, object labeling, feature selection and disease classification. A combination of multiresolution wavelet, dynamic intensity thresholding, segment-based region growing, region elimination, statistical analysis and neural networks, is used in this framework to achieve good structure detection and preliminary diagnosis. Tests conducted on over 200 clinical images with known diagnosis have shown promising results of over 90% accuracy. The scheme outperforms related work in the literature, making it a viable framework for computer-aided diagnosis of biliary diseases. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

Synopsis of Phyllosticta in China

PubMed Central

Zhang, Ke; Shivas, Roger G.; Cai, Lei

2015-01-01

The generic concept of Phyllosticta has undergone substantial changes since its establishment in 1818. The existence of conidia with a mucilaginous sheath and an apical appendage is synapomorphic for Phyllosticta species, which has been shown in recent molecular phylogenetic studies. Thus a natural classification of Phyllosticta species should emphasize above morphological characters. Many names in Phyllosticta, both published in the scientific literatures and in publically accessible databases, need updating. In China, more than 200 species names in Phyllosticta have been recorded, of which, 158 species names are reviewed here based on their morphological descriptions and molecular data. Only 20 species of Phyllosticta are accepted from China. Other records of Phyllosticta refer to Phoma (89 records), Asteromella (14 records), Boeremia (9 records), Phomopsis (7 records) and Microsphaeropsis (1 record), with 19 names of uncertain generic classification. This work demonstrates an urgent need for the re-assessment of records of Phyllosticta worldwide. PMID:26000199

A delphi exercise to identify characteristic features of gout - opinions from patients and physicians, the first stage in developing new classification criteria.

PubMed

Prowse, Rebecca L; Dalbeth, Nicola; Kavanaugh, Arthur; Adebajo, Adewale O; Gaffo, Angelo L; Terkeltaub, Robert; Mandell, Brian F; Suryana, Bagus P P; Goldenstein-Schainberg, Claudia; Diaz-Torne, Cèsar; Khanna, Dinesh; Lioté, Frederic; Mccarthy, Geraldine; Kerr, Gail S; Yamanaka, Hisashi; Janssens, Hein; Baraf, Herbert F; Chen, Jiunn-Horng; Vazquez-Mellado, Janitzia; Harrold, Leslie R; Stamp, Lisa K; Van De Laar, Mart A; Janssen, Matthijs; Doherty, Michael; Boers, Maarten; Edwards, N Lawrence; Gow, Peter; Chapman, Peter; Khanna, Puja; Helliwell, Philip S; Grainger, Rebecca; Schumacher, H Ralph; Neogi, Tuhina; Jansen, Tim L; Louthrenoo, Worawit; Sivera, Francisca; Taylor, William J; Alten, Rieke

2013-04-01

To identify a comprehensive list of features that might discriminate between gout and other rheumatic musculoskeletal conditions, to be used subsequently for a case-control study to develop and test new classification criteria for gout. Two Delphi exercises were conducted using Web-based questionnaires: one with physicians from several countries who had an interest in gout and one with patients from New Zealand who had gout. Physicians rated a list of potentially discriminating features that were identified by literature review and expert opinion, and patients rated a list of features that they generated themselves. Agreement was defined by the RAND/UCLA disagreement index. Forty-four experienced physicians and 9 patients responded to all iterations. For physicians, 71 items were identified by literature review and 15 more were suggested by physicians. The physician survey showed agreement for 26 discriminatory features and 15 as not discriminatory. The patients identified 46 features of gout, for which there was agreement on 25 items as being discriminatory and 7 items as not discriminatory. Patients and physicians agreed upon several key features of gout. Physicians emphasized objective findings, imaging, and patterns of symptoms, whereas patients emphasized severity, functional results, and idiographic perception of symptoms.

Primary tonsillar lymphomas according to the new World Health Organization classification: to report 87 cases and literature review and analysis.

PubMed

Mohammadianpanah, Mohammad; Daneshbod, Yahya; Ramzi, Mani; Hamidizadeh, Nasrin; Dehghani, Seyed Javad; Bidouei, Farzad; Khademi, Bijan; Ahmadloo, Niloofar; Ansari, Mansour; Omidvari, Shapour; Mosalaei, Ahmad; Dehghani, Mehdi

2010-10-01

The present study aimed to define the natural history, World Health Organization (WHO) classification, prognostic factors, and treatment outcome of 87 patients with primary lymphoma of the palatine tonsil and literature review and analysis. Between 1990 and March 2008, 87 consecutive patients diagnosed with primary lymphoid malignancy of the palatine tonsil. All pathologic specimens were reviewed and reclassified according to the recent WHO classification. To investigate the association of tonsillar lymphomas with Epstein-Barr virus (EBV), in situ hybridization was performed for 24 tonsillar lymphomas (23 diffuse large B-cell lymphoma (DLBC) and one classic Hodgkin's disease) and ten normal tonsils as control group. In literature review, we found 26 major related series including 1,602 patients with primary tonsillar lymphoma. The median age of our patients was 52 years (range 11-86 years). There were 39 women and 48 men with a median follow-up of 67 months for living patients. The vast majority (95%) of patients had B-cell phenotype. DLBC was the most frequent histology. In situ hybridization revealed none of 23 DLBC to be positive for EBV. The 5-year disease-free and overall survival rates were 78.9% and 86%, respectively. In the literature review and by analyzing the data collection from 26 major reported series, the median age was 55 years and male/female ratio was 1.3:1. Intermediate grade tumors consisted of 72% of all tonsillar lymphomas and B-cell lymphomas constituted 82% of all cell immunophenotypes. The 5-year disease-free and overall survival rates were 61% and 67%, respectively. The vast majority of tonsillar lymphomas are of B-cell origin and with intermediate to high-grade histology. These neoplasms tend to present in early stage disease and to have favorable outcome. WHO classification predicts more accurately treatment outcome of patients with tonsillar lymphoma. The association of DLBC in the palatine tonsil with EBV infection is infrequent.

The lipoma of tongue - A rare site for a tumor: Case report and review of the literature

PubMed Central

Baonerkar, Hemant A.; Vora, Meena; Sorathia, Rakesh; Shinde, Swapnil

2015-01-01

Lipoma is the most common tumor of the human body, but their presences in the oral cavity are very rare. Reported cases of lipoma of tongue in English literature are very few. Here, we report a case of lipoma of tongue in 63-year-old male patient, with its clinical presentation, the histological picture, classification, and brief review of the literature. PMID:26752882

Purely in silico BCS classification: science based quality standards for the world's drugs.

PubMed

Dahan, Arik; Wolk, Omri; Kim, Young Hoon; Ramachandran, Chandrasekharan; Crippen, Gordon M; Takagi, Toshihide; Bermejo, Marival; Amidon, Gordon L

2013-11-04

BCS classification is a vital tool in the development of both generic and innovative drug products. The purpose of this work was to provisionally classify the world's top selling oral drugs according to the BCS, using in silico methods. Three different in silico methods were examined: the well-established group contribution (CLogP) and atom contribution (ALogP) methods, and a new method based solely on the molecular formula and element contribution (KLogP). Metoprolol was used as the benchmark for the low/high permeability class boundary. Solubility was estimated in silico using a thermodynamic equation that relies on the partition coefficient and melting point. The validity of each method was affirmed by comparison to reference data and literature. We then used each method to provisionally classify the orally administered, IR drug products found in the WHO Model list of Essential Medicines, and the top-selling oral drug products in the United States (US), Great Britain (GB), Spain (ES), Israel (IL), Japan (JP), and South Korea (KR). A combined list of 363 drugs was compiled from the various lists, and 257 drugs were classified using the different in silico permeability methods and literature solubility data, as well as BDDCS classification. Lastly, we calculated the solubility values for 185 drugs from the combined set using in silico approach. Permeability classification with the different in silico methods was correct for 69-72.4% of the 29 reference drugs with known human jejunal permeability, and for 84.6-92.9% of the 14 FDA reference drugs in the set. The correlations (r(2)) between experimental log P values of 154 drugs and their CLogP, ALogP and KLogP were 0.97, 0.82 and 0.71, respectively. The different in silico permeability methods produced comparable results: 30-34% of the US, GB, ES and IL top selling drugs were class 1, 27-36.4% were class 2, 22-25.5% were class 3, and 5.46-14% were class 4 drugs, while ∼8% could not be classified. The WHO list included significantly less class 1 and more class 3 drugs in comparison to the countries' lists, probably due to differences in commonly used drugs in developing vs industrial countries. BDDCS classified more drugs as class 1 compared to in silico BCS, likely due to the more lax benchmark for metabolism (70%), in comparison to the strict permeability benchmark (metoprolol). For 185 out of the 363 drugs, in silico solubility values were calculated, and successfully matched the literature solubility data. In conclusion, relatively simple in silico methods can be used to estimate both permeability and solubility. While CLogP produced the best correlation to experimental values, even KLogP, the most simplified in silico method that is based on molecular formula with no knowledge of molecular structure, produced comparable BCS classification to the sophisticated methods. This KLogP, when combined with a mean melting point and estimated dose, can be used to provisionally classify potential drugs from just molecular formula, even before synthesis. 49-59% of the world's top-selling drugs are highly soluble (class 1 and class 3), and are therefore candidates for waivers of in vivo bioequivalence studies. For these drugs, the replacement of expensive human studies with affordable in vitro dissolution tests would ensure their bioequivalence, and encourage the development and availability of generic drug products in both industrial and developing countries.

Maximizing the Predictive Value of Production Rules

DTIC Science & Technology

1988-08-31

Clancev, 1985] Clancey, W. "Heuristic Classification." Artifcial Intelligence . 27 (1985) 289-350. [Crawford, 19881 Crawford, S. "Extensions to the CART...Optimality 16 6.1.2. Comparative Analysis for Normally Distributed Data 17 6.2. Comparison with Alternative Machine Learning Methods 18 6.2.1. Alternative...are reported on data sets previously analyzed in the Al literature using alternative classification techniques. 1. Introduction MIanv decision-making

"Kalila and Dimna" as One of the Traditional Antecedents of Modern Classifications of Values

ERIC Educational Resources Information Center

Aktas, Elif; Beldag, Adem

2017-01-01

"Kalila and Dimna," which is considered as one of the classic works of the Eastern literature, is a political morality and advice book that is still in effect thanks to the knowledge of wisdom it offers. The aim of this study is to examine this work according to the Western classifications of values (UNESCO, Rokeach, Schwartz, Spranger)…

A Systematic Classification for HVAC Systems and Components

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li, Han; Chen, Yan; Zhang, Jian

Depending on the application, the complexity of an HVAC system can range from a small fan coil unit to a large centralized air conditioning system with primary and secondary distribution loops, and central plant components. Currently, the taxonomy of HVAC systems and the components has various aspects, which can get quite complex because of the various components and system configurations. For example, based on cooling and heating medium delivered to terminal units, systems can be classified as either air systems, water systems or air-water systems. In addition, some of the system names might be commonly used in a confusing manner,more » such as “unitary system” vs. “packaged system.” Without a systematic classification, these components and system terminology can be confusing to understand or differentiate from each other, and it creates ambiguity in communication, interpretation, and documentation. It is valuable to organize and classify HVAC systems and components so that they can be easily understood and used in a consistent manner. This paper aims to develop a systematic classification of HVAC systems and components. First, we summarize the HVAC component information and definitions based on published literature, such as ASHRAE handbooks, regulations, and rating standards. Then, we identify common HVAC system types and map them to the collected components in a meaningful way. Classification charts are generated and described based on the component information. Six main categories are identified for the HVAC components and equipment, i.e., heating and cooling production, heat extraction and rejection, air handling process, distribution system, terminal use, and stand-alone system. Components for each main category are further analyzed and classified in detail. More than fifty system names are identified and grouped based on their characteristics. The result from this paper will be helpful for education, communication, and systems and component documentation.« less

Compensatory neurofuzzy model for discrete data classification in biomedical

NASA Astrophysics Data System (ADS)

Ceylan, Rahime

2015-03-01

Biomedical data is separated to two main sections: signals and discrete data. So, studies in this area are about biomedical signal classification or biomedical discrete data classification. There are artificial intelligence models which are relevant to classification of ECG, EMG or EEG signals. In same way, in literature, many models exist for classification of discrete data taken as value of samples which can be results of blood analysis or biopsy in medical process. Each algorithm could not achieve high accuracy rate on classification of signal and discrete data. In this study, compensatory neurofuzzy network model is presented for classification of discrete data in biomedical pattern recognition area. The compensatory neurofuzzy network has a hybrid and binary classifier. In this system, the parameters of fuzzy systems are updated by backpropagation algorithm. The realized classifier model is conducted to two benchmark datasets (Wisconsin Breast Cancer dataset and Pima Indian Diabetes dataset). Experimental studies show that compensatory neurofuzzy network model achieved 96.11% accuracy rate in classification of breast cancer dataset and 69.08% accuracy rate was obtained in experiments made on diabetes dataset with only 10 iterations.

Texture operator for snow particle classification into snowflake and graupel

NASA Astrophysics Data System (ADS)

Nurzyńska, Karolina; Kubo, Mamoru; Muramoto, Ken-ichiro

2012-11-01

In order to improve the estimation of precipitation, the coefficients of Z-R relation should be determined for each snow type. Therefore, it is necessary to identify the type of falling snow. Consequently, this research addresses a problem of snow particle classification into snowflake and graupel in an automatic manner (as these types are the most common in the study region). Having correctly classified precipitation events, it is believed that it will be possible to estimate the related parameters accurately. The automatic classification system presented here describes the images with texture operators. Some of them are well-known from the literature: first order features, co-occurrence matrix, grey-tone difference matrix, run length matrix, and local binary pattern, but also a novel approach to design simple local statistic operators is introduced. In this work the following texture operators are defined: mean histogram, min-max histogram, and mean-variance histogram. Moreover, building a feature vector, which is based on the structure created in many from mentioned algorithms is also suggested. For classification, the k-nearest neighbourhood classifier was applied. The results showed that it is possible to achieve correct classification accuracy above 80% by most of the techniques. The best result of 86.06%, was achieved for operator built from a structure achieved in the middle stage of the co-occurrence matrix calculation. Next, it was noticed that describing an image with two texture operators does not improve the classification results considerably. In the best case the correct classification efficiency was 87.89% for a pair of texture operators created from local binary pattern and structure build in a middle stage of grey-tone difference matrix calculation. This also suggests that the information gathered by each texture operator is redundant. Therefore, the principal component analysis was applied in order to remove the unnecessary information and additionally reduce the length of the feature vectors. The improvement of the correct classification efficiency for up to 100% is possible for methods: min-max histogram, texture operator built from structure achieved in a middle stage of co-occurrence matrix calculation, texture operator built from a structure achieved in a middle stage of grey-tone difference matrix creation, and texture operator based on a histogram, when the feature vector stores 99% of initial information.

Proposed Diagnostic Criteria, Classification Schema, and Review of Literature of Notochord-Derived Ecchordosis Physaliphora

PubMed Central

Lagman, Carlito; Sarmiento, J. Manuel; Turtz, Alan R; Chitale, Rohan V

2016-01-01

Ecchordosis physaliphora (EP) is a benign notochordal remnant derived from ectopic nests found along the craniospinal axis. It typically presents asymptomatically and is diagnosed using classic radiologic features, particularly location, T1-hypointensity, T2-hyperintensity, and lack of enhancement following gadolinium (Gd) contrast administration. Distinguishing EP from its malignant counterpart, chordoma, is of paramount importance, given the aggressive nature of the latter. Advances in imaging and immunohistochemistry have aided in diagnosis to an extent but, to our knowledge, identification of the genetic fingerprint of EP has yet to take place. Further cytological analysis of these lesions in search of a genetic link is warranted. We propose here a set of diagnostic criteria based on features consistently cited in the literature. In this literature review, 23 case reports were identified and collated into a summary of symptomatic cases of ecchordosis physaliphora. An illustrative case report of two patients was also included.  PMID:27158576

Clinical decision rules, spinal pain classification and prediction of treatment outcome: A discussion of recent reports in the rehabilitation literature

PubMed Central

2012-01-01

Clinical decision rules are an increasingly common presence in the biomedical literature and represent one strategy of enhancing clinical-decision making with the goal of improving the efficiency and effectiveness of healthcare delivery. In the context of rehabilitation research, clinical decision rules have been predominantly aimed at classifying patients by predicting their treatment response to specific therapies. Traditionally, recommendations for developing clinical decision rules propose a multistep process (derivation, validation, impact analysis) using defined methodology. Research efforts aimed at developing a “diagnosis-based clinical decision rule” have departed from this convention. Recent publications in this line of research have used the modified terminology “diagnosis-based clinical decision guide.” Modifications to terminology and methodology surrounding clinical decision rules can make it more difficult for clinicians to recognize the level of evidence associated with a decision rule and understand how this evidence should be implemented to inform patient care. We provide a brief overview of clinical decision rule development in the context of the rehabilitation literature and two specific papers recently published in Chiropractic and Manual Therapies. PMID:22726639

Moment-based approaches in imaging part 2: invariance

PubMed Central

Shu, Huazhong; Luo, Limin; Coatrieux, Jean-Louis

2005-01-01

The several moment families have been reviewed in a first paper [1]. A classification was proposed in order to get a better understanding of their relations. More attention was given to orthogonal moments (in particular Legendre, Zernike, Tchebichef, Krawtchouk, Racah, dual Hahn). Important properties for computer vision applications were just sketched, among which invariance and robustness to noise. These properties may drive the choice of moments when addressing a specific problem. A short, thus non-exhaustive, review of the literature on these issues is proposed in this second paper. PMID:18270055

Knee Pain and Mobility Impairments: Meniscal and Articular Cartilage Lesions Revision 2018.

PubMed

Logerstedt, David S; Scalzitti, David A; Bennell, Kim L; Hinman, Rana S; Silvers-Granelli, Holly; Ebert, Jay; Hambly, Karen; Carey, James L; Snyder-Mackler, Lynn; Axe, Michael J; McDonough, Christine M

2018-02-01

The Orthopaedic Section of the American Physical Therapy Association (APTA) has an ongoing effort to create evidence-based practice guidelines for orthopaedic physical therapy management of patients with musculoskeletal impairments described in the World Health Organization's International Classification of Functioning, Disability, and Health (ICF). The purpose of these revised clinical practice guidelines is to review recent peer-reviewed literature and make recommendations related to meniscus and articular cartilage lesions. J Orthop Sports Phys Ther. 2018;48(2):A1-A50. doi:10.2519/jospt.2018.0301.

Achilles Pain, Stiffness, and Muscle Power Deficits: Midportion Achilles Tendinopathy Revision 2018.

PubMed

Martin, Robroy L; Chimenti, Ruth; Cuddeford, Tyler; Houck, Jeff; Matheson, J W; McDonough, Christine M; Paulseth, Stephen; Wukich, Dane K; Carcia, Christopher R

2018-05-01

The Orthopaedic Section of the American Physical Therapy Association (APTA) has an ongoing effort to create evidence-based practice guidelines for orthopaedic physical therapy management of patients with musculoskeletal impairments described in the World Health Organization's International Classification of Functioning, Disability, and Health (ICF). The purpose of these revised clinical practice guidelines is to review recent peer-reviewed literature and make recommendations related to midportion Achilles tendinopathy. J Orthop Sports Phys Ther 2018;48(5):A1-A38. doi:10.2519/jospt.2018.0302.

Systematization of actinides using cluster analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kopyrin, A.A.; Terent`eva, T.N.; Khramov, N.N.

1994-11-01

A representation of the actinides in multidimensional property space is proposed for systematization of these elements using cluster analysis. Literature data for their atomic properties are used. Owing to the wide variation of published ionization potentials, medians are used to estimate them. Vertical dendograms are used for classification on the basis of distances between the actinides in atomic-property space. The properties of actinium and lawrencium are furthest removed from the main group. Thorium and mendelevium exhibit individualized properties. A cluster based on the einsteinium-fermium pair is joined by californium.

Management of proximal interphalangeal joint injuries

PubMed Central

Freiberg, Arnis

2007-01-01

Injuries to the proximal interphalangeal joint are common but frequently missed. They are often overtreated by prolonged immobilization, resulting in stiffness, which may be permanent. The purpose of the present article is to briefly review the relevant anatomy and biomechanics, present an approach to physical examination and diagnosis, and propose a practical clinical classification. The treatment of the most severe injury – the intra-articular fracture dislocation – is controversial. The various treatment options are discussed, based on personal experience and a review of the literature. A list of relevant references is presented. PMID:19554177

A conceptual framework and classification of capability areas for business process maturity

NASA Astrophysics Data System (ADS)

Van Looy, Amy; De Backer, Manu; Poels, Geert

2014-03-01

The article elaborates on business process maturity, which indicates how well an organisation can perform based on its business processes, i.e. on its way of working. This topic is of paramount importance for managers who try to excel in today's competitive world. Hence, business process maturity is an emerging research field. However, no consensus exists on the capability areas (or skills) needed to excel. Moreover, their theoretical foundation and synergies with other fields are frequently neglected. To overcome this gap, our study presents a conceptual framework with six main capability areas and 17 sub areas. It draws on theories regarding the traditional business process lifecycle, which are supplemented by recognised organisation management theories. The comprehensiveness of this framework is validated by mapping 69 business process maturity models (BPMMs) to the identified capability areas, based on content analysis. Nonetheless, as a consensus neither exists among the collected BPMMs, a classification of different maturity types is proposed, based on cluster analysis and discriminant analysis. Consequently, the findings contribute to the grounding of business process literature. Possible future avenues are evaluating existing BPMMs, directing new BPMMs or investigating which combinations of capability areas (i.e. maturity types) contribute more to performance than others.

Intellectual developmental disorders: towards a new name, definition and framework for “mental retardation/intellectual disability” in ICD-11

PubMed Central

CARULLA, LUIS SALVADOR; REED, GEOFFREY M.; VAEZ-AZIZI, LEILA M.; COOPER, SALLY-ANN; LEAL, RAFAEL MARTINEZ; BERTELLI, MARCO; ADNAMS, COLLEEN; COORAY, SHERVA; DEB, SHOUMITRO; DIRANI, LEYLA AKOURY; GIRIMAJI, SATISH CHANDRA; KATZ, GREGORIO; KWOK, HENRY; LUCKASSON, RUTH; SIMEONSSON, RUNE; WALSH, CAROLYN; MUNIR, KEMIR; SAXENA, SHEKHAR

2011-01-01

Although “intellectual disability” has widely replaced the term “mental retardation”, the debate as to whether this entity should be conceptualized as a health condition or as a disability has intensified as the revision of the World Health Organization (WHO)’s International Classification of Diseases (ICD) advances. Defining intellectual disability as a health condition is central to retaining it in ICD, with significant implications for health policy and access to health services. This paper presents the consensus reached to date by the WHO ICD Working Group on the Classification of Intellectual Disabilities. Literature reviews were conducted and a mixed qualitative approach was followed in a series of meetings to produce consensus-based recommendations combining prior expert knowledge and available evidence. The Working Group proposes replacing mental retardation with intellectual developmental disorders, defined as “a group of developmental conditions characterized by significant impairment of cognitive functions, which are associated with limitations of learning, adaptive behaviour and skills”. The Working Group further advises that intellectual developmental disorders be incorporated in the larger grouping (parent category) of neurodevelopmental disorders, that current subcategories based on clinical severity (i.e., mild, moderate, severe, profound) be continued, and that problem behaviours be removed from the core classification structure of intellectual developmental disorders and instead described as associated features. PMID:21991267

Invited commentary: the incremental value of customization in defining abnormal fetal growth status.

PubMed

Zhang, Jun; Sun, Kun

2013-10-15

Reference tools based on birth weight percentiles at a given gestational week have long been used to define fetuses or infants that are small or large for their gestational ages. However, important deficiencies of the birth weight reference are being increasingly recognized. Overwhelming evidence indicates that an ultrasonography-based fetal weight reference should be used to classify fetal and newborn sizes during pregnancy and at birth, respectively. Questions have been raised as to whether further adjustments for race/ethnicity, parity, sex, and maternal height and weight are helpful to improve the accuracy of the classification. In this issue of the Journal, Carberry et al. (Am J Epidemiol. 2013;178(8):1301-1308) show that adjustment for race/ethnicity is useful, but that additional fine tuning for other factors (i.e., full customization) in the classification may not further improve the ability to predict infant morbidity, mortality, and other fetal growth indicators. Thus, the theoretical advantage of full customization may have limited incremental value for pediatric outcomes, particularly in term births. Literature on the prediction of short-term maternal outcomes and very long-term outcomes (adult diseases) is too scarce to draw any conclusions. Given that each additional variable being incorporated in the classification scheme increases complexity and costs in practice, the clinical utility of full customization in obstetric practice requires further testing.

RBOOST: RIEMANNIAN DISTANCE BASED REGULARIZED BOOSTING

PubMed Central

Liu, Meizhu; Vemuri, Baba C.

2011-01-01

Boosting is a versatile machine learning technique that has numerous applications including but not limited to image processing, computer vision, data mining etc. It is based on the premise that the classification performance of a set of weak learners can be boosted by some weighted combination of them. There have been a number of boosting methods proposed in the literature, such as the AdaBoost, LPBoost, SoftBoost and their variations. However, the learning update strategies used in these methods usually lead to overfitting and instabilities in the classification accuracy. Improved boosting methods via regularization can overcome such difficulties. In this paper, we propose a Riemannian distance regularized LPBoost, dubbed RBoost. RBoost uses Riemannian distance between two square-root densities (in closed form) – used to represent the distribution over the training data and the classification error respectively – to regularize the error distribution in an iterative update formula. Since this distance is in closed form, RBoost requires much less computational cost compared to other regularized Boosting algorithms. We present several experimental results depicting the performance of our algorithm in comparison to recently published methods, LP-Boost and CAVIAR, on a variety of datasets including the publicly available OASIS database, a home grown Epilepsy database and the well known UCI repository. Results depict that the RBoost algorithm performs better than the competing methods in terms of accuracy and efficiency. PMID:21927643

Designing boosting ensemble of relational fuzzy systems.

PubMed

Scherer, Rafał

2010-10-01

A method frequently used in classification systems for improving classification accuracy is to combine outputs of several classifiers. Among various types of classifiers, fuzzy ones are tempting because of using intelligible fuzzy if-then rules. In the paper we build an AdaBoost ensemble of relational neuro-fuzzy classifiers. Relational fuzzy systems bond input and output fuzzy linguistic values by a binary relation; thus, fuzzy rules have additional, comparing to traditional fuzzy systems, weights - elements of a fuzzy relation matrix. Thanks to this the system is better adjustable to data during learning. In the paper an ensemble of relational fuzzy systems is proposed. The problem is that such an ensemble contains separate rule bases which cannot be directly merged. As systems are separate, we cannot treat fuzzy rules coming from different systems as rules from the same (single) system. In the paper, the problem is addressed by a novel design of fuzzy systems constituting the ensemble, resulting in normalization of individual rule bases during learning. The method described in the paper is tested on several known benchmarks and compared with other machine learning solutions from the literature.

Novel nursing terminologies for the rapid response system.

PubMed

Wong, Elizabeth

2009-01-01

Nursing terminology with implications for the rapid response system (RRS) is introduced and proposed: critical incident nursing diagnosis (CIND), defined as the recognition of an acute life-threatening event that occurs as a result of disease, surgery, treatment, or medication; critical incident nursing intervention, defined as any indirect or direct care registered nurse-initiated treatment, based upon clinical judgment and knowledge that a registered nurse performs in response to a CIND; and critical incident control, defined as a response that attempts to reverse a life-threatening condition. The current literature, research studies, meta-analyses from a variety of disciplines, and personal clinical experience serve as the data sources for this article. The current nursing diagnoses, nursing interventions, and nursing outcomes listed in the North American Nursing Diagnosis Association International Classification, Nursing Interventions Classification (NIC), and Nursing Outcomes Classification (NOC), respectively, are inaccurate or inadequate for describing nursing care during life-threatening situations. The lack of such standardized nursing terminology creates a barrier that may impede critical communication and patient care during life-threatening situations when activating the RRS. The North American Nursing Diagnosis Association International Classification, NIC, and NOC are urged to refine their classifications and include CIND, critical incident nursing intervention, and critical incident control. The RRS should incorporate standardized nursing terminology to describe patient care during life-threatening situations. Refining the diagnoses, interventions, and outcomes classifications will permit nursing researchers, among others, to conduct studies on the efficacy of the proposed novel nursing terminology when providing care to patients during life-threatening situations. In addition, including the proposed novel nursing terminology in the RRS offers a means of improving care in such situations.

The Ex Vivo Eye Irritation Test as an alternative test method for serious eye damage/eye irritation.

PubMed

Spöler, Felix; Kray, Oya; Kray, Stefan; Panfil, Claudia; Schrage, Norbert F

2015-07-01

Ocular irritation testing is a common requirement for the classification, labelling and packaging of chemicals (substances and mixtures). The in vivo Draize rabbit eye test (OECD Test Guideline 405) is considered to be the regulatory reference method for the classification of chemicals according to their potential to induce eye injury. In the Draize test, chemicals are applied to rabbit eyes in vivo, and changes are monitored over time. If no damage is observed, the chemical is not categorised. Otherwise, the classification depends on the severity and reversibility of the damage. Alternative test methods have to be designed to match the classifications from the in vivo reference method. However, observation of damage reversibility is usually not possible in vitro. Within the present study, a new organotypic method based on rabbit corneas obtained from food production is demonstrated to close this gap. The Ex Vivo Eye Irritation Test (EVEIT) retains the full biochemical activity of the corneal epithelium, epithelial stem cells and endothelium. This permits the in-depth analysis of ocular chemical trauma beyond that achievable by using established in vitro methods. In particular, the EVEIT is the first test to permit the direct monitoring of recovery of all corneal layers after damage. To develop a prediction model for the EVEIT that is comparable to the GHS system, 37 reference chemicals were analysed. The experimental data were used to derive a three-level potency ranking of eye irritation and corrosion that best fits the GHS categorisation. In vivo data available in the literature were used for comparison. When compared with GHS classification predictions, the overall accuracy of the three-level potency ranking was 78%. The classification of chemicals as irritating versus non-irritating resulted in 96% sensitivity, 91% specificity and 95% accuracy. 2015 FRAME.

First branchial cleft fistula presenting with internal opening on the Eustachian tube: Illustrated cases and literature review.

PubMed

Liu, Yuhe; Li, Tiancheng; Xue, Junfang; Jia, Jun; Xiao, Shuifang; Zhao, Enmin

2012-05-01

Two cases of first branchial cleft fistula with internal opening on the Eustachian tube are reported and the diagnosis, management and embryological hypothesis are discussed. Retrospective study and review of the literature. Both patients were young boys with first branchial cleft anomaly clearly identified by computed tomography fistulography scan and direct Methylene Blue dye injection. In both cases, surgical removal revealed a fistula with internal opening located on the Eustachian tube near the nasopharynx. The main embryological theories and classification are reviewed. A connection between the theories of first branchial apparatus development and the classification by Work might explain the reported clinical association. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Vaginismus: a review of the literature on the classification/diagnosis, etiology and treatment.

PubMed

Lahaie, Marie-André; Boyer, Stéphanie C; Amsel, Rhonda; Khalifé, Samir; Binik, Yitzchak M

2010-09-01

Vaginismus is currently defined as an involuntary vaginal muscle spasm interfering with sexual intercourse that is relatively easy to diagnose and treat. As a result, there has been a lack of research interest with very few well-controlled diagnostic, etiological or treatment outcome studies. Interestingly, the few empirical studies that have been conducted on vaginismus do not support the view that it is easily diagnosed or treated and have shed little light on potential etiology. A review of the literature on the classification/diagnosis, etiology and treatment of vaginismus will be presented with a focus on the latest empirical findings. This article suggests that vaginismus cannot be easily differentiated from dyspareunia and should be treated from a multidisciplinary point of view.

Case study: child with global developmental delay.

PubMed

Okumakpeyi, Pearline; Lunney, Margaret

2010-01-01

This case study focused on the care of a child with global developmental delay. Data were obtained through the author's clinical practice in long-term care pediatric rehabilitation and literature sources. NANDA-International Classifications, the Nursing Interventions Classification (NIC), and Nursing Outcomes Classification (NOC) were used to identify the appropriate nursing diagnosis, nursing interventions, and patient outcomes. This case study provides the pertinent nursing diagnoses, interventions, and outcomes for a child with global developmental delay. The interdisciplinary team approach and family involvement is addressed. Use of NANDA, NIC, and NOC outcomes constructs for enhancing the care of a child with global developmental delay.

Virtual Sensor of Surface Electromyography in a New Extensive Fault-Tolerant Classification System.

PubMed

de Moura, Karina de O A; Balbinot, Alexandre

2018-05-01

A few prosthetic control systems in the scientific literature obtain pattern recognition algorithms adapted to changes that occur in the myoelectric signal over time and, frequently, such systems are not natural and intuitive. These are some of the several challenges for myoelectric prostheses for everyday use. The concept of the virtual sensor, which has as its fundamental objective to estimate unavailable measures based on other available measures, is being used in other fields of research. The virtual sensor technique applied to surface electromyography can help to minimize these problems, typically related to the degradation of the myoelectric signal that usually leads to a decrease in the classification accuracy of the movements characterized by computational intelligent systems. This paper presents a virtual sensor in a new extensive fault-tolerant classification system to maintain the classification accuracy after the occurrence of the following contaminants: ECG interference, electrode displacement, movement artifacts, power line interference, and saturation. The Time-Varying Autoregressive Moving Average (TVARMA) and Time-Varying Kalman filter (TVK) models are compared to define the most robust model for the virtual sensor. Results of movement classification were presented comparing the usual classification techniques with the method of the degraded signal replacement and classifier retraining. The experimental results were evaluated for these five noise types in 16 surface electromyography (sEMG) channel degradation case studies. The proposed system without using classifier retraining techniques recovered of mean classification accuracy was of 4% to 38% for electrode displacement, movement artifacts, and saturation noise. The best mean classification considering all signal contaminants and channel combinations evaluated was the classification using the retraining method, replacing the degraded channel by the virtual sensor TVARMA model. This method recovered the classification accuracy after the degradations, reaching an average of 5.7% below the classification of the clean signal, that is the signal without the contaminants or the original signal. Moreover, the proposed intelligent technique minimizes the impact of the motion classification caused by signal contamination related to degrading events over time. There are improvements in the virtual sensor model and in the algorithm optimization that need further development to provide an increase the clinical application of myoelectric prostheses but already presents robust results to enable research with virtual sensors on biological signs with stochastic behavior.

Virtual Sensor of Surface Electromyography in a New Extensive Fault-Tolerant Classification System

PubMed Central

Balbinot, Alexandre

2018-01-01

A few prosthetic control systems in the scientific literature obtain pattern recognition algorithms adapted to changes that occur in the myoelectric signal over time and, frequently, such systems are not natural and intuitive. These are some of the several challenges for myoelectric prostheses for everyday use. The concept of the virtual sensor, which has as its fundamental objective to estimate unavailable measures based on other available measures, is being used in other fields of research. The virtual sensor technique applied to surface electromyography can help to minimize these problems, typically related to the degradation of the myoelectric signal that usually leads to a decrease in the classification accuracy of the movements characterized by computational intelligent systems. This paper presents a virtual sensor in a new extensive fault-tolerant classification system to maintain the classification accuracy after the occurrence of the following contaminants: ECG interference, electrode displacement, movement artifacts, power line interference, and saturation. The Time-Varying Autoregressive Moving Average (TVARMA) and Time-Varying Kalman filter (TVK) models are compared to define the most robust model for the virtual sensor. Results of movement classification were presented comparing the usual classification techniques with the method of the degraded signal replacement and classifier retraining. The experimental results were evaluated for these five noise types in 16 surface electromyography (sEMG) channel degradation case studies. The proposed system without using classifier retraining techniques recovered of mean classification accuracy was of 4% to 38% for electrode displacement, movement artifacts, and saturation noise. The best mean classification considering all signal contaminants and channel combinations evaluated was the classification using the retraining method, replacing the degraded channel by the virtual sensor TVARMA model. This method recovered the classification accuracy after the degradations, reaching an average of 5.7% below the classification of the clean signal, that is the signal without the contaminants or the original signal. Moreover, the proposed intelligent technique minimizes the impact of the motion classification caused by signal contamination related to degrading events over time. There are improvements in the virtual sensor model and in the algorithm optimization that need further development to provide an increase the clinical application of myoelectric prostheses but already presents robust results to enable research with virtual sensors on biological signs with stochastic behavior. PMID:29723994

Using UMLS to construct a generalized hierarchical concept-based dictionary of brain functions for information extraction from the fMRI literature.

PubMed

Hsiao, Mei-Yu; Chen, Chien-Chung; Chen, Jyh-Horng

2009-10-01

With a rapid progress in the field, a great many fMRI studies are published every year, to the extent that it is now becoming difficult for researchers to keep up with the literature, since reading papers is extremely time-consuming and labor-intensive. Thus, automatic information extraction has become an important issue. In this study, we used the Unified Medical Language System (UMLS) to construct a hierarchical concept-based dictionary of brain functions. To the best of our knowledge, this is the first generalized dictionary of this kind. We also developed an information extraction system for recognizing, mapping and classifying terms relevant to human brain study. The precision and recall of our system was on a par with that of human experts in term recognition, term mapping and term classification. Our approach presented in this paper presents an alternative to the more laborious, manual entry approach to information extraction.

[Status of diagnosis and treatment devices of acupuncture based on SooPAT and bibliometrics in China].

PubMed

Bai, Lin; Ren, Yulan; Guo, Taipin; Chen, Lin; Zhou, Yumei; Feng, Shuwei; Li, Ji; Liang, Fanrong

2016-11-12

To perform a bibliometrics analysis on patent literature regarding diagnosis and treatment devices of acupuncture in China, aiming to provide references for the development of diagnosis and treatment devices of acupuncture. Based on SooPAT, a patent database, the patent literature regarding diagnosis and treatment devices of acupuncture in China was collected. With bibliometrics methods, the annual distribution of type, quantity, classification and content of diagnosis and treatment devices of acupuncture were analyzed. The number of acupuncture diagnosis and treatment devices reached its peak in 2012 and 2013 in China. The A61N in patent and utility model patent were the most, which were mainly related to electrotherapy, magnetic therapy, radioactive therapy and ultrasound therapy, etc. The main content was acupuncture treatment devices and meridian treatment devices. The 24-01 in design patent was the most, involving fixation devices used by doctors, hospitals and laboratories, etc. Currently the majority of diagnosis and treatment devices of acupuncture is therapeutic apparatus, while the acupuncture diagnosis devices are needed.

Lead exposure in US worksites: A literature review and development of an occupational lead exposure database from the published literature

PubMed Central

Koh, Dong-Hee; Locke, Sarah J.; Chen, Yu-Cheng; Purdue, Mark P.; Friesen, Melissa C.

2016-01-01

Background Retrospective exposure assessment of occupational lead exposure in population-based studies requires historical exposure information from many occupations and industries. Methods We reviewed published US exposure monitoring studies to identify lead exposure measurement data. We developed an occupational lead exposure database from the 175 identified papers containing 1,111 sets of lead concentration summary statistics (21% area air, 47% personal air, 32% blood). We also extracted ancillary exposure-related information, including job, industry, task/location, year collected, sampling strategy, control measures in place, and sampling and analytical methods. Results Measurements were published between 1940 and 2010 and represented 27 2-digit standardized industry classification codes. The majority of the measurements were related to lead-based paint work, joining or cutting metal using heat, primary and secondary metal manufacturing, and lead acid battery manufacturing. Conclusions This database can be used in future statistical analyses to characterize differences in lead exposure across time, jobs, and industries. PMID:25968240

Overview of classification systems in peripheral artery disease.

PubMed

Hardman, Rulon L; Jazaeri, Omid; Yi, J; Smith, M; Gupta, Rajan

2014-12-01

Peripheral artery disease (PAD), secondary to atherosclerotic disease, is currently the leading cause of morbidity and mortality in the western world. While PAD is common, it is estimated that the majority of patients with PAD are undiagnosed and undertreated. The challenge to the treatment of PAD is to accurately diagnose the symptoms and determine treatment for each patient. The varied presentations of peripheral vascular disease have led to numerous classification schemes throughout the literature. Consistent grading of patients leads to both objective criteria for treating patients and a baseline for clinical follow-up. Reproducible classification systems are also important in clinical trials and when comparing medical, surgical, and endovascular treatment paradigms. This article reviews the various classification systems for PAD and advantages to each system.

Supporting breast-feeding when a woman is homeless.

PubMed

Crespo-Fierro, Michele; Lunney, Margaret

2011-01-01

This case study demonstrates use of standardized nursing languages in the care of new mothers in community settings. The author collected data from clinical practice as an instructor in a baccalaureate nursing program and from the research literature. The appropriate nursing diagnoses, outcomes, and interventions were identified in partnership with the new mother. This case shows that NANDA International (NANDA-I), the Nursing Outcomes Classification (NOC), and the Nursing Interventions Classification (NIC) are useful to direct nursing care in community settings. When teaching nursing students in a baccalaureate program, nurse faculty can use NANDA-I, NOC, and NIC classifications to guide the growing practice of nursing students in community settings. © 2011, The Authors. International Journal of Nursing Terminologies and Classifications © 2011, NANDA International.

Hippocampome.org: a knowledge base of neuron types in the rodent hippocampus

PubMed Central

Wheeler, Diek W; White, Charise M; Rees, Christopher L; Komendantov, Alexander O; Hamilton, David J; Ascoli, Giorgio A

2015-01-01

Hippocampome.org is a comprehensive knowledge base of neuron types in the rodent hippocampal formation (dentate gyrus, CA3, CA2, CA1, subiculum, and entorhinal cortex). Although the hippocampal literature is remarkably information-rich, neuron properties are often reported with incompletely defined and notoriously inconsistent terminology, creating a formidable challenge for data integration. Our extensive literature mining and data reconciliation identified 122 neuron types based on neurotransmitter, axonal and dendritic patterns, synaptic specificity, electrophysiology, and molecular biomarkers. All ∼3700 annotated properties are individually supported by specific evidence (∼14,000 pieces) in peer-reviewed publications. Systematic analysis of this unprecedented amount of machine-readable information reveals novel correlations among neuron types and properties, the potential connectivity of the full hippocampal circuitry, and outstanding knowledge gaps. User-friendly browsing and online querying of Hippocampome.org may aid design and interpretation of both experiments and simulations. This powerful, simple, and extensible neuron classification endeavor is unique in its detail, utility, and completeness. DOI: http://dx.doi.org/10.7554/eLife.09960.001 PMID:26402459

CAN NEUROIMAGING HELP US TO UNDERSTAND AND CLASSIFY SOMATOFORM DISORDERS? A SYSTEMATIC AND CRITICAL REVIEW

PubMed Central

Browning, Michael; Fletcher, Paul; Sharpe, Michael

2011-01-01

Objective Debate about the nature of the somatoform disorders and their current diagnostic classification has been stimulated by the anticipation of new editions of the DSM and ICD diagnostic classifications. In the current paper we systematically review the literature on the neuroimaging of somatoform disorders and related conditions with the aim of addressing two specific questions: Is there evidence of altered neural function or structure that is specifically associated with somatoform disorders? What conclusions can we draw from these findings about the etiology of somatoform disorders? Methods Studies reporting neuroimaging findings in patients with a somatoform disorder, or a functional somatic syndrome (such as Fibromyalgia) were found using Pubmed, PsycINFO and EMBASE database searches. Reported structural and functional neuroimaging findings were then extracted to form a narrative review. Results A relatively mature literature on symptoms of pain, and less developed literatures on conversion and fatigue symptoms were identified. The available evidence indicates that, when compared to non-clinical groups, somatoform diagnoses are associated with increased activity of limbic regions in response to painful stimuli and a generalized decrease in grey matter density; however methodological considerations restrict the interpretation of these findings. Conclusions While the neuroimaging literature has provided evidence about the possible mechanisms underlying somatoform disorders this is not yet sufficient to provide a basis for classification. By adopting a wider variety of experimental designs and a more dynamic approach to diagnosis there is every reason to be hopeful that neuroimaging data will play a significant role in future taxonomies. PMID:21217095

AdOn HDP-HMM: An Adaptive Online Model for Segmentation and Classification of Sequential Data.

PubMed

Bargi, Ava; Xu, Richard Yi Da; Piccardi, Massimo

2017-09-21

Recent years have witnessed an increasing need for the automated classification of sequential data, such as activities of daily living, social media interactions, financial series, and others. With the continuous flow of new data, it is critical to classify the observations on-the-fly and without being limited by a predetermined number of classes. In addition, a model should be able to update its parameters in response to a possible evolution in the distributions of the classes. This compelling problem, however, does not seem to have been adequately addressed in the literature, since most studies focus on offline classification over predefined class sets. In this paper, we present a principled solution for this problem based on an adaptive online system leveraging Markov switching models and hierarchical Dirichlet process priors. This adaptive online approach is capable of classifying the sequential data over an unlimited number of classes while meeting the memory and delay constraints typical of streaming contexts. In this paper, we introduce an adaptive ''learning rate'' that is responsible for balancing the extent to which the model retains its previous parameters or adapts to new observations. Experimental results on stationary and evolving synthetic data and two video data sets, TUM Assistive Kitchen and collated Weizmann, show a remarkable performance in terms of segmentation and classification, particularly for sequences from evolutionary distributions and/or those containing previously unseen classes.

Classification of Partial Discharge Measured under Different Levels of Noise Contamination

PubMed Central

2017-01-01

Cable joint insulation breakdown may cause a huge loss to power companies. Therefore, it is vital to diagnose the insulation quality to detect early signs of insulation failure. It is well known that there is a correlation between Partial discharge (PD) and the insulation quality. Although many works have been done on PD pattern recognition, it is usually performed in a noise free environment. Also, works on PD pattern recognition in actual cable joint are less likely to be found in literature. Therefore, in this work, classifications of actual cable joint defect types from partial discharge data contaminated by noise were performed. Five cross-linked polyethylene (XLPE) cable joints with artificially created defects were prepared based on the defects commonly encountered on site. Three different types of input feature were extracted from the PD pattern under artificially created noisy environment. These include statistical features, fractal features and principal component analysis (PCA) features. These input features were used to train the classifiers to classify each PD defect types. Classifications were performed using three different artificial intelligence classifiers, which include Artificial Neural Networks (ANN), Adaptive Neuro-Fuzzy Inference System (ANFIS) and Support Vector Machine (SVM). It was found that the classification accuracy decreases with higher noise level but PCA features used in SVM and ANN showed the strongest tolerance against noise contamination. PMID:28085953

Evidences in Neurological Surgery and a Cutting Edge Classification of the Trigeminocardiac Reflex: A Systematic Review.

PubMed

Leon-Ariza, Daniel S; Leon-Ariza, Juan S; Nangiana, Jasvinder; Grau, Gabriel Vargas; Leon-Sarmiento, Fidias E; Quiñones-Hinojosa, Alfredo

2018-06-05

The trigeminocardiac reflex (TCR) is characterized by bradycardia, decrease of main arterial blood pressure (MABP), and sometimes, asystole during surgery. We critically reviewed TCR studies and devised a novel classification scheme for assessing the reflex. and Methods: A comprehensive systematic literature review was performed using PubMed, MEDLINE, Web of Science, EMBASE, and Scielo databases. Eligible studies were extracted based on stringent inclusion and exclusion criteria. Statistical analyses were used to assess cardiovascular variables. TCR was classified according to morphophysiological aspects involved with reflex elicitation. 575 patients were included in this study. TCR was found in 8.9% of patients. The reflex was more often triggered by interventions made within the anterior cranial fossa. The maxillary branch (type II in the new classification) was the most prevalent nerve branch found to trigger the TCR. Heart rate (HR) and mean arterial blood pressure (MABP) were similarly altered (p = 0.06; F = 0.3912809), covaried with age (p = 0.012; F = 9.302), and inversely correlated to each other (r = -0.27). TCR is a critical cardiovascular phenomenon that must be quickly identified, efficiently classified, and should trigger vigilance. Prompt therapeutic measures during neurosurgical procedures should be carefully addressed to avoid unwanted complications. Accurate categorization using the new classification scheme will help to improve understanding and guide the management of TCR in the perioperative period. Copyright © 2018 Elsevier Inc. All rights reserved.

Computational intelligence techniques for biological data mining: An overview

NASA Astrophysics Data System (ADS)

Faye, Ibrahima; Iqbal, Muhammad Javed; Said, Abas Md; Samir, Brahim Belhaouari

2014-10-01

Computational techniques have been successfully utilized for a highly accurate analysis and modeling of multifaceted and raw biological data gathered from various genome sequencing projects. These techniques are proving much more effective to overcome the limitations of the traditional in-vitro experiments on the constantly increasing sequence data. However, most critical problems that caught the attention of the researchers may include, but not limited to these: accurate structure and function prediction of unknown proteins, protein subcellular localization prediction, finding protein-protein interactions, protein fold recognition, analysis of microarray gene expression data, etc. To solve these problems, various classification and clustering techniques using machine learning have been extensively used in the published literature. These techniques include neural network algorithms, genetic algorithms, fuzzy ARTMAP, K-Means, K-NN, SVM, Rough set classifiers, decision tree and HMM based algorithms. Major difficulties in applying the above algorithms include the limitations found in the previous feature encoding and selection methods while extracting the best features, increasing classification accuracy and decreasing the running time overheads of the learning algorithms. The application of this research would be potentially useful in the drug design and in the diagnosis of some diseases. This paper presents a concise overview of the well-known protein classification techniques.

Holoentropy enabled-decision tree for automatic classification of diabetic retinopathy using retinal fundus images.

PubMed

Mane, Vijay Mahadeo; Jadhav, D V

2017-05-24

Diabetic retinopathy (DR) is the most common diabetic eye disease. Doctors are using various test methods to detect DR. But, the availability of test methods and requirements of domain experts pose a new challenge in the automatic detection of DR. In order to fulfill this objective, a variety of algorithms has been developed in the literature. In this paper, we propose a system consisting of a novel sparking process and a holoentropy-based decision tree for automatic classification of DR images to further improve the effectiveness. The sparking process algorithm is developed for automatic segmentation of blood vessels through the estimation of optimal threshold. The holoentropy enabled decision tree is newly developed for automatic classification of retinal images into normal or abnormal using hybrid features which preserve the disease-level patterns even more than the signal level of the feature. The effectiveness of the proposed system is analyzed using standard fundus image databases DIARETDB0 and DIARETDB1 for sensitivity, specificity and accuracy. The proposed system yields sensitivity, specificity and accuracy values of 96.72%, 97.01% and 96.45%, respectively. The experimental result reveals that the proposed technique outperforms the existing algorithms.

Clinical, aetiological, anatomical and pathological classification (CEAP): gold standard and limits.

PubMed

Rabe, E; Pannier, F

2012-03-01

The first CEAP (clinical, aetiological, anatomical and pathological elements) consensus document was published after a consensus conference of the American Venous Forum, held at the sixth annual meeting of the AVF in February 1994 in Maui, Hawaii. In the following years the CEAP classification was published in many international journals and books which has led to widespread international use of the CEAP classification since 1995. The aim of this paper is to review the benefits and limits of CEAP from the available literature. In an actual Medline analysis with the keywords 'CEAP' and 'venous insufficiency', 266 publications using the CEAP classification in venous diseases are available. The CEAP classification was accepted in the venous community and used in scientific publications, but in most of the cases only the clinical classification was used. Limitations of the first version including a lack of clear definition of clinical signs led to a revised version. The CEAP classification is the gold standard of classification of chronic venous disorders today. Nevertheless for proper use some facts have to be taken into account: the CEAP classification is not a severity classification, C2 summarizes all kinds of varicose veins, in C3 it may be difficult to separate venous and other reasons for oedema, and corona phlebectatica is not included in the classification. Further revisions of the CEAP classification may help to overcome the still-existing deficits.

Spinal tuberculosis, natural history of disease, classifications and principles of management with historical perspective.

PubMed

Kumar, Kush

2016-08-01

To describe the natural history spinal tuberculosis, classifications and principles of management based upon the grading of the neurological deficit. Review of literature was conducted with the aim to provide the clinico-radiological correlation of the natural history of spinal tuberculosis in different stages. Management strategy is developed based upon the severity of the neurological deficit. A five stage natural history of spinal tuberculosis is described. Stage of neurological involvement is further divided into 4 grades, predominantly on the basis of progressively increasing motor deficits as negligible, mild, moderate and severe with sensory and autonomic dysfunctions. Suitable principles of management with role of rest, braces, chemotherapy and surgery are discussed. Neurological deficit grading based management is developed. Grade 1 and 2, conservative treatment, grade 3, gray zone and grade 4, operative treatment is emphasized. The five stages of natural history of tuberculosis of spine have been developed from the clinician's point of view. Management of tuberculosis of spine, in general, it is no different than management of soft tissue tuberculosis, in HIV negative or positive patients. Role of surgery is very limited. Management of tubercular paraplegia, based upon the grading of paraplegia is simple, logical, efficient and easy to understand and remember by any orthopedic surgeon.

Recent revisions of phosphate rock reserves and resources: reassuring or misleading? An in-depth literature review of global estimates of phosphate rock reserves and resources

NASA Astrophysics Data System (ADS)

Edixhoven, J. D.; Gupta, J.; Savenije, H. H. G.

2013-09-01

Phosphate rock (PR) is a finite mineral indispensible for fertilizer production and a major pollutant. High grade PR is obtained from deposits which took millions of years to form and are gradually being depleted. Over the past three years, global PR reserves as reported by US Geological Survey (USGS) have seen a massive increase, from 16 000 Mt PR in 2010 to 65 000 Mt PR in 2011. The bulk of this four-fold increase is based on a 2010 report by International Fertilizer Development Center (IFDC), which increased Moroccan reserves from 5700 Mt PR as reported by USGS, to 51 000 Mt PR, reported as upgraded ("beneficiated") concentrate. IFDC used a starkly simplified classification compared to the classification used by USGS and proposed that agreement should be reached on PR resource terminology which should be as simple as possible. The report has profoundly influenced the PR scarcity debate, shifting the emphasis from depletion to the pollution angle of the phosphate problem. Various analysts adopted the findings of IFDC and USGS, and argued that that following depletion of reserves, uneconomic deposits (resources and occurrences) will remain available which will extend the lifetime of available deposits to thousands of years. Given the near total dependence of food production on PR, data on PR deposits must be transparent, comparable, reliable and credible. Based on an in-depth literature review, we analyze (i) how IFDC's simplified terminology compares to international best practice in resource classification and whether it is likely to yield data that meets the abovementioned requirements; (ii) whether the difference between ore reserves and reserves as concentrate is sufficiently noted in the literature, and (iii) whether the IFDC report and its estimate of PR reserves and resources is reliable. We conclude that, while there is a global development toward common criteria in resource reporting, IFDC's definitions contravene this development and - due to their vagueness and their lack of granularity - may cause more confusion than clarity. The difference between ore and concentrate is barely noted in the literature, causing a pervasive confusion and a high degree of error in many assessments. Finally, we conclude that the report presents an inflated picture of global reserves, in particular those of Morocco, where largely hypothetical and inferred resources have simply been converted to "reserves". In view of the essentiality of PR for food production, there currently is insufficient knowledge on the PR deposits available for extraction. Further research is required as to the quantity of PR deposits and their viability for future extraction.

Shin splints--a review of terminology.

PubMed

Batt, M E

1995-01-01

This review is intended to improve the understanding of and rationale for the use of the term shin splints. Currently the term is used widely and variably, with little consensus of definition. Broadly, it denotes the occurrence of exertional lower leg pain; more specifically, it refers to an anatomical site of periostitis. The literature reports a multiplicity of descriptions and definitions of shin splints resultant from the complex etiologies and differing perceptions of these conditions. It is proposed that the term shin splint be recognized as generic, rather than diagnostic, and that specific conditions that currently exist under this term be differentiated. The etiology and interaction of these related conditions are considered, and a classification based on the current literature is given of conditions currently termed shin splints, providing a rationale for their clinical presentations, investigative findings, and interactions.

Classification and reduction of pilot error

NASA Technical Reports Server (NTRS)

Rogers, W. H.; Logan, A. L.; Boley, G. D.

1989-01-01

Human error is a primary or contributing factor in about two-thirds of commercial aviation accidents worldwide. With the ultimate goal of reducing pilot error accidents, this contract effort is aimed at understanding the factors underlying error events and reducing the probability of certain types of errors by modifying underlying factors such as flight deck design and procedures. A review of the literature relevant to error classification was conducted. Classification includes categorizing types of errors, the information processing mechanisms and factors underlying them, and identifying factor-mechanism-error relationships. The classification scheme developed by Jens Rasmussen was adopted because it provided a comprehensive yet basic error classification shell or structure that could easily accommodate addition of details on domain-specific factors. For these purposes, factors specific to the aviation environment were incorporated. Hypotheses concerning the relationship of a small number of underlying factors, information processing mechanisms, and error types types identified in the classification scheme were formulated. ASRS data were reviewed and a simulation experiment was performed to evaluate and quantify the hypotheses.

ECG signal analysis through hidden Markov models.

PubMed

Andreão, Rodrigo V; Dorizzi, Bernadette; Boudy, Jérôme

2006-08-01

This paper presents an original hidden Markov model (HMM) approach for online beat segmentation and classification of electrocardiograms. The HMM framework has been visited because of its ability of beat detection, segmentation and classification, highly suitable to the electrocardiogram (ECG) problem. Our approach addresses a large panel of topics some of them never studied before in other HMM related works: waveforms modeling, multichannel beat segmentation and classification, and unsupervised adaptation to the patient's ECG. The performance was evaluated on the two-channel QT database in terms of waveform segmentation precision, beat detection and classification. Our waveform segmentation results compare favorably to other systems in the literature. We also obtained high beat detection performance with sensitivity of 99.79% and a positive predictivity of 99.96%, using a test set of 59 recordings. Moreover, premature ventricular contraction beats were detected using an original classification strategy. The results obtained validate our approach for real world application.

Post-treatment glenoid classification system for total shoulder arthroplasty.

PubMed

Churchill, R Sean

2012-04-01

Over the past 10 years, numerous advancements in glenoid preparation and resurfacing have occurred. Current glenoid classification systems are either focused solely on the patient's preoperative glenoid bone configuration or on the available glenoid bone stock in revision arthroplasty cases. While these systems provide value in preoperative planning, they fail to properly classify the surgical reconstruction completed. A literature review of common bone preparation methods and sources of glenoid prosthetic failure was performed. Based upon this review, a classification system for grading the status of the glenoid after prosthetic implantation was developed. A 6 category, post-treatment, glenoid classification system is proposed: type 0: no reaming; type I: glenoid reaming into but not through the subchondral bone; type II: glenoid reaming which perforates through <50% of the subchondral bone surface area; type III: glenoid reaming which perforates through >50% of the subchondral bone surface area; type IV: use of structural bone graft; and type V: use of a posterior augmented glenoid prosthesis. Types I-III are further subdivided into subtype A which have 100% bone support of the prosthesis, and subtype B which have a region of unsupported prosthesis. The classification system proposed addresses the surgical management of the glenoid during prosthetic replacement. This unique approach to classifying the glenoid following surgical intervention will allow direct follow-up comparison of similarly treated glenoid replacements. Future multicenter studies, possibly through joint registry databases, could then determine the long-term efficacy of the various glenoid preparation methods. Copyright © 2012 Journal of Shoulder and Elbow Surgery Board of Trustees. Published by Mosby, Inc. All rights reserved.

Burke-Fahn-Marsden dystonia severity, Gross Motor, Manual Ability, and Communication Function Classification scales in childhood hyperkinetic movement disorders including cerebral palsy: a 'Rosetta Stone' study.

PubMed

Elze, Markus C; Gimeno, Hortensia; Tustin, Kylee; Baker, Lesley; Lumsden, Daniel E; Hutton, Jane L; Lin, Jean-Pierre S-M

2016-02-01

Hyperkinetic movement disorders (HMDs) can be assessed using impairment-based scales or functional classifications. The Burke-Fahn-Marsden Dystonia Rating Scale-movement (BFM-M) evaluates dystonia impairment, but may not reflect functional ability. The Gross Motor Function Classification System (GMFCS), Manual Ability Classification System (MACS), and Communication Function Classification System (CFCS) are widely used in the literature on cerebral palsy to classify functional ability, but not in childhood movement disorders. We explore the concordance of these three functional scales in a large sample of paediatric HMDs and the impact of dystonia severity on these scales. Children with HMDs (n=161; median age 10y 3mo, range 2y 6mo-21y) were assessed using the BFM-M, GMFCS, MACS, and CFCS from 2007 to 2013. This cross-sectional study contrasts the information provided by these scales. All four scales were strongly associated (all Spearman's rank correlation coefficient rs >0.72, p<0.001), with worse dystonia severity implying worse function. Secondary dystonias had worse dystonia and less function than primary dystonias (p<0.001). A longer proportion of life lived with dystonia is associated with more severe dystonia (rs =0.42, p<0.001). The BFM-M is strongly linked with the GMFCS, MACS, and CFCS, irrespective of aetiology. Each scale offers interrelated but complementary information and is applicable to all aetiologies. Movement disorders including cerebral palsy can be effectively evaluated using these scales. © 2015 Mac Keith Press.

Natural control capabilities of robotic hands by hand amputated subjects.

PubMed

Atzori, Manfredo; Gijsberts, Arjan; Caputo, Barbara; Muller, Henning

2014-01-01

People with transradial hand amputations who own a myoelectric prosthesis currently have some control capabilities via sEMG. However, the control systems are still limited and not natural. The Ninapro project is aiming at helping the scientific community to overcome these limits through the creation of publicly available electromyography data sources to develop and test machine learning algorithms. In this paper we describe the movement classification results gained from three subjects with an homogeneous level of amputation, and we compare them with the results of 40 intact subjects. The number of considered subjects can seem small at first sight, but it is not considering the literature of the field (which has to face the difficulty of recruiting trans-radial hand amputated subjects). The classification is performed with four different classifiers and the obtained balanced classification rates are up to 58.6% on 50 movements, which is an excellent result compared to the current literature. Successively, for each subject we find a subset of up to 9 highly independent movements, (defined as movements that can be distinguished with more than 90% accuracy), which is a deeply innovative step in literature. The natural control of a robotic hand in so many movements could lead to an immediate progress in robotic hand prosthetics and it could deeply change the quality of life of amputated subjects.

Development of the first disability index for inflammatory bowel disease based on the international classification of functioning, disability and health

PubMed Central

Peyrin-Biroulet, Laurent; Cieza, Alarcos; Sandborn, William J; Coenen, Michaela; Chowers, Yehuda; Hibi, Toshifumi; Kostanjsek, Nenad; Stucki, Gerold

2011-01-01

Objective The impact of inflammatory bowel disease (IBD) on disability remains poorly understood. The World Health Organization's integrative model of human functioning and disability in the International Classification of Functioning, Disability and Health (ICF) makes disability assessment possible. The ICF is a hierarchical coding system with four levels of details that includes over 1400 categories. The aim of this study was to develop the first disability index for IBD by selecting most relevant ICF categories that are affected by IBD. Methods Relevant ICF categories were identified through four preparatory studies (systematic literature review, qualitative study, expert survey and cross-sectional study), which were presented at a consensus conference. Based on the identified ICF categories, a questionnaire to be filled in by clinicians, called the ‘IBD disability index’, was developed. Results The four preparatory studies identified 138 second-level categories: 75 for systematic literature review (153 studies), 38 for qualitative studies (six focus groups; 27 patients), 108 for expert survey (125 experts; 37 countries; seven occupations) and 98 for cross-sectional study (192 patients; three centres). The consensus conference (20 experts; 17 countries) led to the selection of 19 ICF core set categories that were used to develop the IBD disability index: seven on body functions, two on body structures, five on activities and participation and five on environmental factors. Conclusions The IBD disability index is now available. It will be used in studies to evaluate the long-term effect of IBD on patient functional status and will serve as a new endpoint in disease-modification trials. PMID:21646246

Lumbar scoliosis associated with spinal stenosis in idiopathic and degenerative cases.

PubMed

Le Huec, J C; Cogniet, A; Mazas, S; Faundez, A

2016-10-01

Degenerative de novo scoliosis is commonly present in older adult patients. The degenerative process including disc bulging, facet arthritis, and ligamentum flavum hypertrophy contributes to the appearance of symptoms of spinal stenosis. Idiopathic scoliosis has also degenerative changes that can lead to spinal stenosis. The aetiology, prevalence, biomechanics, classification, symptomatology, and treatment of idiopathic and degenerative lumbar scoliosis in association with spinal stenosis are reviewed. Review study is based on a review of pertinent but non-exhaustive literature of the last 20 years in PubMed in English language. Retrospective analysis of studies focused on all parameters concerning scoliosis associated with stenosis. Very few publications have focused specifically on idiopathic scoliosis and stenosis, and this was before the advent of modern segmental instrumentation. On the other hand, many papers were found for degenerative scoliosis and stenosis with treatment methods based on aetiology of spinal canal stenosis and analysis of global sagittal and frontal parameters. Satisfactory clinical results after operative treatment range from 83 to 96 % but with increased percentage of complications. Recent literature analysed the importance of stabilizing or not the spine after decompression in such situation knowing the increasing risk of instability after facet resection. No prospective randomized studies were found to support short instrumentation. Long instrumentation and fusion to prevent distabilization after decompression were always associated with higher complication rates. Imbalance patients with unsatisfactory compensation capacities were at risk of complications. Operative treatment using newly proposed classification system of lumbar scoliosis with associated canal stenosis is useful. Sagittal balance and rotatory dislocation are the main parameters to analyse to determine the length of fusion.

Comparing the usefulness of the 1997 and 2009 WHO dengue case classification: a systematic literature review.

PubMed

Horstick, Olaf; Jaenisch, Thomas; Martinez, Eric; Kroeger, Axel; See, Lucy Lum Chai; Farrar, Jeremy; Ranzinger, Silvia Runge

2014-09-01

The 1997 and 2009 WHO dengue case classifications were compared in a systematic review with 12 eligible studies (4 prospective). Ten expert opinion articles were used for discussion. For the 2009 WHO classification studies show: when determining severe dengue sensitivity ranges between 59-98% (88%/98%: prospective studies), specificity between 41-99% (99%: prospective study) - comparing the 1997 WHO classification: sensitivity 24.8-89.9% (24.8%/74%: prospective studies), specificity: 25%/100% (100%: prospective study). The application of the 2009 WHO classification is easy, however for (non-severe) dengue there may be a risk of monitoring increased case numbers. Warning signs validation studies are needed. For epidemiological/pathogenesis research use of the 2009 WHO classification, opinion papers show that ease of application, increased sensitivity (severe dengue) and international comparability are advantageous; 3 severe dengue criteria (severe plasma leakage, severe bleeding, severe organ manifestation) are useful research endpoints. The 2009 WHO classification has clear advantages for clinical use, use in epidemiology is promising and research use may at least not be a disadvantage. © The American Society of Tropical Medicine and Hygiene.

Utilization of the NSQIP-Pediatric Database in Development and Validation of a New Predictive Model of Pediatric Postoperative Wound Complications.

PubMed

Maizlin, Ilan I; Redden, David T; Beierle, Elizabeth A; Chen, Mike K; Russell, Robert T

2017-04-01

Surgical wound classification, introduced in 1964, stratifies the risk of surgical site infection (SSI) based on a clinical estimate of the inoculum of bacteria encountered during the procedure. Recent literature has questioned the accuracy of predicting SSI risk based on wound classification. We hypothesized that a more specific model founded on specific patient and perioperative factors would more accurately predict the risk of SSI. Using all observations from the 2012 to 2014 pediatric National Surgical Quality Improvement Program-Pediatric (NSQIP-P) Participant Use File, patients were randomized into model creation and model validation datasets. Potential perioperative predictive factors were assessed with univariate analysis for each of 4 outcomes: wound dehiscence, superficial wound infection, deep wound infection, and organ space infection. A multiple logistic regression model with a step-wise backwards elimination was performed. A receiver operating characteristic curve with c-statistic was generated to assess the model discrimination for each outcome. A total of 183,233 patients were included. All perioperative NSQIP factors were evaluated for clinical pertinence. Of the original 43 perioperative predictive factors selected, 6 to 9 predictors for each outcome were significantly associated with postoperative SSI. The predictive accuracy level of our model compared favorably with the traditional wound classification in each outcome of interest. The proposed model from NSQIP-P demonstrated a significantly improved predictive ability for postoperative SSIs than the current wound classification system. This model will allow providers to more effectively counsel families and patients of these risks, and more accurately reflect true risks for individual surgical patients to hospitals and payers. Copyright © 2017 American College of Surgeons. Published by Elsevier Inc. All rights reserved.

A real-time classification algorithm for EEG-based BCI driven by self-induced emotions.

PubMed

Iacoviello, Daniela; Petracca, Andrea; Spezialetti, Matteo; Placidi, Giuseppe

2015-12-01

The aim of this paper is to provide an efficient, parametric, general, and completely automatic real time classification method of electroencephalography (EEG) signals obtained from self-induced emotions. The particular characteristics of the considered low-amplitude signals (a self-induced emotion produces a signal whose amplitude is about 15% of a really experienced emotion) require exploring and adapting strategies like the Wavelet Transform, the Principal Component Analysis (PCA) and the Support Vector Machine (SVM) for signal processing, analysis and classification. Moreover, the method is thought to be used in a multi-emotions based Brain Computer Interface (BCI) and, for this reason, an ad hoc shrewdness is assumed. The peculiarity of the brain activation requires ad-hoc signal processing by wavelet decomposition, and the definition of a set of features for signal characterization in order to discriminate different self-induced emotions. The proposed method is a two stages algorithm, completely parameterized, aiming at a multi-class classification and may be considered in the framework of machine learning. The first stage, the calibration, is off-line and is devoted at the signal processing, the determination of the features and at the training of a classifier. The second stage, the real-time one, is the test on new data. The PCA theory is applied to avoid redundancy in the set of features whereas the classification of the selected features, and therefore of the signals, is obtained by the SVM. Some experimental tests have been conducted on EEG signals proposing a binary BCI, based on the self-induced disgust produced by remembering an unpleasant odor. Since in literature it has been shown that this emotion mainly involves the right hemisphere and in particular the T8 channel, the classification procedure is tested by using just T8, though the average accuracy is calculated and reported also for the whole set of the measured channels. The obtained classification results are encouraging with percentage of success that is, in the average for the whole set of the examined subjects, above 90%. An ongoing work is the application of the proposed procedure to map a large set of emotions with EEG and to establish the EEG headset with the minimal number of channels to allow the recognition of a significant range of emotions both in the field of affective computing and in the development of auxiliary communication tools for subjects affected by severe disabilities. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Land Cover Classification in a Complex Urban-Rural Landscape with Quickbird Imagery

PubMed Central

Moran, Emilio Federico.

2010-01-01

High spatial resolution images have been increasingly used for urban land use/cover classification, but the high spectral variation within the same land cover, the spectral confusion among different land covers, and the shadow problem often lead to poor classification performance based on the traditional per-pixel spectral-based classification methods. This paper explores approaches to improve urban land cover classification with Quickbird imagery. Traditional per-pixel spectral-based supervised classification, incorporation of textural images and multispectral images, spectral-spatial classifier, and segmentation-based classification are examined in a relatively new developing urban landscape, Lucas do Rio Verde in Mato Grosso State, Brazil. This research shows that use of spatial information during the image classification procedure, either through the integrated use of textural and spectral images or through the use of segmentation-based classification method, can significantly improve land cover classification performance. PMID:21643433

The comprehensiveness of the ESHRE/ESGE classification of female genital tract congenital anomalies: a systematic review of cases not classified by the AFS system.

PubMed

Di Spiezio Sardo, A; Campo, R; Gordts, S; Spinelli, M; Cosimato, C; Tanos, V; Brucker, S; Li, T C; Gergolet, M; De Angelis, C; Gianaroli, L; Grimbizis, G

2015-05-01

How comprehensive is the recently published European Society of Human Reproduction and Embryology (ESHRE)/European Society for Gynaecological Endoscopy (ESGE) classification system of female genital anomalies? The ESHRE/ESGE classification provides a comprehensive description and categorization of almost all of the currently known anomalies that could not be classified properly with the American Fertility Society (AFS) system. Until now, the more accepted classification system, namely that of the AFS, is associated with serious limitations in effective categorization of female genital anomalies. Many cases published in the literature could not be properly classified using the AFS system, yet a clear and accurate classification is a prerequisite for treatment. The CONUTA (CONgenital UTerine Anomalies) ESHRE/ESGE group conducted a systematic review of the literature to examine if those types of anomalies that could not be properly classified with the AFS system could be effectively classified with the use of the new ESHRE/ESGE system. An electronic literature search through Medline, Embase and Cochrane library was carried out from January 1988 to January 2014. Three participants independently screened, selected articles of potential interest and finally extracted data from all the included studies. Any disagreement was discussed and resolved after consultation with a fourth reviewer and the results were assessed independently and approved by all members of the CONUTA group. Among the 143 articles assessed in detail, 120 were finally selected reporting 140 cases that could not properly fit into a specific class of the AFS system. Those 140 cases were clustered in 39 different types of anomalies. The congenital anomaly involved a single organ in 12 (30.8%) out of the 39 types of anomalies, while multiple organs and/or segments of Müllerian ducts (complex anomaly) were involved in 27 (69.2%) types. Uterus was the organ most frequently involved (30/39: 76.9%), followed by cervix (26/39: 66.7%) and vagina (23/39: 59%). In all 39 types, the ESHRE/ESGE classification system provided a comprehensive description of each single or complex anomaly. A precise categorization was reached in 38 out of 39 types studied. Only one case of a bizarre uterine anomaly, with no clear embryological defect, could not be categorized and thus was placed in Class 6 (un-classified) of the ESHRE/ESGE system. The review of the literature was thorough but we cannot rule out the possibility that other defects exist which will also require testing in the new ESHRE/ESGE system. These anomalies, however, must be rare. The comprehensiveness of the ESHRE/ESGE classification adds objective scientific validity to its use. This may, therefore, promote its further dissemination and acceptance, which will have a positive outcome in clinical care and research. None. © The Author 2015. Published by Oxford University Press on behalf of the European Society of Human Reproduction and Embryology.

Geometric classification of scalp hair for valid drug testing, 6 more reliable than 8 hair curl groups

PubMed Central

Mkentane, K.; Gumedze, F.; Ngoepe, M.; Davids, L. M.; Khumalo, N. P.

2017-01-01

Introduction Curly hair is reported to contain higher lipid content than straight hair, which may influence incorporation of lipid soluble drugs. The use of race to describe hair curl variation (Asian, Caucasian and African) is unscientific yet common in medical literature (including reports of drug levels in hair). This study investigated the reliability of a geometric classification of hair (based on 3 measurements: the curve diameter, curl index and number of waves). Materials and methods After ethical approval and informed consent, proximal virgin (6cm) hair sampled from the vertex of scalp in 48 healthy volunteers were evaluated. Three raters each scored hairs from 48 volunteers at two occasions each for the 8 and 6-group classifications. One rater applied the 6-group classification to 80 additional volunteers in order to further confirm the reliability of this system. The Kappa statistic was used to assess intra and inter rater agreement. Results Each rater classified 480 hairs on each occasion. No rater classified any volunteer’s 10 hairs into the same group; the most frequently occurring group was used for analysis. The inter-rater agreement was poor for the 8-groups (k = 0.418) but improved for the 6-groups (k = 0.671). The intra-rater agreement also improved (k = 0.444 to 0.648 versus 0.599 to 0.836) for 6-groups; that for the one evaluator for all volunteers was good (k = 0.754). Conclusions Although small, this is the first study to test the reliability of a geometric classification. The 6-group method is more reliable. However, a digital classification system is likely to reduce operator error. A reliable objective classification of human hair curl is long overdue, particularly with the increasing use of hair as a testing substrate for treatment compliance in Medicine. PMID:28570555

A web-based neurological pain classifier tool utilizing Bayesian decision theory for pain classification in spinal cord injury patients

NASA Astrophysics Data System (ADS)

Verma, Sneha K.; Chun, Sophia; Liu, Brent J.

2014-03-01

Pain is a common complication after spinal cord injury with prevalence estimates ranging 77% to 81%, which highly affects a patient's lifestyle and well-being. In the current clinical setting paper-based forms are used to classify pain correctly, however, the accuracy of diagnoses and optimal management of pain largely depend on the expert reviewer, which in many cases is not possible because of very few experts in this field. The need for a clinical decision support system that can be used by expert and non-expert clinicians has been cited in literature, but such a system has not been developed. We have designed and developed a stand-alone tool for correctly classifying pain type in spinal cord injury (SCI) patients, using Bayesian decision theory. Various machine learning simulation methods are used to verify the algorithm using a pilot study data set, which consists of 48 patients data set. The data set consists of the paper-based forms, collected at Long Beach VA clinic with pain classification done by expert in the field. Using the WEKA as the machine learning tool we have tested on the 48 patient dataset that the hypothesis that attributes collected on the forms and the pain location marked by patients have very significant impact on the pain type classification. This tool will be integrated with an imaging informatics system to support a clinical study that will test the effectiveness of using Proton Beam radiotherapy for treating spinal cord injury (SCI) related neuropathic pain as an alternative to invasive surgical lesioning.

Expanding the Taxonomy of the Diagnostic Criteria for Temporomandibular Disorders (DC/TMD)

PubMed Central

Peck, Christopher C.; Goulet, Jean-Paul; Lobbezoo, Frank; Schiffman, Eric L.; Alstergren, Per; Anderson, Gary C.; de Leeuw, Reny; Jensen, Rigmor; Michelotti, Ambra; Ohrbach, Richard; Petersson, Arne; List, Thomas

2014-01-01

Background There is a need to expand the current temporomandibular disorder (TMD) classification to include less common, but clinically important disorders. The immediate aim was to develop a consensus-based classification system and associated diagnostic criteria that have clinical and research utility for less common TMDs. The long-term aim was to establish a foundation, vis-à-vis this classification system, that will stimulate data collection, validity testing, and further criteria refinement. Methods A working group [members of the International RDC/TMD Consortium Network of the International Association for Dental Research (IADR), members of the Orofacial Pain Special Interest Group (SIG) of the International Association for the Study of Pain (IASP), and members from other professional societies] reviewed disorders for inclusion based on clinical significance, the availability of plausible diagnostic criteria, and the ability to operationalize and study the criteria. The disorders were derived from the literature when possible and based on expert opinion as necessary. The expanded TMD taxonomy was presented for feedback at international meetings. Results Of 56 disorders considered, 37 were included in the expanded taxonomy and were placed into the following four categories: temporomandibular joint disorders, masticatory muscle disorders, headache disorders, and disorders affecting associated structures. Those excluded were extremely uncommon, lacking operationalized diagnostic criteria, not clearly related to TMDs, or not sufficiently distinct from disorders already included within the taxonomy. Conclusions The expanded TMD taxonomy offers an integrated approach to clinical diagnosis and provides a framework for further research to operationalize and test the proposed taxonomy and diagnostic criteria. PMID:24443898

Expanding the taxonomy of the diagnostic criteria for temporomandibular disorders.

PubMed

Peck, C C; Goulet, J-P; Lobbezoo, F; Schiffman, E L; Alstergren, P; Anderson, G C; de Leeuw, R; Jensen, R; Michelotti, A; Ohrbach, R; Petersson, A; List, T

2014-01-01

There is a need to expand the current temporomandibular disorders' (TMDs) classification to include less common but clinically important disorders. The immediate aim was to develop a consensus-based classification system and associated diagnostic criteria that have clinical and research utility for less common TMDs. The long-term aim was to establish a foundation, vis-à-vis this classification system, that will stimulate data collection, validity testing and further criteria refinement. A working group [members of the International RDC/TMD Consortium Network of the International Association for Dental Research (IADR), members of the Orofacial Pain Special Interest Group (SIG) of the International Association for the Study of Pain (IASP), and members from other professional societies] reviewed disorders for inclusion based on clinical significance, the availability of plausible diagnostic criteria and the ability to operationalise and study the criteria. The disorders were derived from the literature when possible and based on expert opinion as necessary. The expanded TMDs taxonomy was presented for feedback at international meetings. Of 56 disorders considered, 37 were included in the expanded taxonomy and were placed into the following four categories: temporomandibular joint disorders, masticatory muscle disorders, headache disorders and disorders affecting associated structures. Those excluded were extremely uncommon, lacking operationalised diagnostic criteria, not clearly related to TMDs, or not sufficiently distinct from disorders already included within the taxonomy. The expanded TMDs taxonomy offers an integrated approach to clinical diagnosis and provides a framework for further research to operationalise and test the proposed taxonomy and diagnostic criteria. © 2014 John Wiley & Sons Ltd.

River reach classification for the Greater Mekong Region at high spatial resolution

NASA Astrophysics Data System (ADS)

Ouellet Dallaire, C.; Lehner, B.

2014-12-01

River classifications have been used in river health and ecological assessments as coarse proxies to represent aquatic biodiversity when comprehensive biological and/or species data is unavailable. Currently there are no river classifications or biological data available in a consistent format for the extent of the Greater Mekong Region (GMR; including the Irrawaddy, the Salween, the Chao Praya, the Mekong and the Red River basins). The current project proposes a new river habitat classification for the region, facilitated by the HydroSHEDS (HYDROlogical SHuttle Elevation Derivatives at multiple Scales) database at 500m pixel resolution. The classification project is based on the Global River Classification framework relying on the creation of multiple sub-classifications based on different disciplines. The resulting classes from the sub-classification are later combined into final classes to create a holistic river reach classification. For the GMR, a final habitat classification was created based on three sub-classifications: a hydrological sub-classification based only on discharge indices (river size and flow variability); a physio-climatic sub-classification based on large scale indices of climate and elevation (biomes, ecoregions and elevation); and a geomorphological sub-classification based on local morphology (presence of floodplains, reach gradient and sand transport). Key variables and thresholds were identified in collaboration with local experts to ensure that regional knowledge was included. The final classification is composed 54 unique final classes based on 3 sub-classifications with less than 15 classes each. The resulting classifications are driven by abiotic variables and do not include biological data, but they represent a state-of-the art product based on best available data (mostly global data). The most common river habitat type is the "dry broadleaf, low gradient, very small river". These classifications could be applied in a wide range of hydro-ecological assessments and useful for a variety of stakeholders such as NGO, governments and researchers.

Evaluation of gene expression classification studies: factors associated with classification performance.

PubMed

Novianti, Putri W; Roes, Kit C B; Eijkemans, Marinus J C

2014-01-01

Classification methods used in microarray studies for gene expression are diverse in the way they deal with the underlying complexity of the data, as well as in the technique used to build the classification model. The MAQC II study on cancer classification problems has found that performance was affected by factors such as the classification algorithm, cross validation method, number of genes, and gene selection method. In this paper, we study the hypothesis that the disease under study significantly determines which method is optimal, and that additionally sample size, class imbalance, type of medical question (diagnostic, prognostic or treatment response), and microarray platform are potentially influential. A systematic literature review was used to extract the information from 48 published articles on non-cancer microarray classification studies. The impact of the various factors on the reported classification accuracy was analyzed through random-intercept logistic regression. The type of medical question and method of cross validation dominated the explained variation in accuracy among studies, followed by disease category and microarray platform. In total, 42% of the between study variation was explained by all the study specific and problem specific factors that we studied together.

On Classification in the Study of Failure, and a Challenge to Classifiers

NASA Technical Reports Server (NTRS)

Wasson, Kimberly S.

2003-01-01

Classification schemes are abundant in the literature of failure. They serve a number of purposes, some more successfully than others. We examine several classification schemes constructed for various purposes relating to failure and its investigation, and discuss their values and limits. The analysis results in a continuum of uses for classification schemes, that suggests that the value of certain properties of these schemes is dependent on the goals a classification is designed to forward. The contrast in the value of different properties for different uses highlights a particular shortcoming: we argue that while humans are good at developing one kind of scheme: dynamic, flexible classifications used for exploratory purposes, we are not so good at developing another: static, rigid classifications used to trap and organize data for specific analytic goals. Our lack of strong foundation in developing valid instantiations of the latter impedes progress toward a number of investigative goals. This shortcoming and its consequences pose a challenge to researchers in the study of failure: to develop new methods for constructing and validating static classification schemes of demonstrable value in promoting the goals of investigations. We note current productive activity in this area, and outline foundations for more.

ANALYSIS OF A CLASSIFICATION ERROR MATRIX USING CATEGORICAL DATA TECHNIQUES.

USGS Publications Warehouse

Rosenfield, George H.; Fitzpatrick-Lins, Katherine

1984-01-01

Summary form only given. A classification error matrix typically contains tabulation results of an accuracy evaluation of a thematic classification, such as that of a land use and land cover map. The diagonal elements of the matrix represent the counts corrected, and the usual designation of classification accuracy has been the total percent correct. The nondiagonal elements of the matrix have usually been neglected. The classification error matrix is known in statistical terms as a contingency table of categorical data. As an example, an application of these methodologies to a problem of remotely sensed data concerning two photointerpreters and four categories of classification indicated that there is no significant difference in the interpretation between the two photointerpreters, and that there are significant differences among the interpreted category classifications. However, two categories, oak and cottonwood, are not separable in classification in this experiment at the 0. 51 percent probability. A coefficient of agreement is determined for the interpreted map as a whole, and individually for each of the interpreted categories. A conditional coefficient of agreement for the individual categories is compared to other methods for expressing category accuracy which have already been presented in the remote sensing literature.

Searching the scientific literature: implications for quantitative and qualitative reviews.

PubMed

Wu, Yelena P; Aylward, Brandon S; Roberts, Michael C; Evans, Spencer C

2012-08-01

Literature reviews are an essential step in the research process and are included in all empirical and review articles. Electronic databases are commonly used to gather this literature. However, several factors can affect the extent to which relevant articles are retrieved, influencing future research and conclusions drawn. The current project examined articles obtained by comparable search strategies in two electronic archives using an exemplar search to illustrate factors that authors should consider when designing their own search strategies. Specifically, literature searches were conducted in PsycINFO and PubMed targeting review articles on two exemplar disorders (bipolar disorder and attention deficit/hyperactivity disorder) and issues of classification and/or differential diagnosis. Articles were coded for relevance and characteristics of article content. The two search engines yielded significantly different proportions of relevant articles overall and by disorder. Keywords differed across search engines for the relevant articles identified. Based on these results, it is recommended that when gathering literature for review papers, multiple search engines should be used, and search syntax and strategies be tailored to the unique capabilities of particular engines. For meta-analyses and systematic reviews, authors may consider reporting the extent to which different archives or sources yielded relevant articles for their particular review. Copyright © 2012 Elsevier Ltd. All rights reserved.

Thermal Runaway Due to Strain-Heading Feedback,

DTIC Science & Technology

1985-05-28

ApprovedREPORT DOCUMENTATION PAGE OMBNo. 0704-0188 la. REPORT SECURITY CLASSIFICATION lb. RESTRICTIVE MARKINGS 2a. SECURITY CLASSIFICATION AUTHORITY 3...instability. The thermal runaway phenomenon has been discussed in the geophysics literature (e.g. Brun and Cobbold 1980, Cary et al. 1979 and Wan et al...pp. 325-342. Boley, B.A. and Weiner, J.H., 1960, Theory of Thermal Stresses, John Wiley and Sons, Inc. Brun, Y.P. and Cobbold , P.R., 1980, Strain

Development and application of an interaction network ontology for literature mining of vaccine-associated gene-gene interactions.

PubMed

Hur, Junguk; Özgür, Arzucan; Xiang, Zuoshuang; He, Yongqun

2015-01-01

Literature mining of gene-gene interactions has been enhanced by ontology-based name classifications. However, in biomedical literature mining, interaction keywords have not been carefully studied and used beyond a collection of keywords. In this study, we report the development of a new Interaction Network Ontology (INO) that classifies >800 interaction keywords and incorporates interaction terms from the PSI Molecular Interactions (PSI-MI) and Gene Ontology (GO). Using INO-based literature mining results, a modified Fisher's exact test was established to analyze significantly over- and under-represented enriched gene-gene interaction types within a specific area. Such a strategy was applied to study the vaccine-mediated gene-gene interactions using all PubMed abstracts. The Vaccine Ontology (VO) and INO were used to support the retrieval of vaccine terms and interaction keywords from the literature. INO is aligned with the Basic Formal Ontology (BFO) and imports terms from 10 other existing ontologies. Current INO includes 540 terms. In terms of interaction-related terms, INO imports and aligns PSI-MI and GO interaction terms and includes over 100 newly generated ontology terms with 'INO_' prefix. A new annotation property, 'has literature mining keywords', was generated to allow the listing of different keywords mapping to the interaction types in INO. Using all PubMed documents published as of 12/31/2013, approximately 266,000 vaccine-associated documents were identified, and a total of 6,116 gene-pairs were associated with at least one INO term. Out of 78 INO interaction terms associated with at least five gene-pairs of the vaccine-associated sub-network, 14 terms were significantly over-represented (i.e., more frequently used) and 17 under-represented based on our modified Fisher's exact test. These over-represented and under-represented terms share some common top-level terms but are distinct at the bottom levels of the INO hierarchy. The analysis of these interaction types and their associated gene-gene pairs uncovered many scientific insights. INO provides a novel approach for defining hierarchical interaction types and related keywords for literature mining. The ontology-based literature mining, in combination with an INO-based statistical interaction enrichment test, provides a new platform for efficient mining and analysis of topic-specific gene interaction networks.

Blastocyst classification systems used in Latin America: is a consensus possible?

PubMed Central

Puga-Torres, Tatiana; Blum-Rojas, Xavier; Blum-Narváez, Medardo

2017-01-01

Objective To identify different blastocyst classification systems used by embryologists in Latin American countries and evaluate the possibility of establishing a consensus among these countries. Methods An E-mail survey was carried out through the Latin American Network of Assisted Reproduction (REDLARA) aimed at embryologists from assisted reproduction centers in Latin countries. Results Sixty surveys were collected from 12 Latin American countries, of which 66.7% had >10years of professional practice as embryologists. Seven different blastocyst classification systems were reported, of which 5 have previously been described in the literature. Conclusion Although the group of embryologists surveyed use different blastocyst classification systems, most in this group consider that the embryo score system should be unified in their countries as well as in the region. PMID:28837032

Object-Based Random Forest Classification of Land Cover from Remotely Sensed Imagery for Industrial and Mining Reclamation

NASA Astrophysics Data System (ADS)

Chen, Y.; Luo, M.; Xu, L.; Zhou, X.; Ren, J.; Zhou, J.

2018-04-01

The RF method based on grid-search parameter optimization could achieve a classification accuracy of 88.16 % in the classification of images with multiple feature variables. This classification accuracy was higher than that of SVM and ANN under the same feature variables. In terms of efficiency, the RF classification method performs better than SVM and ANN, it is more capable of handling multidimensional feature variables. The RF method combined with object-based analysis approach could highlight the classification accuracy further. The multiresolution segmentation approach on the basis of ESP scale parameter optimization was used for obtaining six scales to execute image segmentation, when the segmentation scale was 49, the classification accuracy reached the highest value of 89.58 %. The classification accuracy of object-based RF classification was 1.42 % higher than that of pixel-based classification (88.16 %), and the classification accuracy was further improved. Therefore, the RF classification method combined with object-based analysis approach could achieve relatively high accuracy in the classification and extraction of land use information for industrial and mining reclamation areas. Moreover, the interpretation of remotely sensed imagery using the proposed method could provide technical support and theoretical reference for remotely sensed monitoring land reclamation.

Land Cover Analysis by Using Pixel-Based and Object-Based Image Classification Method in Bogor

NASA Astrophysics Data System (ADS)

Amalisana, Birohmatin; Rokhmatullah; Hernina, Revi

2017-12-01

The advantage of image classification is to provide earth’s surface information like landcover and time-series changes. Nowadays, pixel-based image classification technique is commonly performed with variety of algorithm such as minimum distance, parallelepiped, maximum likelihood, mahalanobis distance. On the other hand, landcover classification can also be acquired by using object-based image classification technique. In addition, object-based classification uses image segmentation from parameter such as scale, form, colour, smoothness and compactness. This research is aimed to compare the result of landcover classification and its change detection between parallelepiped pixel-based and object-based classification method. Location of this research is Bogor with 20 years range of observation from 1996 until 2016. This region is famous as urban areas which continuously change due to its rapid development, so that time-series landcover information of this region will be interesting.

Random forest feature selection, fusion and ensemble strategy: Combining multiple morphological MRI measures to discriminate among healhy elderly, MCI, cMCI and alzheimer's disease patients: From the alzheimer's disease neuroimaging initiative (ADNI) database.

PubMed

Dimitriadis, S I; Liparas, Dimitris; Tsolaki, Magda N

2018-05-15

In the era of computer-assisted diagnostic tools for various brain diseases, Alzheimer's disease (AD) covers a large percentage of neuroimaging research, with the main scope being its use in daily practice. However, there has been no study attempting to simultaneously discriminate among Healthy Controls (HC), early mild cognitive impairment (MCI), late MCI (cMCI) and stable AD, using features derived from a single modality, namely MRI. Based on preprocessed MRI images from the organizers of a neuroimaging challenge, 3 we attempted to quantify the prediction accuracy of multiple morphological MRI features to simultaneously discriminate among HC, MCI, cMCI and AD. We explored the efficacy of a novel scheme that includes multiple feature selections via Random Forest from subsets of the whole set of features (e.g. whole set, left/right hemisphere etc.), Random Forest classification using a fusion approach and ensemble classification via majority voting. From the ADNI database, 60 HC, 60 MCI, 60 cMCI and 60 CE were used as a training set with known labels. An extra dataset of 160 subjects (HC: 40, MCI: 40, cMCI: 40 and AD: 40) was used as an external blind validation dataset to evaluate the proposed machine learning scheme. In the second blind dataset, we succeeded in a four-class classification of 61.9% by combining MRI-based features with a Random Forest-based Ensemble Strategy. We achieved the best classification accuracy of all teams that participated in this neuroimaging competition. The results demonstrate the effectiveness of the proposed scheme to simultaneously discriminate among four groups using morphological MRI features for the very first time in the literature. Hence, the proposed machine learning scheme can be used to define single and multi-modal biomarkers for AD. Copyright © 2017 Elsevier B.V. All rights reserved.

Extracting time-frequency feature of single-channel vastus medialis EMG signals for knee exercise pattern recognition.

PubMed

Zhang, Yi; Li, Peiyang; Zhu, Xuyang; Su, Steven W; Guo, Qing; Xu, Peng; Yao, Dezhong

2017-01-01

The EMG signal indicates the electrophysiological response to daily living of activities, particularly to lower-limb knee exercises. Literature reports have shown numerous benefits of the Wavelet analysis in EMG feature extraction for pattern recognition. However, its application to typical knee exercises when using only a single EMG channel is limited. In this study, three types of knee exercises, i.e., flexion of the leg up (standing), hip extension from a sitting position (sitting) and gait (walking) are investigated from 14 healthy untrained subjects, while EMG signals from the muscle group of vastus medialis and the goniometer on the knee joint of the detected leg are synchronously monitored and recorded. Four types of lower-limb motions including standing, sitting, stance phase of walking, and swing phase of walking, are segmented. The Wavelet Transform (WT) based Singular Value Decomposition (SVD) approach is proposed for the classification of four lower-limb motions using a single-channel EMG signal from the muscle group of vastus medialis. Based on lower-limb motions from all subjects, the combination of five-level wavelet decomposition and SVD is used to comprise the feature vector. The Support Vector Machine (SVM) is then configured to build a multiple-subject classifier for which the subject independent accuracy will be given across all subjects for the classification of four types of lower-limb motions. In order to effectively indicate the classification performance, EMG features from time-domain (e.g., Mean Absolute Value (MAV), Root-Mean-Square (RMS), integrated EMG (iEMG), Zero Crossing (ZC)) and frequency-domain (e.g., Mean Frequency (MNF) and Median Frequency (MDF)) are also used to classify lower-limb motions. The five-fold cross validation is performed and it repeats fifty times in order to acquire the robust subject independent accuracy. Results show that the proposed WT-based SVD approach has the classification accuracy of 91.85%±0.88% which outperforms other feature models.

Lumbar disc nomenclature: version 2.0: recommendations of the combined task forces of the North American Spine Society, the American Society of Spine Radiology, and the American Society of Neuroradiology.

PubMed

Fardon, David F; Williams, Alan L; Dohring, Edward J; Murtagh, F Reed; Gabriel Rothman, Stephen L; Sze, Gordon K

2014-11-15

This article comprises a review of the literature pertaining to the normal and pathological lumbar disc and the compilation of a standardized nomenclature. To provide a resource that promotes a clear understanding of lumbar disc terminology among clinicians, radiologists, and researchers. The article "Nomenclature and Classification of Lumbar Disc Pathology. Recommendations of the Combined Task Forces of the North American Spine Society, American Society of Spine Radiology and American Society of Neuroradiology" was published in 2001 in Spine © Lippincott, Williams and Wilkins and formally endorsed by the 3 boards. Its purpose, which it served for well over a decade, was to promote greater clarity and consistency of usage of spine terminology. Since 2001, there has been sufficient evolution in our understanding of the lumbar disc to suggest the need for revision and updating. The document represents the consensus recommendations of the current combined task forces and reflects changes consistent with current concepts in radiological and clinical care. A PubMed search was performed for literature pertaining to the lumbar disc. The task force members individually and collectively reviewed the literature and revised the 2001 document. It was then reviewed by the governing boards of the American Society of Spine Radiology, the American Society of Neuroradiology, and the North American Spine Society. After further revision based on their feedback, the paper was approved for publication. The article provides a discussion of the recommended diagnostic categories and a glossary of terms pertaining to the lumbar disc, a detailed discussion of the terms and their recommended usage, as well as updated illustrations and literature references. We have revised and updated a document that, since 2001, has provided a widely accepted nomenclature that helps maintain consistency and accuracy in the description of the properties of the normal and abnormal lumbar discs and that serves as a system for classification and reporting built upon that nomenclature.

Employing the International Classification of Functioning, Disability and Health framework to capture user feedback in the design and testing stage of development of home-based arm rehabilitation technology.

PubMed

Sivan, Manoj; Gallagher, Justin; Holt, Ray; Weightman, Andrew; O'Connor, Rory; Levesley, Martin

2016-01-01

The purpose of this study was to evaluate the International Classification of Functioning, Disability and Health (ICF) as a framework to ensure that key aspects of user feedback are identified in the design and testing stages of development of a home-based upper limb rehabilitation system. Seventeen stroke survivors with residual upper limb weakness, and seven healthcare professionals with expertise in stroke rehabilitation, were enrolled in the user-centered design process. Through semi-structured interviews, they provided feedback on the hardware, software and impact of a home-based rehabilitation device to facilitate self-managed arm exercise. Members of the multidisciplinary clinical and engineering research team, based on previous experience and existing literature in user-centred design, developed the topic list for the interviews. Meaningful concepts were extracted from participants' interviews based on existing ICF linking rules and matched to categories within the ICF Comprehensive Core Set for stroke. Most of the interview concepts (except personal factors) matched the existing ICF Comprehensive Core Set categories. Personal factors that emerged from interviews e.g. gender, age, interest, compliance, motivation, choice and convenience that might determine device usability are yet to be categorised within the ICF framework and hence could not be matched to a specific Core Set category.

A newly developed tool for classifying study designs in systematic reviews of interventions and exposures showed substantial reliability and validity.

PubMed

Seo, Hyun-Ju; Kim, Soo Young; Lee, Yoon Jae; Jang, Bo-Hyoung; Park, Ji-Eun; Sheen, Seung-Soo; Hahn, Seo Kyung

2016-02-01

To develop a study Design Algorithm for Medical Literature on Intervention (DAMI) and test its interrater reliability, construct validity, and ease of use. We developed and then revised the DAMI to include detailed instructions. To test the DAMI's reliability, we used a purposive sample of 134 primary, mainly nonrandomized studies. We then compared the study designs as classified by the original authors and through the DAMI. Unweighted kappa statistics were computed to test interrater reliability and construct validity based on the level of agreement between the original and DAMI classifications. Assessment time was also recorded to evaluate ease of use. The DAMI includes 13 study designs, including experimental and observational studies of interventions and exposure. Both the interrater reliability (unweighted kappa = 0.67; 95% CI [0.64-0.75]) and construct validity (unweighted kappa = 0.63, 95% CI [0.52-0.67]) were substantial. Mean classification time using the DAMI was 4.08 ± 2.44 minutes (range, 0.51-10.92). The DAMI showed substantial interrater reliability and construct validity. Furthermore, given its ease of use, it could be used to accurately classify medical literature for systematic reviews of interventions although minimizing disagreement between authors of such reviews. Copyright © 2016 Elsevier Inc. All rights reserved.

A Systematic Literature Mapping of Risk Analysis of Big Data in Cloud Computing Environment

NASA Astrophysics Data System (ADS)

Bee Yusof Ali, Hazirah; Marziana Abdullah, Lili; Kartiwi, Mira; Nordin, Azlin; Salleh, Norsaremah; Sham Awang Abu Bakar, Normi

2018-05-01

This paper investigates previous literature that focusses on the three elements: risk assessment, big data and cloud. We use a systematic literature mapping method to search for journals and proceedings. The systematic literature mapping process is utilized to get a properly screened and focused literature. With the help of inclusion and exclusion criteria, the search of literature is further narrowed. Classification helps us in grouping the literature into categories. At the end of the mapping, gaps can be seen. The gap is where our focus should be in analysing risk of big data in cloud computing environment. Thus, a framework of how to assess the risk of security, privacy and trust associated with big data and cloud computing environment is highly needed.

Laundry detergent pod ingestions: is there a need for endoscopy?

PubMed

Smith, Erika; Liebelt, Erica; Nogueira, Jan

2014-09-01

Laundry detergent pod (LDP) exposures in children have resulted in several referrals to the emergency department. Signs and symptoms can include gastrointestinal symptoms (vomiting, drooling), neurological symptoms (depressed sensorium), or metabolic changes (lactic acidosis). There is limited literature on esophageal injury following LDP ingestions. We reviewed three cases of pediatric LDP ingestions that underwent an upper endoscopy in a tertiary care pediatric hospital. All of our patients were younger than 3 years old. The upper endoscopies revealed superficial esophageal erosions in two patients and erythema in the other. None of the patients had oral burns. Two of them developed swallowing dysfunction. Follow-up upper GI studies were normal. Our three patients ingested laundry detergent pods and all of them developed some degree of esophageal injury despite the absence of oral erythema, ulcers, or swelling. A review of literature suggests LDP exposures are more severe than non-pod detergents. Reasons as to why this may be remain unclear, although investigation into the ingredients and mode of delivery may help us to better understand. In a literature review, no esophageal strictures have been reported after LDP ingestion. We reviewed esophageal injury classification systems in an attempt to predict who may be at greatest risk for stricture based on initial findings. Our case series demonstrates it is hard to predict esophageal injury based on signs and symptoms. Based on a literature review, long-term esophageal stricture is unlikely, but if gastrointestinal symptoms persist, it is reasonable to evaluate with an upper endoscopy. Larger studies are needed.

Behavior genetics of personality disorders: informing classification and conceptualization in DSM-5.

PubMed

South, Susan C; DeYoung, Nathaniel J

2013-07-01

Personality pathology is currently captured in the Diagnostic and Statistical Manual through 10 categorical personality disorder (PD) diagnoses grouped into three descriptive clusters. This classification system has been criticized by many for using discrete categories and arbitrary thresholds when making clinical decisions. To address these critiques, the DSM-5 Personality and Personality Disorders Work Group has put forth a proposal that significantly alters the structure and content of the DSM-IV PD section. If this DSM-5 Work Group has conducted its own systematic review of the empirical literature, this review has not been released or made widely available. As such, it is up to the psychology community at large to determine how well the suggested changes align with findings from extant PD research. The current article joins this effort by addressing the contribution of behavior genetic findings to the revision process for classification of PDs in DSM-5. First, we provide a brief review of the history of PD classification in the DSM. Next, we present an overview and rationale for each of the five major suggested changes to PD diagnoses. For each suggested change, we outline the available evidence from behavior genetics and interpretations of these findings. Finally, we offer a summary of considerations for PD classification as the DSM-5 moves forward. Review of the behavior genetics literature suggests that several features of the DSM-5 proposal, including the elimination of 4 PDs, merging clinical disorders and PDs on a single axis, and the implementation of a trait rating system, require significantly greater explication before a product is finalized.

A global view of shifting cultivation: Recent, current, and future extent

PubMed Central

Mertz, Ole; Frolking, Steve; Egelund Christensen, Andreas; Hurni, Kaspar; Sedano, Fernando; Parsons Chini, Louise; Sahajpal, Ritvik; Hansen, Matthew; Hurtt, George

2017-01-01

Mosaic landscapes under shifting cultivation, with their dynamic mix of managed and natural land covers, often fall through the cracks in remote sensing–based land cover and land use classifications, as these are unable to adequately capture such landscapes’ dynamic nature and complex spectral and spatial signatures. But information about such landscapes is urgently needed to improve the outcomes of global earth system modelling and large-scale carbon and greenhouse gas accounting. This study combines existing global Landsat-based deforestation data covering the years 2000 to 2014 with very high-resolution satellite imagery to visually detect the specific spatio-temporal pattern of shifting cultivation at a one-degree cell resolution worldwide. The accuracy levels of our classification were high with an overall accuracy above 87%. We estimate the current global extent of shifting cultivation and compare it to other current global mapping endeavors as well as results of literature searches. Based on an expert survey, we make a first attempt at estimating past trends as well as possible future trends in the global distribution of shifting cultivation until the end of the 21st century. With 62% of the investigated one-degree cells in the humid and sub-humid tropics currently showing signs of shifting cultivation—the majority in the Americas (41%) and Africa (37%)—this form of cultivation remains widespread, and it would be wrong to speak of its general global demise in the last decades. We estimate that shifting cultivation landscapes currently cover roughly 280 million hectares worldwide, including both cultivated fields and fallows. While only an approximation, this estimate is clearly smaller than the areas mentioned in the literature which range up to 1,000 million hectares. Based on our expert survey and historical trends we estimate a possible strong decrease in shifting cultivation over the next decades, raising issues of livelihood security and resilience among people currently depending on shifting cultivation. PMID:28886132

A global view of shifting cultivation: Recent, current, and future extent

DOE Office of Scientific and Technical Information (OSTI.GOV)

Heinimann, Andreas; Mertz, Ole; Frolking, Steve

Mosaic landscapes under shifting cultivation, with their dynamic mix of managed and natural land covers, often fall through the cracks in remote sensing-based land cover and land use classifications, as these are unable to adequately capture such landscapes' dynamic nature and complex spectral and spatial signatures. But information about such landscapes is urgently needed to improve the outcomes of global earth system modelling and large-scale carbon and greenhouse gas accounting. This study combines existing global Landsat-based deforestation data covering the years 2000 to 2014 with very high-resolution satellite imagery to visually detect the specific spatio-temporal pattern of shifting cultivation atmore » a one-degree cell resolution worldwide. The accuracy levels of our classification were high with an overall accuracy above 87%. We estimate the current global extent of shifting cultivation and compare it to other current global mapping endeavors as well as results of literature searches. Based on an expert survey, we make a first attempt at estimating past trends as well as possible future trends in the global distribution of shifting cultivation until the end of the 21 st century. With 62% of the investigated one-degree cells in the humid and sub-humid tropics currently showing signs of shifting cultivation$-$the majority in the Americas (41%) and Africa (37%)$-$this form of cultivation remains widespread, and it would be wrong to speak of its general global demise in the last decades. We estimate that shifting cultivation landscapes currently cover roughly 280 million hectares worldwide, including both cultivated fields and fallows. While only an approximation, this estimate is clearly smaller than the areas mentioned in the literature which range up to 1,000 million hectares. Based on our expert survey and historical trends we estimate a possible strong decrease in shifting cultivation over the next decades, raising issues of livelihood security and resilience among people currently depending on shifting cultivation.« less

A global view of shifting cultivation: Recent, current, and future extent

DOE PAGES

Heinimann, Andreas; Mertz, Ole; Frolking, Steve; ...

2017-09-08

Mosaic landscapes under shifting cultivation, with their dynamic mix of managed and natural land covers, often fall through the cracks in remote sensing-based land cover and land use classifications, as these are unable to adequately capture such landscapes' dynamic nature and complex spectral and spatial signatures. But information about such landscapes is urgently needed to improve the outcomes of global earth system modelling and large-scale carbon and greenhouse gas accounting. This study combines existing global Landsat-based deforestation data covering the years 2000 to 2014 with very high-resolution satellite imagery to visually detect the specific spatio-temporal pattern of shifting cultivation atmore » a one-degree cell resolution worldwide. The accuracy levels of our classification were high with an overall accuracy above 87%. We estimate the current global extent of shifting cultivation and compare it to other current global mapping endeavors as well as results of literature searches. Based on an expert survey, we make a first attempt at estimating past trends as well as possible future trends in the global distribution of shifting cultivation until the end of the 21 st century. With 62% of the investigated one-degree cells in the humid and sub-humid tropics currently showing signs of shifting cultivation$-$the majority in the Americas (41%) and Africa (37%)$-$this form of cultivation remains widespread, and it would be wrong to speak of its general global demise in the last decades. We estimate that shifting cultivation landscapes currently cover roughly 280 million hectares worldwide, including both cultivated fields and fallows. While only an approximation, this estimate is clearly smaller than the areas mentioned in the literature which range up to 1,000 million hectares. Based on our expert survey and historical trends we estimate a possible strong decrease in shifting cultivation over the next decades, raising issues of livelihood security and resilience among people currently depending on shifting cultivation.« less

Effects of gross motor function and manual function levels on performance-based ADL motor skills of children with spastic cerebral palsy.

PubMed

Park, Myoung-Ok

2017-02-01

[Purpose] The purpose of this study was to determine effects of Gross Motor Function Classification System and Manual Ability Classification System levels on performance-based motor skills of children with spastic cerebral palsy. [Subjects and Methods] Twenty-three children with cerebral palsy were included. The Assessment of Motor and Process Skills was used to evaluate performance-based motor skills in daily life. Gross motor function was assessed using Gross Motor Function Classification Systems, and manual function was measured using the Manual Ability Classification System. [Results] Motor skills in daily activities were significantly different on Gross Motor Function Classification System level and Manual Ability Classification System level. According to the results of multiple regression analysis, children categorized as Gross Motor Function Classification System level III scored lower in terms of performance based motor skills than Gross Motor Function Classification System level I children. Also, when analyzed with respect to Manual Ability Classification System level, level II was lower than level I, and level III was lower than level II in terms of performance based motor skills. [Conclusion] The results of this study indicate that performance-based motor skills differ among children categorized based on Gross Motor Function Classification System and Manual Ability Classification System levels of cerebral palsy.

Exclusive endoscopic resection of juvenile nasopharyngeal angiofibroma: a systematic review of the literature.

PubMed

Khoueir, Nadim; Nicolas, Nicolas; Rohayem, Ziad; Haddad, Amine; Abou Hamad, Walid

2014-03-01

To systematically review the exclusive endoscopic treatment of juvenile nasopharyngeal angiofibroma in the literature to define the clinical features in terms of staging and the treatment outcomes in terms of bleeding, recurrence, residual tumor, and complications. Online databases, including PubMed and EMBASE, were used. Reference sections of identified studies were examined for additional articles. The literature was searched by 2 reviewers with the following inclusion criteria: English or French language and exclusive endoscopic treatment of juvenile nasopharyngeal angiofibroma. We were only able to perform a meta-analysis on the categorical outcomes using DerSimonian and Laird random effects models. Ninety-two studies were included with a majority of retrospective studies (54/92; 58.6%). No randomized controlled trials were found. A total of 821 patients were identified. The Radowski classification was the most commonly used (29/92; 31.15%). The mean operative blood loss was 564.21 mL (minimum, 20 mL; maximum, 1482 mL). It was 414.6 mL (minimum, 20 mL; maximum, 1000 mL) and 774.2 mL (minimum, 228 mL; maximum, 1482 mL), respectively, in the group with and without embolization. No conclusion could be made because it was not stratified by tumor stage and because of the absence of randomized controlled trials. The random effect estimate of recurrence was 10% (95% confidence interval [CI], 8.3-11.7). It was 9.3% (95% CI, 7.2-11.5) for complications and 7.7% (95% CI, 5.4-10.1) for residual tumor. The endoscopic treatment is an evolving modality. It is considered today the treatment of choice. A new classification system based on the endoscopic approach should be proposed in future studies.

Evaluation of the mechanism and principles of management of temporomandibular joint dislocation. Systematic review of literature and a proposed new classification of temporomandibular joint dislocation

PubMed Central

2011-01-01

Background Virtually all the articles in literature addressed only a specific type of dislocation. The aim of this review was to project a comprehensive understanding of the pathologic processes and management of all types of dislodgement of the head of the mandibular condyle from its normal position in the glenoid fossa. In addition, a new classification of temporomandibular joint dislocation was also proposed. Method and materials A thorough computer literature search was done using the Medline, Cochrane library and Embase database. Key words like temporo-mandibular joint dislocation were used for the search. Additional manual search was done by going through published home-based and foreign articles. Case reports/series, and original articles that documented the type of dislocation, number of cases treated in the series and original articles. Treatment done and outcome of treatment were included in the study. Result A total of 128 articles were reviewed out which 79 were found relevant. Of these, 26 were case reports, 17 were case series and 36 were original articles. 79 cases were acute dislocations, 35 cases were chronic protracted TMJ dislocations and 311 cases were chronic recurrent TMJ dislocations. Etiology was predominantly trauma in 60% of cases and other causes contributed about 40%. Of all the cases reviewed, only 4 were unilateral dislocation. Various treatment modalities are outlined in this report as indicated for each type of dislocation. Conclusion The more complex and invasive method of treatment may not necessarily offer the best option and outcome of treatment, therefore conservative approaches should be exhausted and utilized appropriately before adopting the more invasive surgical techniques. PMID:21676208

Evaluation of the mechanism and principles of management of temporomandibular joint dislocation. Systematic review of literature and a proposed new classification of temporomandibular joint dislocation.

PubMed

Akinbami, Babatunde O

2011-06-15

Virtually all the articles in literature addressed only a specific type of dislocation. The aim of this review was to project a comprehensive understanding of the pathologic processes and management of all types of dislodgement of the head of the mandibular condyle from its normal position in the glenoid fossa. In addition, a new classification of temporomandibular joint dislocation was also proposed. A thorough computer literature search was done using the Medline, Cochrane library and Embase database. Key words like temporo-mandibular joint dislocation were used for the search. Additional manual search was done by going through published home-based and foreign articles. Case reports/series, and original articles that documented the type of dislocation, number of cases treated in the series and original articles. Treatment done and outcome of treatment were included in the study. A total of 128 articles were reviewed out which 79 were found relevant. Of these, 26 were case reports, 17 were case series and 36 were original articles. 79 cases were acute dislocations, 35 cases were chronic protracted TMJ dislocations and 311 cases were chronic recurrent TMJ dislocations. Etiology was predominantly trauma in 60% of cases and other causes contributed about 40%. Of all the cases reviewed, only 4 were unilateral dislocation. Various treatment modalities are outlined in this report as indicated for each type of dislocation. The more complex and invasive method of treatment may not necessarily offer the best option and outcome of treatment, therefore conservative approaches should be exhausted and utilized appropriately before adopting the more invasive surgical techniques.

Proposed Core Competencies and Empirical Validation Procedure in Competency Modeling: Confirmation and Classification.

PubMed

Baczyńska, Anna K; Rowiński, Tomasz; Cybis, Natalia

2016-01-01

Competency models provide insight into key skills which are common to many positions in an organization. Moreover, there is a range of competencies that is used by many companies. Researchers have developed core competency terminology to underline their cross-organizational value. The article presents a theoretical model of core competencies consisting of two main higher-order competencies called performance and entrepreneurship. Each of them consists of three elements: the performance competency includes cooperation, organization of work and goal orientation, while entrepreneurship includes innovativeness, calculated risk-taking and pro-activeness. However, there is lack of empirical validation of competency concepts in organizations and this would seem crucial for obtaining reliable results from organizational research. We propose a two-step empirical validation procedure: (1) confirmation factor analysis, and (2) classification of employees. The sample consisted of 636 respondents (M = 44.5; SD = 15.1). Participants were administered a questionnaire developed for the study purpose. The reliability, measured by Cronbach's alpha, ranged from 0.60 to 0.83 for six scales. Next, we tested the model using a confirmatory factor analysis. The two separate, single models of performance and entrepreneurial orientations fit quite well to the data, while a complex model based on the two single concepts needs further research. In the classification of employees based on the two higher order competencies we obtained four main groups of employees. Their profiles relate to those found in the literature, including so-called niche finders and top performers. Some proposal for organizations is discussed.

An Ecological Framework for Monitoring Sustainable Management of Wildlife: A New Mexico Furbearer Example.

DTIC Science & Technology

1996-09-01

Understanding use relative to availability is necessary to manage wildlife harvest sustainably. We used ecological zones ( ecozones ) as a framework...ecological classification scheme, reviewed technical literature mapped species distribution among ecozones , assessed harvest, estimated sustainable extraction...other wildlife. Technical literature review of 70 key words and species names identified 534 citations regarding furbearers in ecozones shared by New

Meta-Analysis of Human Factors Engineering Studies Comparing Individual Differences, Practice Effects and Equipment Design Variations.

DTIC Science & Technology

1985-02-21

Approvoid foT public 90Ieleol, 2* . tJni7nited " - . - o . - ’--. * . -... . 1 UNCLASSIFIED S, E CURITY CLASSIFICATION OF THIS PAGE-" REPORT DOCUMENTATION...ACCESSION NO. 11. TITLE (Include Security Classification) . Veta -Analysis of Human Factors Engineering Studies Comparing Individual Differences, Practice...Background C Opportunity D Significance E History III. PHASE I FINAL REPORT A Literature Review B Formal Analysis C Results D Implications for Phase II IV

Analysis of classifiers performance for classification of potential microcalcification

NASA Astrophysics Data System (ADS)

M. N., Arun K.; Sheshadri, H. S.

2013-07-01

Breast cancer is a significant public health problem in the world. According to the literature early detection improve breast cancer prognosis. Mammography is a screening tool used for early detection of breast cancer. About 10-30% cases are missed during the routine check as it is difficult for the radiologists to make accurate analysis due to large amount of data. The Microcalcifications (MCs) are considered to be important signs of breast cancer. It has been reported in literature that 30% - 50% of breast cancer detected radio graphically show MCs on mammograms. Histologic examinations report 62% to 79% of breast carcinomas reveals MCs. MC are tiny, vary in size, shape, and distribution, and MC may be closely connected to surrounding tissues. There is a major challenge using the traditional classifiers in the classification of individual potential MCs as the processing of mammograms in appropriate stage generates data sets with an unequal amount of information for both classes (i.e., MC, and Not-MC). Most of the existing state-of-the-art classification approaches are well developed by assuming the underlying training set is evenly distributed. However, they are faced with a severe bias problem when the training set is highly imbalanced in distribution. This paper addresses this issue by using classifiers which handle the imbalanced data sets. In this paper, we also compare the performance of classifiers which are used in the classification of potential MC.

Loneliness, social isolation and social relationships: what are we measuring? A novel framework for classifying and comparing tools

PubMed Central

Kanaan, Mona; Gilbody, Simon; Hanratty, Barbara

2016-01-01

Objectives We present a novel way of classifying and comparing measures of social relationships to help readers interpret the growing literature on loneliness and social isolation and to provide researchers with a starting point to guide their choice of measuring tool. Methods Measures of social relationships used in epidemiological studies were identified from two systematic reviews—one review on the association between social relationships and health and social care service use, and a second review on the association between social relationships and health. Questions from each measure were retrieved and tabulated to derive a classification of social relationship measures. Results We present a classification of measures according to two dimensions: (1) whether instruments cover structural or functional aspects of social relationships and (2) the degree of subjectivity asked of respondents. We explain how this classification can be used to clarify the remit of the many questionnaires used in the literature and to compare them. Conclusions Different dimensions of social relationships are likely to have different implications for health. Our classification of social relationship measures transcends disciplinary and conceptual boundaries, allowing researchers to compare tools that developed from different theoretical perspectives. Careful choice of measures is essential to further our understanding of the links between social relationships and health, to identify people in need of help and to design appropriate prevention and intervention strategies. PMID:27091822

Limb length inequality: clinical implications for assessment and intervention.

PubMed

Brady, Rebecca J; Dean, John B; Skinner, T Marc; Gross, Michael T

2003-05-01

The purpose of this paper is to review relevant literature concerning limb length inequalities in adults and to make recommendations for assessment and intervention based on the literature and our own clinical experience. Literature searches were conducted in the MEDLINE, PubMed, and CINAHL databases. Limb length inequality and common classification criteria are defined and etiological factors are presented. Common methods of detecting limb length inequality include direct (tape measure methods), indirect (pelvic leveling), and radiological techniques. Interventions include shoe inserts or external shoe lift therapy for mild cases. Surgery may be appropriate in severe cases. Little agreement exists regarding the prevalence of limb length inequality, the degree of limb length inequality that is considered clinically significant, and the reliability and validity of assessment methods. Based on correlational studies, the relationship between limb length inequality and orthopaedic pathologies is questionable. Stronger support for the link between low back pain (LBP) and limb length inequality is provided by intervention studies. Methods involving palpation of pelvic landmarks with block correction have the most support for clinical assessment of limb length inequality. Standing radiographs are suggested when clinical assessment methods are unsatisfactory. Clinicians should exercise caution when undertaking intervention strategies for limb length inequality of less than 5 mm when limb length inequality has been identified with clinical techniques. Recommendations are provided regarding intervention strategies.

The generalization ability of online SVM classification based on Markov sampling.

PubMed

Xu, Jie; Yan Tang, Yuan; Zou, Bin; Xu, Zongben; Li, Luoqing; Lu, Yang

2015-03-01

In this paper, we consider online support vector machine (SVM) classification learning algorithms with uniformly ergodic Markov chain (u.e.M.c.) samples. We establish the bound on the misclassification error of an online SVM classification algorithm with u.e.M.c. samples based on reproducing kernel Hilbert spaces and obtain a satisfactory convergence rate. We also introduce a novel online SVM classification algorithm based on Markov sampling, and present the numerical studies on the learning ability of online SVM classification based on Markov sampling for benchmark repository. The numerical studies show that the learning performance of the online SVM classification algorithm based on Markov sampling is better than that of classical online SVM classification based on random sampling as the size of training samples is larger.

Multi-objective evolutionary algorithms for fuzzy classification in survival prediction.

PubMed

Jiménez, Fernando; Sánchez, Gracia; Juárez, José M

2014-03-01

This paper presents a novel rule-based fuzzy classification methodology for survival/mortality prediction in severe burnt patients. Due to the ethical aspects involved in this medical scenario, physicians tend not to accept a computer-based evaluation unless they understand why and how such a recommendation is given. Therefore, any fuzzy classifier model must be both accurate and interpretable. The proposed methodology is a three-step process: (1) multi-objective constrained optimization of a patient's data set, using Pareto-based elitist multi-objective evolutionary algorithms to maximize accuracy and minimize the complexity (number of rules) of classifiers, subject to interpretability constraints; this step produces a set of alternative (Pareto) classifiers; (2) linguistic labeling, which assigns a linguistic label to each fuzzy set of the classifiers; this step is essential to the interpretability of the classifiers; (3) decision making, whereby a classifier is chosen, if it is satisfactory, according to the preferences of the decision maker. If no classifier is satisfactory for the decision maker, the process starts again in step (1) with a different input parameter set. The performance of three multi-objective evolutionary algorithms, niched pre-selection multi-objective algorithm, elitist Pareto-based multi-objective evolutionary algorithm for diversity reinforcement (ENORA) and the non-dominated sorting genetic algorithm (NSGA-II), was tested using a patient's data set from an intensive care burn unit and a standard machine learning data set from an standard machine learning repository. The results are compared using the hypervolume multi-objective metric. Besides, the results have been compared with other non-evolutionary techniques and validated with a multi-objective cross-validation technique. Our proposal improves the classification rate obtained by other non-evolutionary techniques (decision trees, artificial neural networks, Naive Bayes, and case-based reasoning) obtaining with ENORA a classification rate of 0.9298, specificity of 0.9385, and sensitivity of 0.9364, with 14.2 interpretable fuzzy rules on average. Our proposal improves the accuracy and interpretability of the classifiers, compared with other non-evolutionary techniques. We also conclude that ENORA outperforms niched pre-selection and NSGA-II algorithms. Moreover, given that our multi-objective evolutionary methodology is non-combinational based on real parameter optimization, the time cost is significantly reduced compared with other evolutionary approaches existing in literature based on combinational optimization. Copyright © 2014 Elsevier B.V. All rights reserved.

Business model framework applications in health care: A systematic review.

PubMed

Fredriksson, Jens Jacob; Mazzocato, Pamela; Muhammed, Rafiq; Savage, Carl

2017-11-01

It has proven to be a challenge for health care organizations to achieve the Triple Aim. In the business literature, business model frameworks have been used to understand how organizations are aligned to achieve their goals. We conducted a systematic literature review with an explanatory synthesis approach to understand how business model frameworks have been applied in health care. We found a large increase in applications of business model frameworks during the last decade. E-health was the most common context of application. We identified six applications of business model frameworks: business model description, financial assessment, classification based on pre-defined typologies, business model analysis, development, and evaluation. Our synthesis suggests that the choice of business model framework and constituent elements should be informed by the intent and context of application. We see a need for harmonization in the choice of elements in order to increase generalizability, simplify application, and help organizations realize the Triple Aim.

Sudden unexpected death from oligodendroglioma: a case report and review of the literature.

PubMed

Manousaki, Maria; Papadaki, Helen; Papavdi, Asteria; Kranioti, Elena F; Mylonakis, Panagiotis; Varakis, John; Michalodimitrakis, Manolis

2011-12-01

Sudden and unexpected deaths due to asymptomatic 5 primary brain tumors are extremely rare, with an incidence that ranges from 0.16 to 3.2%. Usually, such tumors are glioblastomas or, less commonly, astrocytomas. Asymptomatic oligodendrogliomas causing sudden death are hardly ever reported among medico-legal investigated cases.We report a rare case of sudden and unexpected death from a previously asymptomatic and undiagnosed, well-differentiated, grade II oligodendrogloioma (WHO classification). According to the autopsy and the microscopic findings brain edema as a result of obstruction of the cerebrospinal fluid flow due to hemorrhagic leakage of the oligodendroglioma is incriminated as the most probable physiopathological mechanism for the sudden death. Diagnosis is mainly based on the special microscopic features of the tumor cells (typical "fried-egg" appearance), interrupted by a dense network of branching capillaries. We discuss further the pathophysiological mechanisms of death and present a short review of literature.

Outcomes of physical therapy, speech pathology, and occupational therapy for people with motor neuron disease: a systematic review.

PubMed

Morris, Meg E; Perry, Alison; Bilney, Belinda; Curran, Andrea; Dodd, Karen; Wittwer, Joanne E; Dalton, Gregory W

2006-09-01

This article describes a systematic review and critical evaluation of the international literature on the effects of physical therapy, speech pathology, and occupational therapy for people with motor neuron disease (PwMND). The results were interpreted using the framework of the International Classification of Functioning, Disability and Health. This enabled us to summarize therapy outcomes at the level of body structure and function, activity limitations, participation restrictions, and quality of life. Databases searched included MEDLINE, PUBMED, CINAHL, PSYCInfo, Data base of Abstracts of Reviews of Effectiveness (DARE), The Physiotherapy Evidence data base (PEDro), Evidence Based Medicine Reviews (EMBASE), the Cochrane database of systematic reviews, and the Cochrane Controlled Trials Register. Evidence was graded according to the Harbour and Miller classification. Most of the evidence was found to be at the level of "clinical opinion" rather than of controlled clinical trials. Several nonrandomized small group and "observational studies" provided low-level evidence to support physical therapy for improving muscle strength and pulmonary function. There was also some evidence to support the effectiveness of speech pathology interventions for dysarthria. The search identified a small number of studies on occupational therapy for PwMND, which were small, noncontrolled pre-post-designs or clinical reports.

Acoustic surface perception from naturally occurring step sounds of a dexterous hexapod robot

NASA Astrophysics Data System (ADS)

Cuneyitoglu Ozkul, Mine; Saranli, Afsar; Yazicioglu, Yigit

2013-10-01

Legged robots that exhibit dynamic dexterity naturally interact with the surface to generate complex acoustic signals carrying rich information on the surface as well as the robot platform itself. However, the nature of a legged robot, which is a complex, hybrid dynamic system, renders the more common approach of model-based system identification impractical. The present paper focuses on acoustic surface identification and proposes a non-model-based analysis and classification approach adopted from the speech processing literature. A novel feature set composed of spectral band energies augmented by their vector time derivatives and time-domain averaged zero crossing rate is proposed. Using a multi-dimensional vector classifier, these features carry enough information to accurately classify a range of commonly occurring indoor and outdoor surfaces without using of any mechanical system model. A comparative experimental study is carried out and classification performance and computational complexity are characterized. Different feature combinations, classifiers and changes in critical design parameters are investigated. A realistic and representative acoustic data set is collected with the robot moving at different speeds on a number of surfaces. The study demonstrates promising performance of this non-model-based approach, even in an acoustically uncontrolled environment. The approach also has good chance of performing in real-time.

Brittleness of twig bases in the genus Salix: fracture mechanics and ecological relevance.

PubMed

Beismann, H; Wilhelmi, H; Baillères, H; Spatz, H C; Bogenrieder, A; Speck, T

2000-03-01

The twig bases within the genus Salix were investigated. Brittleness of twig bases as defined in the literature neither correlates with Young's modulus nor with growth strains, which were measured for S. alba, S. fragilis and S. x rubens. For the species S. alba, S. appendiculata, S. eleagnos, S. fragilis, S. purpurea, S. triandra, S. viminalis, and S. x rubens, fracture surfaces of broken twigs were investigated and semiquantitatively described in terms of 'relative roughness' (ratio of rough area of fracture surface over whole area of fracture surface). The relative roughness clearly corresponds with the classification into brittle and nonbrittle species given in the literature. An attempt was made to quantify brittleness with mechanical tests. The absolute values of stress and strain do not correlate with the brittleness of the twig bases as defined by the relative roughness. However, the 'index stress' (ratio of stress at yield over stress at fracture) or the 'index strain' (ratio of strain at yield over strain at fracture), correlate well with the relative roughness. The graphic analysis of index stress against index strain reveals a straight line on which the eight species are ordered according to their brittleness. Depending on growth form and habitat, brittle twig bases of willows may function ecologically as mechanical safety mechanisms and, additionally, as a propagation mechanism.

A nearest neighbor approach for automated transporter prediction and categorization from protein sequences.

PubMed

Li, Haiquan; Dai, Xinbin; Zhao, Xuechun

2008-05-01

Membrane transport proteins play a crucial role in the import and export of ions, small molecules or macromolecules across biological membranes. Currently, there are a limited number of published computational tools which enable the systematic discovery and categorization of transporters prior to costly experimental validation. To approach this problem, we utilized a nearest neighbor method which seamlessly integrates homologous search and topological analysis into a machine-learning framework. Our approach satisfactorily distinguished 484 transporter families in the Transporter Classification Database, a curated and representative database for transporters. A five-fold cross-validation on the database achieved a positive classification rate of 72.3% on average. Furthermore, this method successfully detected transporters in seven model and four non-model organisms, ranging from archaean to mammalian species. A preliminary literature-based validation has cross-validated 65.8% of our predictions on the 11 organisms, including 55.9% of our predictions overlapping with 83.6% of the predicted transporters in TransportDB.

A vectorial semantics approach to personality assessment.

PubMed

Neuman, Yair; Cohen, Yochai

2014-04-23

Personality assessment and, specifically, the assessment of personality disorders have traditionally been indifferent to computational models. Computational personality is a new field that involves the automatic classification of individuals' personality traits that can be compared against gold-standard labels. In this context, we introduce a new vectorial semantics approach to personality assessment, which involves the construction of vectors representing personality dimensions and disorders, and the automatic measurements of the similarity between these vectors and texts written by human subjects. We evaluated our approach by using a corpus of 2468 essays written by students who were also assessed through the five-factor personality model. To validate our approach, we measured the similarity between the essays and the personality vectors to produce personality disorder scores. These scores and their correspondence with the subjects' classification of the five personality factors reproduce patterns well-documented in the psychological literature. In addition, we show that, based on the personality vectors, we can predict each of the five personality factors with high accuracy.

DIMETER: A Haptic Master Device for Tremor Diagnosis in Neurodegenerative Diseases

PubMed Central

González, Roberto; Barrientos, Antonio; del Cerro, Jaime; Coca, Benito

2014-01-01

In this study, a device based on patient motion capture is developed for the reliable and non-invasive diagnosis of neurodegenerative diseases. The primary objective of this study is the classification of differential diagnosis between Parkinson's disease (PD) and essential tremor (ET). The DIMETER system has been used in the diagnoses of a significant number of patients at two medical centers in Spain. Research studies on classification have primarily focused on the use of well-known and reliable diagnosis criteria developed by qualified personnel. Here, we first present a literature review of the methods used to detect and evaluate tremor; then, we describe the DIMETER device in terms of the software and hardware used and the battery of tests developed to obtain the best diagnoses. All of the tests are classified and described in terms of the characteristics of the data obtained. A list of parameters obtained from the tests is provided, and the results obtained using multilayer perceptron (MLP) neural networks are presented and analyzed. PMID:24608001

A Vectorial Semantics Approach to Personality Assessment

NASA Astrophysics Data System (ADS)

Neuman, Yair; Cohen, Yochai

2014-04-01

Personality assessment and, specifically, the assessment of personality disorders have traditionally been indifferent to computational models. Computational personality is a new field that involves the automatic classification of individuals' personality traits that can be compared against gold-standard labels. In this context, we introduce a new vectorial semantics approach to personality assessment, which involves the construction of vectors representing personality dimensions and disorders, and the automatic measurements of the similarity between these vectors and texts written by human subjects. We evaluated our approach by using a corpus of 2468 essays written by students who were also assessed through the five-factor personality model. To validate our approach, we measured the similarity between the essays and the personality vectors to produce personality disorder scores. These scores and their correspondence with the subjects' classification of the five personality factors reproduce patterns well-documented in the psychological literature. In addition, we show that, based on the personality vectors, we can predict each of the five personality factors with high accuracy.

Land use change and effects on water quality and ecosystem health in the Lake Tahoe basin, Nevada and California: year-1 progress

USGS Publications Warehouse

Forney, William; Raumann, Christian G.; Minor, T.B.; Smith, J. LaRue; Vogel, John; Vitales, Robert

2002-01-01

As part of the requirements for the Geographic Research and Applications Prospectus grants, this Open-File Report is the second of two that resulted from the first year of the project. The first Open-File Report (OFR 01-418) introduced the project, reviewed the existing body of literature, and outlined the research approach. This document will present an update of the research approach and offer some preliminary results from multiple efforts, specifically, the production of historical digital orthophoto quadrangles, the development of the land use/land cover (LULC) classification system, the development of a temporal transportation layer, the classification of anthropogenic cover types from the IKONOS imagery, a preliminary evaluation of landscape ecology metrics (quantification of spatial and temporal patterns of ecosystem structure and function with appropriate indices) and their utility in comparing two LULC systems, and a new initiative in community-based science and facilitation.

A Vectorial Semantics Approach to Personality Assessment

PubMed Central

Neuman, Yair; Cohen, Yochai

2014-01-01

Personality assessment and, specifically, the assessment of personality disorders have traditionally been indifferent to computational models. Computational personality is a new field that involves the automatic classification of individuals' personality traits that can be compared against gold-standard labels. In this context, we introduce a new vectorial semantics approach to personality assessment, which involves the construction of vectors representing personality dimensions and disorders, and the automatic measurements of the similarity between these vectors and texts written by human subjects. We evaluated our approach by using a corpus of 2468 essays written by students who were also assessed through the five-factor personality model. To validate our approach, we measured the similarity between the essays and the personality vectors to produce personality disorder scores. These scores and their correspondence with the subjects' classification of the five personality factors reproduce patterns well-documented in the psychological literature. In addition, we show that, based on the personality vectors, we can predict each of the five personality factors with high accuracy. PMID:24755833

Management of thoracolumbar spine trauma: An overview

PubMed Central

Rajasekaran, S; Kanna, Rishi Mugesh; Shetty, Ajoy Prasad

2015-01-01

Thoracolumbar spine fractures are common injuries that can result in significant disability, deformity and neurological deficit. Controversies exist regarding the appropriate radiological investigations, the indications for surgical management and the timing, approach and type of surgery. This review provides an overview of the epidemiology, biomechanical principles, radiological and clinical evaluation, classification and management principles. Literature review of all relevant articles published in PubMed covering thoracolumbar spine fractures with or without neurologic deficit was performed. The search terms used were thoracolumbar, thoracic, lumbar, fracture, trauma and management. All relevant articles and abstracts covering thoracolumbar spine fractures with and without neurologic deficit were reviewed. Biomechanically the thoracolumbar spine is predisposed to a higher incidence of spinal injuries. Computed tomography provides adequate bony detail for assessing spinal stability while magnetic resonance imaging shows injuries to soft tissues (posterior ligamentous complex [PLC]) and neurological structures. Different classification systems exist and the most recent is the AO spine knowledge forum classification of thoracolumbar trauma. Treatment includes both nonoperative and operative methods and selected based on the degree of bony injury, neurological involvement, presence of associated injuries and the integrity of the PLC. Significant advances in imaging have helped in the better understanding of thoracolumbar fractures, including information on canal morphology and injury to soft tissue structures. The ideal classification that is simple, comprehensive and guides management is still elusive. Involvement of three columns, progressive neurological deficit, significant kyphosis and canal compromise with neurological deficit are accepted indications for surgical stabilization through anterior, posterior or combined approaches. PMID:25593358

Machine learning in infrared object classification - an all-sky selection of YSO candidates

NASA Astrophysics Data System (ADS)

Marton, Gabor; Zahorecz, Sarolta; Toth, L. Viktor; Magnus McGehee, Peregrine; Kun, Maria

2015-08-01

Object classification is a fundamental and challenging problem in the era of big data. I will discuss up-to-date methods and their application to classify infrared point sources.We analysed the ALLWISE catalogue, the most recent public source catalogue of the Wide-field Infrared Survey Explorer (WISE) to compile a reliable list of Young Stellar Object (YSO) candidates. We tested and compared classical and up-to-date statistical methods as well, to discriminate source types like extragalactic objects, evolved stars, main sequence stars, objects related to the interstellar medium and YSO candidates by using their mid-IR WISE properties and associated near-IR 2MASS data.In the particular classification problem the Support Vector Machines (SVM), a class of supervised learning algorithm turned out to be the best tool. As a result we classify Class I and II YSOs with >90% accuracy while the fraction of contaminating extragalactic objects remains well below 1%, based on the number of known objects listed in the SIMBAD and VizieR databases. We compare our results to other classification schemes from the literature and show that the SVM outperforms methods that apply linear cuts on the colour-colour and colour-magnitude space. Our homogenous YSO candidate catalog can serve as an excellent pathfinder for future detailed observations of individual objects and a starting point of statistical studies that aim to add pieces to the big picture of star formation theory.

Multimodal Neuroimaging: Basic Concepts and Classification of Neuropsychiatric Diseases.

PubMed

Tulay, Emine Elif; Metin, Barış; Tarhan, Nevzat; Arıkan, Mehmet Kemal

2018-06-01

Neuroimaging techniques are widely used in neuroscience to visualize neural activity, to improve our understanding of brain mechanisms, and to identify biomarkers-especially for psychiatric diseases; however, each neuroimaging technique has several limitations. These limitations led to the development of multimodal neuroimaging (MN), which combines data obtained from multiple neuroimaging techniques, such as electroencephalography, functional magnetic resonance imaging, and yields more detailed information about brain dynamics. There are several types of MN, including visual inspection, data integration, and data fusion. This literature review aimed to provide a brief summary and basic information about MN techniques (data fusion approaches in particular) and classification approaches. Data fusion approaches are generally categorized as asymmetric and symmetric. The present review focused exclusively on studies based on symmetric data fusion methods (data-driven methods), such as independent component analysis and principal component analysis. Machine learning techniques have recently been introduced for use in identifying diseases and biomarkers of disease. The machine learning technique most widely used by neuroscientists is classification-especially support vector machine classification. Several studies differentiated patients with psychiatric diseases and healthy controls with using combined datasets. The common conclusion among these studies is that the prediction of diseases increases when combining data via MN techniques; however, there remain a few challenges associated with MN, such as sample size. Perhaps in the future N-way fusion can be used to combine multiple neuroimaging techniques or nonimaging predictors (eg, cognitive ability) to overcome the limitations of MN.

Frequency Optimization for Enhancement of Surface Defect Classification Using the Eddy Current Technique

PubMed Central

Fan, Mengbao; Wang, Qi; Cao, Binghua; Ye, Bo; Sunny, Ali Imam; Tian, Guiyun

2016-01-01

Eddy current testing is quite a popular non-contact and cost-effective method for nondestructive evaluation of product quality and structural integrity. Excitation frequency is one of the key performance factors for defect characterization. In the literature, there are many interesting papers dealing with wide spectral content and optimal frequency in terms of detection sensitivity. However, research activity on frequency optimization with respect to characterization performances is lacking. In this paper, an investigation into optimum excitation frequency has been conducted to enhance surface defect classification performance. The influences of excitation frequency for a group of defects were revealed in terms of detection sensitivity, contrast between defect features, and classification accuracy using kernel principal component analysis (KPCA) and a support vector machine (SVM). It is observed that probe signals are the most sensitive on the whole for a group of defects when excitation frequency is set near the frequency at which maximum probe signals are retrieved for the largest defect. After the use of KPCA, the margins between the defect features are optimum from the perspective of the SVM, which adopts optimal hyperplanes for structure risk minimization. As a result, the best classification accuracy is obtained. The main contribution is that the influences of excitation frequency on defect characterization are interpreted, and experiment-based procedures are proposed to determine the optimal excitation frequency for a group of defects rather than a single defect with respect to optimal characterization performances. PMID:27164112

Systematic review of autosomal recessive ataxias and proposal for a classification.

PubMed

Beaudin, Marie; Klein, Christopher J; Rouleau, Guy A; Dupré, Nicolas

2017-01-01

The classification of autosomal recessive ataxias represents a significant challenge because of high genetic heterogeneity and complex phenotypes. We conducted a comprehensive systematic review of the literature to examine all recessive ataxias in order to propose a new classification and properly circumscribe this field as new technologies are emerging for comprehensive targeted gene testing. We searched Pubmed and Embase to identify original articles on recessive forms of ataxia in humans for which a causative gene had been identified. Reference lists and public databases, including OMIM and GeneReviews, were also reviewed. We evaluated the clinical descriptions to determine if ataxia was a core feature of the phenotype and assessed the available evidence on the genotype-phenotype association. Included disorders were classified as primary recessive ataxias, as other complex movement or multisystem disorders with prominent ataxia, or as disorders that may occasionally present with ataxia. After removal of duplicates, 2354 references were reviewed and assessed for inclusion. A total of 130 articles were completely reviewed and included in this qualitative analysis. The proposed new list of autosomal recessive ataxias includes 45 gene-defined disorders for which ataxia is a core presenting feature. We propose a clinical algorithm based on the associated symptoms. We present a new classification for autosomal recessive ataxias that brings awareness to their complex phenotypes while providing a unified categorization of this group of disorders. This review should assist in the development of a consensus nomenclature useful in both clinical and research applications.

Reporting observational studies of the use of information technology in the clinical consultation. A position statement from the IMIA Primary Health Care Informatics Working Group (IMIA PCI WG).

PubMed

de Lusignan, S; Pearce, C; Kumarapeli, P; Stavropoulou, C; Kushniruk, A; Sheikh, A; Shachak, A; Mendis, K

2011-01-01

To develop a classification system to improve the reporting of observational studies of the use of information technology (IT) in clinical consultations. Literature review, workshops, and development of a position statement. We grouped the important aspects for consistent reporting into a "faceted classification"; the components relevant to a particular study to be used independently. The eight facets of our classification are: (1) Theoretical and methodological approach: e.g. dramaturgical, cognitive; (2) DATA COLLECTION: Type and method of observation; (3) Room layout and environment: How this affects interaction between clinician, patient and computer. (4) Initiation and Interaction: Who starts the consultation, and how the participants interact; (5) Information and knowledge utilisation: What sources of information or decision support are used or provided; (6) Timing and type of consultation variables: Standard descriptors that can be used to allow comparison of duration and description of continuous activities (e.g. speech, eye contact) and episodic ones, such as prescribing; (7) Post-consultation impact measures: Satisfaction surveys and health economic assessment based on the perceived quality of the clinician-patient interaction; and (8) Data capture, storage, and export formats: How to archive and curate data to facilitate further analysis. Adoption of this classification should make it easier to interpret research findings and facilitate the synthesis of evidence across studies. Those engaged in IT-consultation research shouldconsider adopting this reporting guide.

Frequency Optimization for Enhancement of Surface Defect Classification Using the Eddy Current Technique.

PubMed

Fan, Mengbao; Wang, Qi; Cao, Binghua; Ye, Bo; Sunny, Ali Imam; Tian, Guiyun

2016-05-07

Eddy current testing is quite a popular non-contact and cost-effective method for nondestructive evaluation of product quality and structural integrity. Excitation frequency is one of the key performance factors for defect characterization. In the literature, there are many interesting papers dealing with wide spectral content and optimal frequency in terms of detection sensitivity. However, research activity on frequency optimization with respect to characterization performances is lacking. In this paper, an investigation into optimum excitation frequency has been conducted to enhance surface defect classification performance. The influences of excitation frequency for a group of defects were revealed in terms of detection sensitivity, contrast between defect features, and classification accuracy using kernel principal component analysis (KPCA) and a support vector machine (SVM). It is observed that probe signals are the most sensitive on the whole for a group of defects when excitation frequency is set near the frequency at which maximum probe signals are retrieved for the largest defect. After the use of KPCA, the margins between the defect features are optimum from the perspective of the SVM, which adopts optimal hyperplanes for structure risk minimization. As a result, the best classification accuracy is obtained. The main contribution is that the influences of excitation frequency on defect characterization are interpreted, and experiment-based procedures are proposed to determine the optimal excitation frequency for a group of defects rather than a single defect with respect to optimal characterization performances.

EXTENDING AQUATIC CLASSIFICATION TO THE LANDSCAPE SCALE HYDROLOGY-BASED STRATEGIES

EPA Science Inventory

Aquatic classification of single water bodies (lakes, wetlands, estuaries) is often based on geologic origin, while stream classification has relied on multiple factors related to landform, geomorphology, and soils. We have developed an approach to aquatic classification based o...

Operations research in intensive care unit management: a literature review.

PubMed

Bai, Jie; Fügener, Andreas; Schoenfelder, Jan; Brunner, Jens O

2018-03-01

The intensive care unit (ICU) is a crucial and expensive resource largely affected by uncertainty and variability. Insufficient ICU capacity causes many negative effects not only in the ICU itself, but also in other connected departments along the patient care path. Operations research/management science (OR/MS) plays an important role in identifying ways to manage ICU capacities efficiently and in ensuring desired levels of service quality. As a consequence, numerous papers on the topic exist. The goal of this paper is to provide the first structured literature review on how OR/MS may support ICU management. We start our review by illustrating the important role the ICU plays in the hospital patient flow. Then we focus on the ICU management problem (single department management problem) and classify the literature from multiple angles, including decision horizons, problem settings, and modeling and solution techniques. Based on the classification logic, research gaps and opportunities are highlighted, e.g., combining bed capacity planning and personnel scheduling, modeling uncertainty with non-homogenous distribution functions, and exploring more efficient solution approaches.

Support vector machines to detect physiological patterns for EEG and EMG-based human-computer interaction: a review

NASA Astrophysics Data System (ADS)

Quitadamo, L. R.; Cavrini, F.; Sbernini, L.; Riillo, F.; Bianchi, L.; Seri, S.; Saggio, G.

2017-02-01

Support vector machines (SVMs) are widely used classifiers for detecting physiological patterns in human-computer interaction (HCI). Their success is due to their versatility, robustness and large availability of free dedicated toolboxes. Frequently in the literature, insufficient details about the SVM implementation and/or parameters selection are reported, making it impossible to reproduce study analysis and results. In order to perform an optimized classification and report a proper description of the results, it is necessary to have a comprehensive critical overview of the applications of SVM. The aim of this paper is to provide a review of the usage of SVM in the determination of brain and muscle patterns for HCI, by focusing on electroencephalography (EEG) and electromyography (EMG) techniques. In particular, an overview of the basic principles of SVM theory is outlined, together with a description of several relevant literature implementations. Furthermore, details concerning reviewed papers are listed in tables and statistics of SVM use in the literature are presented. Suitability of SVM for HCI is discussed and critical comparisons with other classifiers are reported.

NASA Scope and Subject Category Guide

NASA Technical Reports Server (NTRS)

2011-01-01

This guide provides a simple, effective tool to assist aerospace information analysts and database builders in the high-level subject classification of technical materials. Each of the 76 subject categories comprising the classification scheme is presented with a description of category scope, a listing of subtopics, cross references, and an indication of particular areas of NASA interest. The guide also includes an index of nearly 3,000 specific research topics cross referenced to the subject categories. The portable document format (PDF) version of the guide contains links in the index from each input subject to its corresponding categories. In addition to subject classification, the guide can serve as an aid to searching databases that use the classification scheme, and is also an excellent selection guide for those involved in the acquisition of aerospace literature. The CD-ROM contains both HTML and PDF versions.

Digital Dinosaur Discoveries.

ERIC Educational Resources Information Center

Pittman, Kim

1997-01-01

Presents an activity with the objective that students apply and integrate what they learn about classification, food webs, and paleontology to the creation of a scientifically sound ecosystem. Students read and discuss literature selections during the unit. (DDR)

Postmortem ICD interrogation in mode of death classification.

PubMed

Nikolaidou, Theodora; Johnson, Miriam J; Ghosh, Justin M; Marincowitz, Carl; Shah, Saumil; Lammiman, Michael J; Schilling, Richard J; Clark, Andrew L

2018-04-01

The definition of sudden death due to arrhythmia relies on the time interval between onset of symptoms and death. However, not all sudden deaths are due to arrhythmia. In patients with an implantable cardioverter defibrillator (ICD), postmortem device interrogation may help better distinguish the mode of death compared to a time-based definition alone. This study aims to assess the proportion of "sudden" cardiac deaths in patients with an ICD that have confirmed arrhythmia. We conducted a literature search for studies using postmortem ICD interrogation and a time-based classification of the mode of death. A modified QUADAS-2 checklist was used to assess risk of bias in individual studies. Outcome data were pooled where sufficient data were available. Our search identified 22 studies undertaken between 1982 and 2015 with 23,600 participants. The pooled results (excluding studies with high risk of bias) suggest that ventricular arrhythmias are present at the time of death in 76% of "sudden" deaths (95% confidence interval [CI] 67-85; range 42-88). Postmortem ICD interrogation identifies 24% of "sudden" deaths to be nonarrhythmic. Postmortem device interrogation should be considered in all cases of unexplained sudden cardiac death. © 2018 Wiley Periodicals, Inc.

The application of fuzzy Delphi and fuzzy inference system in supplier ranking and selection

NASA Astrophysics Data System (ADS)

Tahriri, Farzad; Mousavi, Maryam; Hozhabri Haghighi, Siamak; Zawiah Md Dawal, Siti

2014-06-01

In today's highly rival market, an effective supplier selection process is vital to the success of any manufacturing system. Selecting the appropriate supplier is always a difficult task because suppliers posses varied strengths and weaknesses that necessitate careful evaluations prior to suppliers' ranking. This is a complex process with many subjective and objective factors to consider before the benefits of supplier selection are achieved. This paper identifies six extremely critical criteria and thirteen sub-criteria based on the literature. A new methodology employing those criteria and sub-criteria is proposed for the assessment and ranking of a given set of suppliers. To handle the subjectivity of the decision maker's assessment, an integration of fuzzy Delphi with fuzzy inference system has been applied and a new ranking method is proposed for supplier selection problem. This supplier selection model enables decision makers to rank the suppliers based on three classifications including "extremely preferred", "moderately preferred", and "weakly preferred". In addition, in each classification, suppliers are put in order from highest final score to the lowest. Finally, the methodology is verified and validated through an example of a numerical test bed.

A Sensory 3D Map of the Odor Description Space Derived from a Comparison of Numeric Odor Profile Databases.

PubMed

Zarzo, Manuel

2015-06-01

Many authors have proposed different schemes of odor classification, which are useful to aid the complex task of describing smells. However, reaching a consensus on a particular classification seems difficult because our psychophysical space of odor description is a continuum and is not clustered into well-defined categories. An alternative approach is to describe the perceptual space of odors as a low-dimensional coordinate system. This idea was first proposed by Crocker and Henderson in 1927, who suggested using numeric profiles based on 4 dimensions: "fragrant," "acid," "burnt," and "caprylic." In the present work, the odor profiles of 144 aroma chemicals were compared by means of statistical regression with comparable numeric odor profiles obtained from 2 databases, enabling a plausible interpretation of the 4 dimensions. Based on the results and taking into account comparable 2D sensory maps of odor descriptors from the literature, a 3D sensory map (odor cube) has been drawn up to improve understanding of the similarities and dissimilarities of the odor descriptors most frequently used in fragrance chemistry. © The Author 2015. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

[Gait disorders in geriatric patients. Classification and therapy].

PubMed

Jahn, K; Heinze, C; Selge, C; Heßelbarth, K; Schniepp, R

2015-04-01

Slow walking with reduced body dynamics is a characteristic feature of locomotion in the elderly. Impaired mobility and falls associated with gait disorders significantly contribute to a reduced quality of life in the elderly. A gait disorder is not an inevitable consequence of aging. This article shows that it is worth recognizing specific deficits and differentiating specific aspects in multifactorial disorders because many causes can be well treated. Also provided are the bases for clinical classification and therapeutic principles. Review of recent literature and clinical review based on own experience and own scientific results. Common causes of disturbed gait in the elderly are neurological deficits, including sensory deficits (e.g. peripheral neuropathy and vestibulopathy), neurodegeneration (e.g. cerebellar ataxia and parkinsonian syndromes, cognitive impairment (e.g. degenerative dementia), degeneration of joints (e.g. coxarthrosis) and general loss of muscle mass (sarcopenia). Furthermore, a fear of falling also contributes to the gait disorder. Multimodal therapies are often necessary and the principles are presented. Identification of deficits is a prerequisite for specific therapy. As physical activity protects against cognitive impairment, reduces the risk of falling and improves overall quality of life, a structured assessment of causes for gait impairment is crucial.

[Historical outline on the nomenclature of neck lymph nodes as a basis of neck dissection classification].

PubMed

Werner, J A

2001-07-01

The neck dissection classification is based considerably on the organization of the lymph nodes of the neck. Terminology and anatomical allocation of nearly 300 cervicofacial lymph nodes repeatedly changed since the beginning of the 20th century. Analysis of the literature on neck lymph node organization with reference to the development of the neck dissection classification. The first fundamental nomenclature of the neck lymph nodes is founded on the work of Rouviére (1932). Suárez (1963) described the functional neck dissection on the basis of the fascial compartmentalization of the neck. Lindberg (1972) left the predominantly anatomically correlated grouping of the cervical lymph nodes as described by Rouviére and divided the lymphatic system of the neck on basis of pathophysiological mechanisms. The attention regarding the location of occult metastases led to the description of the selective neck dissection. Since the fundamental work of Shah et al. (1981) there was a multiplicity of more or less slight changes of the neck node regions. These changes were again basis for new neck dissection terminologies. A new classification was introduced in the year 2000 as the revised version of the American Head and Neck Society. The revised version of the neck dissection classification can reduce former controversies, particularly regarding an optimized intraoperative allocation of the lymph nodes and a simplified terminology of the selective neck dissection. With the goal of a standardization of the neck dissection forms it remains to be seen if the proponents of the functional neck dissection after Suárez consider the extent of the neck dissection in patients with N0 neck in favor of the selective neck dissection.

Towards the Automatic Classification of Avian Flight Calls for Bioacoustic Monitoring

PubMed Central

Bello, Juan Pablo; Farnsworth, Andrew; Robbins, Matt; Keen, Sara; Klinck, Holger; Kelling, Steve

2016-01-01

Automatic classification of animal vocalizations has great potential to enhance the monitoring of species movements and behaviors. This is particularly true for monitoring nocturnal bird migration, where automated classification of migrants’ flight calls could yield new biological insights and conservation applications for birds that vocalize during migration. In this paper we investigate the automatic classification of bird species from flight calls, and in particular the relationship between two different problem formulations commonly found in the literature: classifying a short clip containing one of a fixed set of known species (N-class problem) and the continuous monitoring problem, the latter of which is relevant to migration monitoring. We implemented a state-of-the-art audio classification model based on unsupervised feature learning and evaluated it on three novel datasets, one for studying the N-class problem including over 5000 flight calls from 43 different species, and two realistic datasets for studying the monitoring scenario comprising hundreds of thousands of audio clips that were compiled by means of remote acoustic sensors deployed in the field during two migration seasons. We show that the model achieves high accuracy when classifying a clip to one of N known species, even for a large number of species. In contrast, the model does not perform as well in the continuous monitoring case. Through a detailed error analysis (that included full expert review of false positives and negatives) we show the model is confounded by varying background noise conditions and previously unseen vocalizations. We also show that the model needs to be parameterized and benchmarked differently for the continuous monitoring scenario. Finally, we show that despite the reduced performance, given the right conditions the model can still characterize the migration pattern of a specific species. The paper concludes with directions for future research. PMID:27880836

Parameterization of Shape and Compactness in Object-based Image Classification Using Quickbird-2 Imagery

NASA Astrophysics Data System (ADS)

Tonbul, H.; Kavzoglu, T.

2016-12-01

In recent years, object based image analysis (OBIA) has spread out and become a widely accepted technique for the analysis of remotely sensed data. OBIA deals with grouping pixels into homogenous objects based on spectral, spatial and textural features of contiguous pixels in an image. The first stage of OBIA, named as image segmentation, is the most prominent part of object recognition. In this study, multiresolution segmentation, which is a region-based approach, was employed to construct image objects. In the application of multi-resolution, three parameters, namely shape, compactness and scale must be set by the analyst. Segmentation quality remarkably influences the fidelity of the thematic maps and accordingly the classification accuracy. Therefore, it is of great importance to search and set optimal values for the segmentation parameters. In the literature, main focus has been on the definition of scale parameter, assuming that the effect of shape and compactness parameters is limited in terms of achieved classification accuracy. The aim of this study is to deeply analyze the influence of shape/compactness parameters by varying their values while using the optimal scale parameter determined by the use of Estimation of Scale Parameter (ESP-2) approach. A pansharpened Qickbird-2 image covering Trabzon, Turkey was employed to investigate the objectives of the study. For this purpose, six different combinations of shape/compactness were utilized to make deductions on the behavior of shape and compactness parameters and optimal setting for all parameters as a whole. Objects were assigned to classes using nearest neighbor classifier in all segmentation observations and equal number of pixels was randomly selected to calculate accuracy metrics. The highest overall accuracy (92.3%) was achieved by setting the shape/compactness criteria to 0.3/0.3. The results of this study indicate that shape/compactness parameters can have significant effect on classification accuracy with 4% change in overall accuracy. Also, statistical significance of differences in accuracy was tested using the McNemar's test and found that the difference between poor and optimal setting of shape/compactness parameters was statistically significant, suggesting a search for optimal parameterization instead of default setting.

7 CFR 27.36 - Classification and Micronaire determinations based on official standards.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 2 2010-01-01 2010-01-01 false Classification and Micronaire determinations based on... COMMODITY STANDARDS AND STANDARD CONTAINER REGULATIONS COTTON CLASSIFICATION UNDER COTTON FUTURES LEGISLATION Regulations Classification and Micronaire Determinations § 27.36 Classification and Micronaire...

7 CFR 27.36 - Classification and Micronaire determinations based on official standards.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 7 Agriculture 2 2011-01-01 2011-01-01 false Classification and Micronaire determinations based on... COMMODITY STANDARDS AND STANDARD CONTAINER REGULATIONS COTTON CLASSIFICATION UNDER COTTON FUTURES LEGISLATION Regulations Classification and Micronaire Determinations § 27.36 Classification and Micronaire...

Automatic welding detection by an intelligent tool pipe inspection

NASA Astrophysics Data System (ADS)

Arizmendi, C. J.; Garcia, W. L.; Quintero, M. A.

2015-07-01

This work provide a model based on machine learning techniques in welds recognition, based on signals obtained through in-line inspection tool called “smart pig” in Oil and Gas pipelines. The model uses a signal noise reduction phase by means of pre-processing algorithms and attribute-selection techniques. The noise reduction techniques were selected after a literature review and testing with survey data. Subsequently, the model was trained using recognition and classification algorithms, specifically artificial neural networks and support vector machines. Finally, the trained model was validated with different data sets and the performance was measured with cross validation and ROC analysis. The results show that is possible to identify welding automatically with an efficiency between 90 and 98 percent.

Hypotheses generation as supervised link discovery with automated class labeling on large-scale biomedical concept networks

PubMed Central

2012-01-01

Computational approaches to generate hypotheses from biomedical literature have been studied intensively in recent years. Nevertheless, it still remains a challenge to automatically discover novel, cross-silo biomedical hypotheses from large-scale literature repositories. In order to address this challenge, we first model a biomedical literature repository as a comprehensive network of biomedical concepts and formulate hypotheses generation as a process of link discovery on the concept network. We extract the relevant information from the biomedical literature corpus and generate a concept network and concept-author map on a cluster using Map-Reduce frame-work. We extract a set of heterogeneous features such as random walk based features, neighborhood features and common author features. The potential number of links to consider for the possibility of link discovery is large in our concept network and to address the scalability problem, the features from a concept network are extracted using a cluster with Map-Reduce framework. We further model link discovery as a classification problem carried out on a training data set automatically extracted from two network snapshots taken in two consecutive time duration. A set of heterogeneous features, which cover both topological and semantic features derived from the concept network, have been studied with respect to their impacts on the accuracy of the proposed supervised link discovery process. A case study of hypotheses generation based on the proposed method has been presented in the paper. PMID:22759614

Retinopathy of Prematurity: Clinical Features, Classification, Natural History, Management and Outcome.

PubMed

Shah, Parag K; Prabhu, Vishma; Ranjan, Ratnesh; Narendran, Venkatapathy; Kalpana, Narendran

2016-11-07

Retinopathy of prematurity is an avoidable cause of childhood blindness. Proper understanding of the classification and treatment methods is a must in tackling this disease. Literature search with PubMed was conducted covering the period 1940-2015 with regards to retinopathy of prematurity, retrolental fibroplasia, its natural history, classification and treatment. The clinical features, screening and staging of retinopathy of prematurity according to International classification of retinopathy of prematurity (ICROP) has been included with illustrations. The standard current treatment indications, modalities and outcomes from landmark randomized controlled trials on retinopathy of prematurity have been mentioned. This review would help pediatricians to update their current knowledge on classification and treatment of retinopathy of prematurity. Screening for retinopathy of prematurity, in India, should be performed in all preterm neonates who are born <34 weeks gestation and/or <1750 grams birthweight; as well as in babies 34-36 weeks gestation or 1750-2000 grams birthweight if they have risk factors for ROP. Screening should start by one month after birth.

Content comparison of occupation-based instruments in adult rheumatology and musculoskeletal rehabilitation based on the International Classification of Functioning, Disability and Health.

PubMed

Stamm, Tanja A; Cieza, Alarcos; Machold, Klaus P; Smolen, Josef S; Stucki, Gerold

2004-12-15

To compare the content of clinical, occupation-based instruments that are used in adult rheumatology and musculoskeletal rehabilitation in occupational therapy based on the International Classification of Functioning, Disability and Health (ICF). Clinical instruments of occupational performance and occupation in adult rehabilitation and rheumatology were identified in a literature search. All items of these instruments were linked to the ICF categories according to 10 linking rules. On the basis of the linking, the content of these instruments was compared and the relationship between the capacity and performance component explored. The following 7 instruments were identified: the Canadian Occupational Performance Measure, the Assessment of Motor and Process Skills, the Sequential Occupational Dexterity Assessment, the Jebson Taylor Hand Function Test, the Moberg Picking Up Test, the Button Test, and the Functional Dexterity Test. The items of the 7 instruments were linked to 53 different ICF categories. Five items could not be linked to the ICF. The areas covered by the 7 occupation-based instruments differ importantly: The main focus of all 7 instruments is on the ICF component activities and participation. Body functions are covered by 2 instruments. Two instruments were linked to 1 single ICF category only. Clinicians and researchers who need to select an occupation-based instrument must be aware of the areas that are covered by this instrument and the potential areas that are not covered at all.

A One-Versus-All Class Binarization Strategy for Bearing Diagnostics of Concurrent Defects

PubMed Central

Ng, Selina S. Y.; Tse, Peter W.; Tsui, Kwok L.

2014-01-01

In bearing diagnostics using a data-driven modeling approach, a concern is the need for data from all possible scenarios to build a practical model for all operating conditions. This paper is a study on bearing diagnostics with the concurrent occurrence of multiple defect types. The authors are not aware of any work in the literature that studies this practical problem. A strategy based on one-versus-all (OVA) class binarization is proposed to improve fault diagnostics accuracy while reducing the number of scenarios for data collection, by predicting concurrent defects from training data of normal and single defects. The proposed OVA diagnostic approach is evaluated with empirical analysis using support vector machine (SVM) and C4.5 decision tree, two popular classification algorithms frequently applied to system health diagnostics and prognostics. Statistical features are extracted from the time domain and the frequency domain. Prediction performance of the proposed strategy is compared with that of a simple multi-class classification, as well as that of random guess and worst-case classification. We have verified the potential of the proposed OVA diagnostic strategy in performance improvements for single-defect diagnosis and predictions of BPFO plus BPFI concurrent defects using two laboratory-collected vibration data sets. PMID:24419162

Holistic approach for automated background EEG assessment in asphyxiated full-term infants

NASA Astrophysics Data System (ADS)

Matic, Vladimir; Cherian, Perumpillichira J.; Koolen, Ninah; Naulaers, Gunnar; Swarte, Renate M.; Govaert, Paul; Van Huffel, Sabine; De Vos, Maarten

2014-12-01

Objective. To develop an automated algorithm to quantify background EEG abnormalities in full-term neonates with hypoxic ischemic encephalopathy. Approach. The algorithm classifies 1 h of continuous neonatal EEG (cEEG) into a mild, moderate or severe background abnormality grade. These classes are well established in the literature and a clinical neurophysiologist labeled 272 1 h cEEG epochs selected from 34 neonates. The algorithm is based on adaptive EEG segmentation and mapping of the segments into the so-called segments’ feature space. Three features are suggested and further processing is obtained using a discretized three-dimensional distribution of the segments’ features represented as a 3-way data tensor. Further classification has been achieved using recently developed tensor decomposition/classification methods that reduce the size of the model and extract a significant and discriminative set of features. Main results. Effective parameterization of cEEG data has been achieved resulting in high classification accuracy (89%) to grade background EEG abnormalities. Significance. For the first time, the algorithm for the background EEG assessment has been validated on an extensive dataset which contained major artifacts and epileptic seizures. The demonstrated high robustness, while processing real-case EEGs, suggests that the algorithm can be used as an assistive tool to monitor the severity of hypoxic insults in newborns.

The role of Brazilian National Health Information Systems in assessing the impact of Zika virus outbreak.

PubMed

Pavão, Ana Luiza Braz; Barcellos, Christovam; Pedroso, Marcel; Boccolini, Cristiano; Romero, Dália

2017-01-01

The Zika virus (ZIKV) epidemic has become a public health emergency following its association with severe neurological complications. We aim to discuss how the Brazilian National Health Information Systems can help to assess the impact of the ZIKV epidemic on health outcomes potentially related to ZIKV. Health outcomes potentially related to ZIKV infection were described based on a literature review of published studies on ZIKV infection outcomes and on recent protocols developed and published by the Brazilian Ministry of Health for different stages of the life cycle. These outcomes were correlated with the International Classification of Diseases 10th Revision (ICD-10) classification system, as this is the diagnostic classification registered in the Health Information System. A suggested list of 50 clinical manifestations, dispersed into 4 ICD chapters, and their information sources was created to help monitor the ZIKV epidemics and trends. Correlation of these selected ICD-10 codes and the HIS, as well as, a review of the potentialities and limitations of health information systems were performed. The potential of the Health Information System and its underutilization by stakeholders and researchers have been a barrier in diagnosing and reporting ZIKV infection and its complications. The ZIKV outbreak is still a challenge for health practice and the Brazilian Health Information System.

[Resources and risks in old age: the LUCAS-I marker set for a classification of elderly people as fit, pre-frail and frail. First results on validity from the Longitudinal Urban Cohort Ageing Study (LUCAS), Hamburg].

PubMed

Dapp, U; Anders, J; Golgert, S; von Renteln-Kruse, W; Minder, C E

2012-06-01

There is a need for a simple self-administered instrument to assess frailty in community-dwelling seniors. We present a new marker set to assess the functional state of seniors. Contrary to current literature, we focus not only on risks, but also include resources. The questions relate to facts (ways to do things), rather than on subjective information (e.g. exhaustion). It was developed in the context of the Longitudinal Urban Cohort Ageing Study (LUCAS) in Hamburg, Germany. The classification based on these questions proposes operational definitions of the terms fit, pre-frail and frail and is predictive for need for nursing care as well as mortality. A wealth of results establishes the validity of the categorisation compared to other health questions. One of the classification questions concerns cycling. For areas where cycling is not suitable, we propose to replace this question with one about independently walking 500 m. However, the cycling question appears to indicate frailty earlier. The self-administered questionnaire provides a simple, cost-effective way to screen seniors for early signs of declining function in order to start preventive action.

Two steps forward, one step back? A commentary on the disease-specific core sets of the International Classification of Functioning, Disability and Health (ICF).

PubMed

McIntyre, Anne; Tempest, Stephanie

2007-09-30

The International Classification of Functioning, Disability and Health (ICF) has been received favourably by health care professionals, disability rights organizations and proponents of the social model of disability. The success of the ICF largely depends on its uptake in practice and is considered unwieldy in its full format. To enhance the application of the ICF in practice, disease and site-specific core sets have been developed. The objective of this paper is to stimulate thought and discussion about the place of the ICF core sets in rehabilitation practice. The authors' review of the literature uses the ICF core sets (especially stroke), to debate if the ICF is at risk of taking two steps forward, one step back in its holistic portrayal of health. ICF disease specific core sets could be seen as taking two steps forward to enhance the user friendliness of the ICF and evidence-based practice in rehabilitation. However, there is a danger of taking one step back in reverting to a disease-specific classification. It is too early to conclude the efficacy of the disease-specific core sets, but there is an opportunity to debate where the next steps may lead.

A one-versus-all class binarization strategy for bearing diagnostics of concurrent defects.

PubMed

Ng, Selina S Y; Tse, Peter W; Tsui, Kwok L

2014-01-13

In bearing diagnostics using a data-driven modeling approach, a concern is the need for data from all possible scenarios to build a practical model for all operating conditions. This paper is a study on bearing diagnostics with the concurrent occurrence of multiple defect types. The authors are not aware of any work in the literature that studies this practical problem. A strategy based on one-versus-all (OVA) class binarization is proposed to improve fault diagnostics accuracy while reducing the number of scenarios for data collection, by predicting concurrent defects from training data of normal and single defects. The proposed OVA diagnostic approach is evaluated with empirical analysis using support vector machine (SVM) and C4.5 decision tree, two popular classification algorithms frequently applied to system health diagnostics and prognostics. Statistical features are extracted from the time domain and the frequency domain. Prediction performance of the proposed strategy is compared with that of a simple multi-class classification, as well as that of random guess and worst-case classification. We have verified the potential of the proposed OVA diagnostic strategy in performance improvements for single-defect diagnosis and predictions of BPFO plus BPFI concurrent defects using two laboratory-collected vibration data sets.

Automated classification of tropical shrub species: a hybrid of leaf shape and machine learning approach

PubMed Central

Murat, Miraemiliana; Abu, Arpah; Yap, Hwa Jen; Yong, Kien-Thai

2017-01-01

Plants play a crucial role in foodstuff, medicine, industry, and environmental protection. The skill of recognising plants is very important in some applications, including conservation of endangered species and rehabilitation of lands after mining activities. However, it is a difficult task to identify plant species because it requires specialized knowledge. Developing an automated classification system for plant species is necessary and valuable since it can help specialists as well as the public in identifying plant species easily. Shape descriptors were applied on the myDAUN dataset that contains 45 tropical shrub species collected from the University of Malaya (UM), Malaysia. Based on literature review, this is the first study in the development of tropical shrub species image dataset and classification using a hybrid of leaf shape and machine learning approach. Four types of shape descriptors were used in this study namely morphological shape descriptors (MSD), Histogram of Oriented Gradients (HOG), Hu invariant moments (Hu) and Zernike moments (ZM). Single descriptor, as well as the combination of hybrid descriptors were tested and compared. The tropical shrub species are classified using six different classifiers, which are artificial neural network (ANN), random forest (RF), support vector machine (SVM), k-nearest neighbour (k-NN), linear discriminant analysis (LDA) and directed acyclic graph multiclass least squares twin support vector machine (DAG MLSTSVM). In addition, three types of feature selection methods were tested in the myDAUN dataset, Relief, Correlation-based feature selection (CFS) and Pearson’s coefficient correlation (PCC). The well-known Flavia dataset and Swedish Leaf dataset were used as the validation dataset on the proposed methods. The results showed that the hybrid of all descriptors of ANN outperformed the other classifiers with an average classification accuracy of 98.23% for the myDAUN dataset, 95.25% for the Flavia dataset and 99.89% for the Swedish Leaf dataset. In addition, the Relief feature selection method achieved the highest classification accuracy of 98.13% after 80 (or 60%) of the original features were reduced, from 133 to 53 descriptors in the myDAUN dataset with the reduction in computational time. Subsequently, the hybridisation of four descriptors gave the best results compared to others. It is proven that the combination MSD and HOG were good enough for tropical shrubs species classification. Hu and ZM descriptors also improved the accuracy in tropical shrubs species classification in terms of invariant to translation, rotation and scale. ANN outperformed the others for tropical shrub species classification in this study. Feature selection methods can be used in the classification of tropical shrub species, as the comparable results could be obtained with the reduced descriptors and reduced in computational time and cost. PMID:28924506

Automated classification of tropical shrub species: a hybrid of leaf shape and machine learning approach.

PubMed

Murat, Miraemiliana; Chang, Siow-Wee; Abu, Arpah; Yap, Hwa Jen; Yong, Kien-Thai

2017-01-01

Plants play a crucial role in foodstuff, medicine, industry, and environmental protection. The skill of recognising plants is very important in some applications, including conservation of endangered species and rehabilitation of lands after mining activities. However, it is a difficult task to identify plant species because it requires specialized knowledge. Developing an automated classification system for plant species is necessary and valuable since it can help specialists as well as the public in identifying plant species easily. Shape descriptors were applied on the myDAUN dataset that contains 45 tropical shrub species collected from the University of Malaya (UM), Malaysia. Based on literature review, this is the first study in the development of tropical shrub species image dataset and classification using a hybrid of leaf shape and machine learning approach. Four types of shape descriptors were used in this study namely morphological shape descriptors (MSD), Histogram of Oriented Gradients (HOG), Hu invariant moments (Hu) and Zernike moments (ZM). Single descriptor, as well as the combination of hybrid descriptors were tested and compared. The tropical shrub species are classified using six different classifiers, which are artificial neural network (ANN), random forest (RF), support vector machine (SVM), k-nearest neighbour (k-NN), linear discriminant analysis (LDA) and directed acyclic graph multiclass least squares twin support vector machine (DAG MLSTSVM). In addition, three types of feature selection methods were tested in the myDAUN dataset, Relief, Correlation-based feature selection (CFS) and Pearson's coefficient correlation (PCC). The well-known Flavia dataset and Swedish Leaf dataset were used as the validation dataset on the proposed methods. The results showed that the hybrid of all descriptors of ANN outperformed the other classifiers with an average classification accuracy of 98.23% for the myDAUN dataset, 95.25% for the Flavia dataset and 99.89% for the Swedish Leaf dataset. In addition, the Relief feature selection method achieved the highest classification accuracy of 98.13% after 80 (or 60%) of the original features were reduced, from 133 to 53 descriptors in the myDAUN dataset with the reduction in computational time. Subsequently, the hybridisation of four descriptors gave the best results compared to others. It is proven that the combination MSD and HOG were good enough for tropical shrubs species classification. Hu and ZM descriptors also improved the accuracy in tropical shrubs species classification in terms of invariant to translation, rotation and scale. ANN outperformed the others for tropical shrub species classification in this study. Feature selection methods can be used in the classification of tropical shrub species, as the comparable results could be obtained with the reduced descriptors and reduced in computational time and cost.

The debate over diagnosis related groups.

PubMed

Spiegel, A D; Kavaler, F

1985-01-01

With the advent of the Prospective Payment System (PPS) using Diagnosis Related Groups (DRGs) as a classification method, the pros and cons of that mechanism have been sharply debated. Grouping the comments into categories related to administration/management, DRG system and quality of care, a review of relevant literature highlights the pertinent attitudes and views of professionals and organizations. Points constantly argued include data utilization, meaningful medical classifications, resource use, gaming, profit centers, patient homogeneity, severity of illness, length of stay, technology limitations and the erosion of standards.

The comprehensiveness of the ESHRE/ESGE classification of female genital tract congenital anomalies: a systematic review of cases not classified by the AFS system

PubMed Central

Di Spiezio Sardo, A.; Campo, R.; Gordts, S.; Spinelli, M.; Cosimato, C.; Tanos, V.; Brucker, S.; Li, T. C.; Gergolet, M.; De Angelis, C.; Gianaroli, L.; Grimbizis, G.

2015-01-01

STUDY QUESTION How comprehensive is the recently published European Society of Human Reproduction and Embryology (ESHRE)/European Society for Gynaecological Endoscopy (ESGE) classification system of female genital anomalies? SUMMARY ANSWER The ESHRE/ESGE classification provides a comprehensive description and categorization of almost all of the currently known anomalies that could not be classified properly with the American Fertility Society (AFS) system. WHAT IS KNOWN ALREADY Until now, the more accepted classification system, namely that of the AFS, is associated with serious limitations in effective categorization of female genital anomalies. Many cases published in the literature could not be properly classified using the AFS system, yet a clear and accurate classification is a prerequisite for treatment. STUDY DESIGN, SIZE AND DURATION The CONUTA (CONgenital UTerine Anomalies) ESHRE/ESGE group conducted a systematic review of the literature to examine if those types of anomalies that could not be properly classified with the AFS system could be effectively classified with the use of the new ESHRE/ESGE system. An electronic literature search through Medline, Embase and Cochrane library was carried out from January 1988 to January 2014. Three participants independently screened, selected articles of potential interest and finally extracted data from all the included studies. Any disagreement was discussed and resolved after consultation with a fourth reviewer and the results were assessed independently and approved by all members of the CONUTA group. PARTICIPANTS/MATERIALS, SETTING, METHODS Among the 143 articles assessed in detail, 120 were finally selected reporting 140 cases that could not properly fit into a specific class of the AFS system. Those 140 cases were clustered in 39 different types of anomalies. MAIN RESULTS AND THE ROLE OF CHANCE The congenital anomaly involved a single organ in 12 (30.8%) out of the 39 types of anomalies, while multiple organs and/or segments of Müllerian ducts (complex anomaly) were involved in 27 (69.2%) types. Uterus was the organ most frequently involved (30/39: 76.9%), followed by cervix (26/39: 66.7%) and vagina (23/39: 59%). In all 39 types, the ESHRE/ESGE classification system provided a comprehensive description of each single or complex anomaly. A precise categorization was reached in 38 out of 39 types studied. Only one case of a bizarre uterine anomaly, with no clear embryological defect, could not be categorized and thus was placed in Class 6 (un-classified) of the ESHRE/ESGE system. LIMITATIONS, REASONS FOR CAUTION The review of the literature was thorough but we cannot rule out the possibility that other defects exist which will also require testing in the new ESHRE/ESGE system. These anomalies, however, must be rare. WIDER IMPLICATIONS OF THE FINDINGS The comprehensiveness of the ESHRE/ESGE classification adds objective scientific validity to its use. This may, therefore, promote its further dissemination and acceptance, which will have a positive outcome in clinical care and research. STUDY FUNDING/COMPETING INTEREST(S) None. PMID:25788565

Successful classification of cocaine dependence using brain imaging: a generalizable machine learning approach.

PubMed

Mete, Mutlu; Sakoglu, Unal; Spence, Jeffrey S; Devous, Michael D; Harris, Thomas S; Adinoff, Bryon

2016-10-06

Neuroimaging studies have yielded significant advances in the understanding of neural processes relevant to the development and persistence of addiction. However, these advances have not explored extensively for diagnostic accuracy in human subjects. The aim of this study was to develop a statistical approach, using a machine learning framework, to correctly classify brain images of cocaine-dependent participants and healthy controls. In this study, a framework suitable for educing potential brain regions that differed between the two groups was developed and implemented. Single Photon Emission Computerized Tomography (SPECT) images obtained during rest or a saline infusion in three cohorts of 2-4 week abstinent cocaine-dependent participants (n = 93) and healthy controls (n = 69) were used to develop a classification model. An information theoretic-based feature selection algorithm was first conducted to reduce the number of voxels. A density-based clustering algorithm was then used to form spatially connected voxel clouds in three-dimensional space. A statistical classifier, Support Vectors Machine (SVM), was then used for participant classification. Statistically insignificant voxels of spatially connected brain regions were removed iteratively and classification accuracy was reported through the iterations. The voxel-based analysis identified 1,500 spatially connected voxels in 30 distinct clusters after a grid search in SVM parameters. Participants were successfully classified with 0.88 and 0.89 F-measure accuracies in 10-fold cross validation (10xCV) and leave-one-out (LOO) approaches, respectively. Sensitivity and specificity were 0.90 and 0.89 for LOO; 0.83 and 0.83 for 10xCV. Many of the 30 selected clusters are highly relevant to the addictive process, including regions relevant to cognitive control, default mode network related self-referential thought, behavioral inhibition, and contextual memories. Relative hyperactivity and hypoactivity of regional cerebral blood flow in brain regions in cocaine-dependent participants are presented with corresponding level of significance. The SVM-based approach successfully classified cocaine-dependent and healthy control participants using voxels selected with information theoretic-based and statistical methods from participants' SPECT data. The regions found in this study align with brain regions reported in the literature. These findings support the future use of brain imaging and SVM-based classifier in the diagnosis of substance use disorders and furthering an understanding of their underlying pathology.

Using remote sensing in support of environmental management: A framework for selecting products, algorithms and methods.

PubMed

de Klerk, Helen M; Gilbertson, Jason; Lück-Vogel, Melanie; Kemp, Jaco; Munch, Zahn

2016-11-01

Traditionally, to map environmental features using remote sensing, practitioners will use training data to develop models on various satellite data sets using a number of classification approaches and use test data to select a single 'best performer' from which the final map is made. We use a combination of an omission/commission plot to evaluate various results and compile a probability map based on consistently strong performing models across a range of standard accuracy measures. We suggest that this easy-to-use approach can be applied in any study using remote sensing to map natural features for management action. We demonstrate this approach using optical remote sensing products of different spatial and spectral resolution to map the endemic and threatened flora of quartz patches in the Knersvlakte, South Africa. Quartz patches can be mapped using either SPOT 5 (used due to its relatively fine spatial resolution) or Landsat8 imagery (used because it is freely accessible and has higher spectral resolution). Of the variety of classification algorithms available, we tested maximum likelihood and support vector machine, and applied these to raw spectral data, the first three PCA summaries of the data, and the standard normalised difference vegetation index. We found that there is no 'one size fits all' solution to the choice of a 'best fit' model (i.e. combination of classification algorithm or data sets), which is in agreement with the literature that classifier performance will vary with data properties. We feel this lends support to our suggestion that rather than the identification of a 'single best' model and a map based on this result alone, a probability map based on the range of consistently top performing models provides a rigorous solution to environmental mapping. Copyright © 2016 Elsevier Ltd. All rights reserved.

Comparisons of fish species traits from small streams to large rivers

USGS Publications Warehouse

Goldstein, R.M.; Meador, M.R.

2004-01-01

To examine the relations between fish community function and stream size, we classified 429 lotic freshwater fish species based on multiple categories within six species traits: (1) substrate preference, (2) geomorphic preference, (3) trophic ecology, (4) locomotion morphology, (5) reproductive strategy, and (6) stream size preference. Stream size categories included small streams, small, medium, and large rivers, and no size preference. The frequencies of each species trait category were determined for each stream size category based on life history information from the literature. Cluster analysis revealed the presence of covarying groups of species trait categories. One cluster (RUN) included the traits of planktivore and herbivore feeding ecology, migratory reproductive behavior and broadcast spawning, preferences for main-channel habitats, and a lack of preferences for substrate type. The frequencies of classifications for the RUN cluster varied significantly across stream size categories (P = 0.009), being greater for large rivers than for small streams and rivers. Another cluster (RIFFLE) included the traits of invertivore feeding ecology, simple nester reproductive behavior, a preference for riffles, and a preference for bedrock, boulder, and cobble-rubble substrate. No significant differences in the frequency of classifications among stream size categories were detected for the RIFFLE cluster (P = 0.328). Our results suggest that fish community function is structured by large-scale differences in habitat and is different for large rivers than for small streams and rivers. Our findings support theoretical predictions of variation in species traits among stream reaches based on ecological frameworks such as landscape filters, habitat templates, and the river continuum concept. We believe that the species trait classifications presented here provide an opportunity for further examination of fish species' relations to physical, chemical, and biological factors in lotic habitats ranging from small streams to large rivers.

Biowaiver or Bioequivalence: Ambiguity in Sildenafil Citrate BCS Classification.

PubMed

Miranda, Claudia; Pérez-Rodríguez, Zenia; Hernández-Armengol, Rosario; Quiñones-García, Yaidel; Betancourt-Purón, Tania; Cabrera-Pérez, Miguel Ángel

2018-05-01

The aim of the present study is to contribute to the scientific characterization of sildenafil citrate according to the Biopharmaceutics Classification System, following the World Health Organization (WHO) guidelines for biowaivers. The solubility and intestinal permeability data of sildenafil citrate were collected from literature; however, the experimental solubility studies are inconclusive and its "high permeability" suggests an API in the borderline of BCS Class I and Class II. The pH-solubility profile was determined using the saturation shake-flask method over the pH range of 1.2-6.8 at a temperature of 37 °C in aqueous media. The intestinal permeability was determined in rat by a closed-loop in situ perfusion method (the Doluisio technique). The solubility of sildenafil citrate is pH-dependent and at pH 6.8 the dose/solubility ratio obtained does not meet the WHO criteria for "high solubility." The high permeability values obtained by in situ intestinal perfusion in rat reinforce the published permeability data for sildenafil citrate. The experimental results obtained and the data available in the literature suggest that sildenafil citrate is clearly a Class II of BCS, according to the current biopharmaceutics classification system and WHO guidance.

Predicting Tillage Patterns in the Tiffin River Watershed Using Remote Sensing Methods

NASA Astrophysics Data System (ADS)

Brooks, C.; McCarty, J. L.; Dean, D. B.; Mann, B. F.

2012-12-01

Previous research in tillage mapping has focused primarily on utilizing low to no-cost, moderate (30 m to 15 m) resolution satellite data. Successful data processing techniques published in the scientific literature have focused on extracting and/or classifying tillage patterns through manipulation of spectral bands. For instance, Daughtry et al. (2005) evaluated several spectral indices for crop residue cover using satellite multispectral and hyperspectral data and to categorize soil tillage intensity in agricultural fields. A weak to moderate relationship between Landsat Thematic Mapper (TM) indices and crop residue cover was found; similar results were reported in Minnesota. Building on the findings from the scientific literature and previous work done by MTRI in the heavily agricultural Tiffin watershed of northwest Ohio and southeast Michigan, a decision tree classifier approach (also referred to as a classification tree) was used, linking several satellite data to on-the-ground tillage information in order to boost classification results. This approach included five tillage indices and derived products. A decision tree methodology enabled the development of statistically optimized (i.e., minimizing misclassification rates) classification algorithms at various desired time steps: monthly, seasonally, and annual over the 2006-2010 time period. Due to their flexibility, processing speed, and availability within all major remote sensing and statistical software packages, decision trees can ingest several data inputs from multiple sensors and satellite products, selecting only the bands, band ratios, indices, and products that further reduce misclassification errors. The project team created crop-specific tillage pattern classification trees whereby a training data set (~ 50% of available ground data) was created for production of the actual decision tree and a validation data set was set aside (~ 50% of available ground data) in order to assess the accuracy of the classification. A seasonal time step was used, optimizing a decision tree based on seasonal ground data for tillage patterns and satellite data and products for years 2006 through 2010. Annual crop type maps derived by the project team and the USDA Cropland Data Layer project was used an input to understand locations of corn, soybeans, wheat, etc. on a yearly basis. As previously stated, the robustness of the decision tree approach is the ability to implement various satellite data and products across temporal, spectral, and spatial resolutions, thereby improving the resulting classification and providing a reliable method that is not sensor-dependent. Tillage pattern classification from satellite imagery is not a simple task and has proven a challenge to previous researchers investigating this remote sensing topic. The team's decision tree method produced a practical, usable output within a focused project time period. Daughtry, C.S.T., Hunt Jr., E.R., Doraiswamy, P.C., McMurtrey III, J.E. 2005. Remote sensing the spatial distribution of crop residues. Agron. J. 97, 864-871.

Rule-based land use/land cover classification in coastal areas using seasonal remote sensing imagery: a case study from Lianyungang City, China.

PubMed

Yang, Xiaoyan; Chen, Longgao; Li, Yingkui; Xi, Wenjia; Chen, Longqian

2015-07-01

Land use/land cover (LULC) inventory provides an important dataset in regional planning and environmental assessment. To efficiently obtain the LULC inventory, we compared the LULC classifications based on single satellite imagery with a rule-based classification based on multi-seasonal imagery in Lianyungang City, a coastal city in China, using CBERS-02 (the 2nd China-Brazil Environmental Resource Satellites) images. The overall accuracies of the classification based on single imagery are 78.9, 82.8, and 82.0% in winter, early summer, and autumn, respectively. The rule-based classification improves the accuracy to 87.9% (kappa 0.85), suggesting that combining multi-seasonal images can considerably improve the classification accuracy over any single image-based classification. This method could also be used to analyze seasonal changes of LULC types, especially for those associated with tidal changes in coastal areas. The distribution and inventory of LULC types with an overall accuracy of 87.9% and a spatial resolution of 19.5 m can assist regional planning and environmental assessment efficiently in Lianyungang City. This rule-based classification provides a guidance to improve accuracy for coastal areas with distinct LULC temporal spectral features.

Geographic Object-Based Image Analysis - Towards a new paradigm.

PubMed

Blaschke, Thomas; Hay, Geoffrey J; Kelly, Maggi; Lang, Stefan; Hofmann, Peter; Addink, Elisabeth; Queiroz Feitosa, Raul; van der Meer, Freek; van der Werff, Harald; van Coillie, Frieke; Tiede, Dirk

2014-01-01

The amount of scientific literature on (Geographic) Object-based Image Analysis - GEOBIA has been and still is sharply increasing. These approaches to analysing imagery have antecedents in earlier research on image segmentation and use GIS-like spatial analysis within classification and feature extraction approaches. This article investigates these development and its implications and asks whether or not this is a new paradigm in remote sensing and Geographic Information Science (GIScience). We first discuss several limitations of prevailing per-pixel methods when applied to high resolution images. Then we explore the paradigm concept developed by Kuhn (1962) and discuss whether GEOBIA can be regarded as a paradigm according to this definition. We crystallize core concepts of GEOBIA, including the role of objects, of ontologies and the multiplicity of scales and we discuss how these conceptual developments support important methods in remote sensing such as change detection and accuracy assessment. The ramifications of the different theoretical foundations between the ' per-pixel paradigm ' and GEOBIA are analysed, as are some of the challenges along this path from pixels, to objects, to geo-intelligence. Based on several paradigm indications as defined by Kuhn and based on an analysis of peer-reviewed scientific literature we conclude that GEOBIA is a new and evolving paradigm.

DiseaseConnect: a comprehensive web server for mechanism-based disease–disease connections

PubMed Central

Liu, Chun-Chi; Tseng, Yu-Ting; Li, Wenyuan; Wu, Chia-Yu; Mayzus, Ilya; Rzhetsky, Andrey; Sun, Fengzhu; Waterman, Michael; Chen, Jeremy J. W.; Chaudhary, Preet M.; Loscalzo, Joseph; Crandall, Edward; Zhou, Xianghong Jasmine

2014-01-01

The DiseaseConnect (http://disease-connect.org) is a web server for analysis and visualization of a comprehensive knowledge on mechanism-based disease connectivity. The traditional disease classification system groups diseases with similar clinical symptoms and phenotypic traits. Thus, diseases with entirely different pathologies could be grouped together, leading to a similar treatment design. Such problems could be avoided if diseases were classified based on their molecular mechanisms. Connecting diseases with similar pathological mechanisms could inspire novel strategies on the effective repositioning of existing drugs and therapies. Although there have been several studies attempting to generate disease connectivity networks, they have not yet utilized the enormous and rapidly growing public repositories of disease-related omics data and literature, two primary resources capable of providing insights into disease connections at an unprecedented level of detail. Our DiseaseConnect, the first public web server, integrates comprehensive omics and literature data, including a large amount of gene expression data, Genome-Wide Association Studies catalog, and text-mined knowledge, to discover disease–disease connectivity via common molecular mechanisms. Moreover, the clinical comorbidity data and a comprehensive compilation of known drug–disease relationships are additionally utilized for advancing the understanding of the disease landscape and for facilitating the mechanism-based development of new drug treatments. PMID:24895436

Geographic Object-Based Image Analysis – Towards a new paradigm

PubMed Central

Blaschke, Thomas; Hay, Geoffrey J.; Kelly, Maggi; Lang, Stefan; Hofmann, Peter; Addink, Elisabeth; Queiroz Feitosa, Raul; van der Meer, Freek; van der Werff, Harald; van Coillie, Frieke; Tiede, Dirk

2014-01-01

The amount of scientific literature on (Geographic) Object-based Image Analysis – GEOBIA has been and still is sharply increasing. These approaches to analysing imagery have antecedents in earlier research on image segmentation and use GIS-like spatial analysis within classification and feature extraction approaches. This article investigates these development and its implications and asks whether or not this is a new paradigm in remote sensing and Geographic Information Science (GIScience). We first discuss several limitations of prevailing per-pixel methods when applied to high resolution images. Then we explore the paradigm concept developed by Kuhn (1962) and discuss whether GEOBIA can be regarded as a paradigm according to this definition. We crystallize core concepts of GEOBIA, including the role of objects, of ontologies and the multiplicity of scales and we discuss how these conceptual developments support important methods in remote sensing such as change detection and accuracy assessment. The ramifications of the different theoretical foundations between the ‘per-pixel paradigm’ and GEOBIA are analysed, as are some of the challenges along this path from pixels, to objects, to geo-intelligence. Based on several paradigm indications as defined by Kuhn and based on an analysis of peer-reviewed scientific literature we conclude that GEOBIA is a new and evolving paradigm. PMID:24623958

Biowaiver Monographs for Immediate Release Solid Oral Dosage Forms: Levetiracetam.

PubMed

Petruševska, Marija; Berglez, Sandra; Krisch, Igor; Legen, Igor; Megušar, Klara; Peternel, Luka; Abrahamsson, Bertil; Cristofoletti, Rodrigo; Groot, D W; Kopp, Sabine; Langguth, Peter; Mehta, Mehul; Polli, James E; Shah, Vinod P; Dressman, Jennifer

2015-09-01

Literature and experimental data relevant for the decision to allow a waiver of in vivo bioequivalence (BE) testing for the approval of immediate release (IR) solid oral dosage forms containing levetiracetam are reviewed. Data on solubility and permeability suggest that levetiracetam belongs to class I of the biopharmaceutical classification system (BCS). Levetiracetam's therapeutic use, its wide therapeutic index, and its favorable pharmacokinetic properties make levetiracetam a valid candidate for the BCS-based biowaiver approach. Further, no BE studies with levetiracetam IR formulations in which the test formulation failed to show BE with the comparator have been reported in the open literature. On the basis of the overall evidence, it appears unlikely that a BCS-based biowaiver approach for levetiracetam IR solid oral dosage forms formulated with established excipients would expose patients to undue risks. Thus, the BCS-based biowaiver approach procedure is recommended for IR solid oral dosage form containing levetiracetam, provided the excipients in the formulation are also present in products that have been approved in countries belonging to or associated with the International Committee on Harmonization and are used in their usual quantities, and provided the dissolution profiles of the test and reference product comply with the current requirements for BCS-based biowaivers. © 2015 Wiley Periodicals, Inc. and the American Pharmacists Association.

A systematic review and development of a classification framework for factors associated with missing patient-reported outcome data.

PubMed

Palmer, Michael J; Mercieca-Bebber, Rebecca; King, Madeleine; Calvert, Melanie; Richardson, Harriet; Brundage, Michael

2018-02-01

Missing patient-reported outcome data can lead to biased results, to loss of power to detect between-treatment differences, and to research waste. Awareness of factors may help researchers reduce missing patient-reported outcome data through study design and trial processes. The aim was to construct a Classification Framework of factors associated with missing patient-reported outcome data in the context of comparative studies. The first step in this process was informed by a systematic review. Two databases (MEDLINE and CINAHL) were searched from inception to March 2015 for English articles. Inclusion criteria were (a) relevant to patient-reported outcomes, (b) discussed missing data or compliance in prospective medical studies, and (c) examined predictors or causes of missing data, including reasons identified in actual trial datasets and reported on cover sheets. Two reviewers independently screened titles and abstracts. Discrepancies were discussed with the research team prior to finalizing the list of eligible papers. In completing the systematic review, four particular challenges to synthesizing the extracted information were identified. To address these challenges, operational principles were established by consensus to guide the development of the Classification Framework. A total of 6027 records were screened. In all, 100 papers were eligible and included in the review. Of these, 57% focused on cancer, 23% did not specify disease, and 20% reported for patients with a variety of non-cancer conditions. In total, 40% of the papers offered a descriptive analysis of possible factors associated with missing data, but some papers used other methods. In total, 663 excerpts of text (units), each describing a factor associated with missing patient-reported outcome data, were extracted verbatim. Redundant units were identified and sequestered. Similar units were grouped, and an iterative process of consensus among the investigators was used to reduce these units to a list of factors that met the guiding principles. The list was organized on a framework, using an iterative consensus-based process. The resultant Classification Framework is a summary of the factors associated with missing patient-reported outcome data described in the literature. It consists of 5 components (instrument, participant, centre, staff, and study) and 46 categories, each with one or more sub-categories or examples. A systematic review of the literature revealed 46 unique categories of factors associated with missing patient-reported outcome data, organized into 5 main component groups. The Classification Framework may assist researchers to improve the design of new randomized clinical trials and to implement procedures to reduce missing patient-reported outcome data. Further research using the Classification Framework to inform quantitative analyses of missing patient-reported outcome data in existing clinical trials and to inform qualitative inquiry of research staff is planned.

Teaching sexual history-taking skills using the Sexual Events Classification System.

PubMed

Fidler, Donald C; Petri, Justin Daniel; Chapman, Mark

2010-01-01

The authors review the literature about educational programs for teaching sexual history-taking skills and describe novel techniques for teaching these skills. Psychiatric residents enrolled in a brief sexual history-taking course that included instruction on the Sexual Events Classification System, feedback on residents' video-recorded interviews with simulated patients, discussion of videos that simulated bad interviews, simulated patients, and a competency scoring form to score a video of a simulated interview. After the course, residents completed an anonymous survey to assess the usefulness of the experience. After the course, most residents felt more comfortable taking sexual histories. They described the Sexual Events Classification System and simulated interviews as practical methods for teaching sexual history-taking skills. The Sexual Events Classification System and simulated patient experiences may serve as a practical model for teaching sexual history-taking skills to general psychiatric residents.

A Discriminative Approach to EEG Seizure Detection

PubMed Central

Johnson, Ashley N.; Sow, Daby; Biem, Alain

2011-01-01

Seizures are abnormal sudden discharges in the brain with signatures represented in electroencephalograms (EEG). The efficacy of the application of speech processing techniques to discriminate between seizure and non-seizure states in EEGs is reported. The approach accounts for the challenges of unbalanced datasets (seizure and non-seizure), while also showing a system capable of real-time seizure detection. The Minimum Classification Error (MCE) algorithm, which is a discriminative learning algorithm with wide-use in speech processing, is applied and compared with conventional classification techniques that have already been applied to the discrimination between seizure and non-seizure states in the literature. The system is evaluated on 22 pediatric patients multi-channel EEG recordings. Experimental results show that the application of speech processing techniques and MCE compare favorably with conventional classification techniques in terms of classification performance, while requiring less computational overhead. The results strongly suggests the possibility of deploying the designed system at the bedside. PMID:22195192

Recent Changes of Classification for Squamous Intraepithelial Lesions of the Head and Neck.

PubMed

Cho, Kyung-Ja; Song, Joon Seon

2018-05-18

- Interpretation of atypical squamous lesions of the head and neck has always been a nettlesome task for pathologists. Moreover, many different grading systems for squamous intraepithelial lesions have been proposed in past decades. The recent World Health Organization 2017 classification presents 2 types of 2-tier systems for laryngeal and oral precursor lesions. - To review the recent changes in classification and the clinical significance for squamous intraepithelial lesions of the head and neck. - Personal experience and data from the literature. - The 2-tier grading system for laryngeal dysplasia, presented by World Health Organization in 2017, is expected to improve diagnostic reproducibility and clinical implication. However, the diagnostic criteria for low-grade dysplasia do not distinguish it clearly from basal cell hyperplasia. The World Health Organization 2017 classification of oral epithelial dysplasia remains unclear, and complicated and variable grading systems still make head and neck intraepithelial lesions difficult to interpret.

Singular spectrum decomposition of Bouligand-Minkowski fractal descriptors: an application to the classification of texture Images

NASA Astrophysics Data System (ADS)

Florindo, João. Batista

2018-04-01

This work proposes the use of Singular Spectrum Analysis (SSA) for the classification of texture images, more specifically, to enhance the performance of the Bouligand-Minkowski fractal descriptors in this task. Fractal descriptors are known to be a powerful approach to model and particularly identify complex patterns in natural images. Nevertheless, the multiscale analysis involved in those descriptors makes them highly correlated. Although other attempts to address this point was proposed in the literature, none of them investigated the relation between the fractal correlation and the well-established analysis employed in time series. And SSA is one of the most powerful techniques for this purpose. The proposed method was employed for the classification of benchmark texture images and the results were compared with other state-of-the-art classifiers, confirming the potential of this analysis in image classification.

Kepler Stellar Properties Catalog Update for Q1-Q17 DR25 Transit Search

NASA Technical Reports Server (NTRS)

Mathur, Savita; Huber, Daniel

2016-01-01

Huber et al. (2014) presented revised stellar properties for 196,468 Kepler targets, which were used for the Q1-Q16 TPSDV planet search (Tenenbaum et al. 2014). The catalog was based on atmospheric properties (i.e., temperature (Teff), surface gravity (log(g)), and metallicity ([FeH])) published in the literature using a variety of methods (e.g., asteroseismology, spectroscopy, exoplanet transits, photometry), which were then homogeneously fitted to a grid of Dartmouth (DSEP) isochrones (Dotter et al. 2008). The catalog was updated in early 2015 for the Q1-Q17 Data Release (DR) 24 transit search (Seader et al. 2015) based on the latest classifications of Kepler targets in the literature at that time. The methodology followed Huber et al. (2014). Here we provide updated stellar properties of 197,096 Kepler targets. Like the previous catalog, this update is based on atmospheric properties that were either published in the literature or provided by the Kepler community follow-up program (CFOP). The input values again come from different methods: asteroseismology, spectroscopy, flicker, and photometry. This catalog update was developed to support the SOC 9.3 TPSDV planet search (Twicken et al. 2016), which is expected to be the final search and data release by the Kepler project.In this document, we describe the method and the inputs that were used to build the catalog. The methodology follows Huber et al. (2014) with a few improvements as described in Section 2.

Building a Shared Definitional Model of Long Duration Human Spaceflight

NASA Technical Reports Server (NTRS)

Orr, M.; Whitmire, A.; Sandoval, L.; Leveton, L.; Arias, D.

2011-01-01

In 1956, on the eve of human space travel Strughold first proposed a simple classification of the present and future stages of manned flight that identified key factors, risks and developmental stages for the evolutionary journey ahead. As we look to optimize the potential of the ISS as a gateway to new destinations, we need a current shared working definitional model of long duration human space flight to help guide our path. Initial search of formal and grey literature augmented by liaison with subject matter experts. Search strategy focused on both the use of term long duration mission and long duration spaceflight, and also broader related current and historical definitions and classification models of spaceflight. The related sea and air travel literature was also subsequently explored with a view to identifying analogous models or classification systems. There are multiple different definitions and classification systems for spaceflight including phase and type of mission, craft and payload and related risk management models. However the frequently used concepts of long duration mission and long duration spaceflight are infrequently operationally defined by authors, and no commonly referenced classical or gold standard definition or model of these terms emerged from the search. The categorization (Cat) system for sailing was found to be of potential analogous utility, with its focus on understanding the need for crew and craft autonomy at various levels of potential adversity and inability to gain outside support or return to a safe location, due to factors of time, distance and location.

Definition and classification of chyle leak after pancreatic operation: A consensus statement by the International Study Group on Pancreatic Surgery.

PubMed

Besselink, Marc G; van Rijssen, L Bengt; Bassi, Claudio; Dervenis, Christos; Montorsi, Marco; Adham, Mustapha; Asbun, Horacio J; Bockhorn, Maximillian; Strobel, Oliver; Büchler, Markus W; Busch, Olivier R; Charnley, Richard M; Conlon, Kevin C; Fernández-Cruz, Laureano; Fingerhut, Abe; Friess, Helmut; Izbicki, Jakob R; Lillemoe, Keith D; Neoptolemos, John P; Sarr, Michael G; Shrikhande, Shailesh V; Sitarz, Robert; Vollmer, Charles M; Yeo, Charles J; Hartwig, Werner; Wolfgang, Christopher L; Gouma, Dirk J

2017-02-01

Recent literature suggests that chyle leak may complicate up to 10% of pancreatic resections. Treatment depends on its severity, which may include chylous ascites. No international consensus definition or grading system of chyle leak currently is available. The International Study Group on Pancreatic Surgery, an international panel of pancreatic surgeons working in well-known, high-volume centers, reviewed the literature and worked together to establish a consensus on the definition and classification of chyle leak after pancreatic operation. Chyle leak was defined as output of milky-colored fluid from a drain, drain site, or wound on or after postoperative day 3, with a triglyceride content ≥110 mg/dL (≥1.2 mmol/L). Three different grades of severity were defined according to the management needed: grade A, no specific intervention other than oral dietary restrictions; grade B, prolongation of hospital stay, nasoenteral nutrition with dietary restriction, total parenteral nutrition, octreotide, maintenance of surgical drains, or placement of new percutaneous drains; and grade C, need for other more invasive in-hospital treatment, intensive care unit admission, or mortality. This classification and grading system for chyle leak after pancreatic resection allows for comparison of outcomes between series. As with the other the International Study Group on Pancreatic Surgery consensus statements, this classification should facilitate communication and evaluation of different approaches to the prevention and treatment of this complication. Copyright © 2016 Elsevier Inc. All rights reserved.

Discrete Biogeography Based Optimization for Feature Selection in Molecular Signatures.

PubMed

Liu, Bo; Tian, Meihong; Zhang, Chunhua; Li, Xiangtao

2015-04-01

Biomarker discovery from high-dimensional data is a complex task in the development of efficient cancer diagnoses and classification. However, these data are usually redundant and noisy, and only a subset of them present distinct profiles for different classes of samples. Thus, selecting high discriminative genes from gene expression data has become increasingly interesting in the field of bioinformatics. In this paper, a discrete biogeography based optimization is proposed to select the good subset of informative gene relevant to the classification. In the proposed algorithm, firstly, the fisher-markov selector is used to choose fixed number of gene data. Secondly, to make biogeography based optimization suitable for the feature selection problem; discrete migration model and discrete mutation model are proposed to balance the exploration and exploitation ability. Then, discrete biogeography based optimization, as we called DBBO, is proposed by integrating discrete migration model and discrete mutation model. Finally, the DBBO method is used for feature selection, and three classifiers are used as the classifier with the 10 fold cross-validation method. In order to show the effective and efficiency of the algorithm, the proposed algorithm is tested on four breast cancer dataset benchmarks. Comparison with genetic algorithm, particle swarm optimization, differential evolution algorithm and hybrid biogeography based optimization, experimental results demonstrate that the proposed method is better or at least comparable with previous method from literature when considering the quality of the solutions obtained. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Job and Work Evaluation: A Literature Review.

ERIC Educational Resources Information Center

Heneman, Robert L.

2003-01-01

Describes advantages and disadvantages of work evaluation methods: ranking, market pricing, banding, classification, single-factor, competency, point-factor, and factor comparison. Compares work evaluation perspectives: traditional, realist, market advocate, strategist, organizational development, social reality, contingency theory, competency,…

On phenomenology and classification of hoarding: a review.

PubMed

Maier, T

2004-11-01

Hoarding is a behavioural abnormity characterized by the excessive collection of poorly usable objects. It is described mainly in association with obsessive-compulsive disorders (OCDs) and in geriatric populations. Yet the literature on the phenomenon is heterogeneous and the notion obviously lacks a consistent definition. This review attempts to describe the psychopathological and clinical spectrum of hoarding and may contribute to clarify its classification. Systematic review and discussion of the literature on hoarding. Hoarding is a complex behavioural phenomenon associated with different mental disorders. The psychopathological structure is variously composed of elements of OCDs, impulse-control disorders, and ritualistic behaviour. Severe self-neglect is a possible consequence of hoarding. Without further specifications the term hoarding is of limited heuristic value and cannot guide therapeutic interventions satisfactorily. The condition needs to be evaluated carefully in every particular case in relation to the aforementioned psychopathological concepts.

Object-based land cover classification based on fusion of multifrequency SAR data and THAICHOTE optical imagery

NASA Astrophysics Data System (ADS)

Sukawattanavijit, Chanika; Srestasathiern, Panu

2017-10-01

Land Use and Land Cover (LULC) information are significant to observe and evaluate environmental change. LULC classification applying remotely sensed data is a technique popularly employed on a global and local dimension particularly, in urban areas which have diverse land cover types. These are essential components of the urban terrain and ecosystem. In the present, object-based image analysis (OBIA) is becoming widely popular for land cover classification using the high-resolution image. COSMO-SkyMed SAR data was fused with THAICHOTE (namely, THEOS: Thailand Earth Observation Satellite) optical data for land cover classification using object-based. This paper indicates a comparison between object-based and pixel-based approaches in image fusion. The per-pixel method, support vector machines (SVM) was implemented to the fused image based on Principal Component Analysis (PCA). For the objectbased classification was applied to the fused images to separate land cover classes by using nearest neighbor (NN) classifier. Finally, the accuracy assessment was employed by comparing with the classification of land cover mapping generated from fused image dataset and THAICHOTE image. The object-based data fused COSMO-SkyMed with THAICHOTE images demonstrated the best classification accuracies, well over 85%. As the results, an object-based data fusion provides higher land cover classification accuracy than per-pixel data fusion.

Literature survey for suppression of scattered light in large space telescopes

NASA Technical Reports Server (NTRS)

Tifft, W. G.; Fannin, B. B.

1973-01-01

A literature survey is presented of articles dealing with all aspects of predicting, measuring, and controlling unwanted scattered (stray) light. The survey is divided into four broad classifications: (1) existing baffle/telescope designs; (2) computer programs for the analysis/design of light suppression systems; (3) the mechanism, measurement, and control of light scattering; and (4) the advantages and problems introduced by the space environment for the operation of diffraction-limited optical systems.

Discovering semantic features in the literature: a foundation for building functional associations

PubMed Central

Chagoyen, Monica; Carmona-Saez, Pedro; Shatkay, Hagit; Carazo, Jose M; Pascual-Montano, Alberto

2006-01-01

Background Experimental techniques such as DNA microarray, serial analysis of gene expression (SAGE) and mass spectrometry proteomics, among others, are generating large amounts of data related to genes and proteins at different levels. As in any other experimental approach, it is necessary to analyze these data in the context of previously known information about the biological entities under study. The literature is a particularly valuable source of information for experiment validation and interpretation. Therefore, the development of automated text mining tools to assist in such interpretation is one of the main challenges in current bioinformatics research. Results We present a method to create literature profiles for large sets of genes or proteins based on common semantic features extracted from a corpus of relevant documents. These profiles can be used to establish pair-wise similarities among genes, utilized in gene/protein classification or can be even combined with experimental measurements. Semantic features can be used by researchers to facilitate the understanding of the commonalities indicated by experimental results. Our approach is based on non-negative matrix factorization (NMF), a machine-learning algorithm for data analysis, capable of identifying local patterns that characterize a subset of the data. The literature is thus used to establish putative relationships among subsets of genes or proteins and to provide coherent justification for this clustering into subsets. We demonstrate the utility of the method by applying it to two independent and vastly different sets of genes. Conclusion The presented method can create literature profiles from documents relevant to sets of genes. The representation of genes as additive linear combinations of semantic features allows for the exploration of functional associations as well as for clustering, suggesting a valuable methodology for the validation and interpretation of high-throughput experimental data. PMID:16438716

Object based image analysis for the classification of the growth stages of Avocado crop, in Michoacán State, Mexico

NASA Astrophysics Data System (ADS)

Gao, Yan; Marpu, Prashanth; Morales Manila, Luis M.

2014-11-01

This paper assesses the suitability of 8-band Worldview-2 (WV2) satellite data and object-based random forest algorithm for the classification of avocado growth stages in Mexico. We tested both pixel-based with minimum distance (MD) and maximum likelihood (MLC) and object-based with Random Forest (RF) algorithm for this task. Training samples and verification data were selected by visual interpreting the WV2 images for seven thematic classes: fully grown, middle stage, and early stage of avocado crops, bare land, two types of natural forests, and water body. To examine the contribution of the four new spectral bands of WV2 sensor, all the tested classifications were carried out with and without the four new spectral bands. Classification accuracy assessment results show that object-based classification with RF algorithm obtained higher overall higher accuracy (93.06%) than pixel-based MD (69.37%) and MLC (64.03%) method. For both pixel-based and object-based methods, the classifications with the four new spectral bands (overall accuracy obtained higher accuracy than those without: overall accuracy of object-based RF classification with vs without: 93.06% vs 83.59%, pixel-based MD: 69.37% vs 67.2%, pixel-based MLC: 64.03% vs 36.05%, suggesting that the four new spectral bands in WV2 sensor contributed to the increase of the classification accuracy.

A comprehensive analysis of earthquake damage patterns using high dimensional model representation feature selection

NASA Astrophysics Data System (ADS)

Taşkin Kaya, Gülşen

2013-10-01

Recently, earthquake damage assessment using satellite images has been a very popular ongoing research direction. Especially with the availability of very high resolution (VHR) satellite images, a quite detailed damage map based on building scale has been produced, and various studies have also been conducted in the literature. As the spatial resolution of satellite images increases, distinguishability of damage patterns becomes more cruel especially in case of using only the spectral information during classification. In order to overcome this difficulty, textural information needs to be involved to the classification to improve the visual quality and reliability of damage map. There are many kinds of textural information which can be derived from VHR satellite images depending on the algorithm used. However, extraction of textural information and evaluation of them have been generally a time consuming process especially for the large areas affected from the earthquake due to the size of VHR image. Therefore, in order to provide a quick damage map, the most useful features describing damage patterns needs to be known in advance as well as the redundant features. In this study, a very high resolution satellite image after Iran, Bam earthquake was used to identify the earthquake damage. Not only the spectral information, textural information was also used during the classification. For textural information, second order Haralick features were extracted from the panchromatic image for the area of interest using gray level co-occurrence matrix with different size of windows and directions. In addition to using spatial features in classification, the most useful features representing the damage characteristic were selected with a novel feature selection method based on high dimensional model representation (HDMR) giving sensitivity of each feature during classification. The method called HDMR was recently proposed as an efficient tool to capture the input-output relationships in high-dimensional systems for many problems in science and engineering. The HDMR method is developed to improve the efficiency of the deducing high dimensional behaviors. The method is formed by a particular organization of low dimensional component functions, in which each function is the contribution of one or more input variables to the output variables.

Unravelling the myotonic dystrophy type 1 clinical spectrum: A systematic registry-based study with implications for disease classification.

PubMed

De Antonio, M; Dogan, C; Hamroun, D; Mati, M; Zerrouki, S; Eymard, B; Katsahian, S; Bassez, G

2016-10-01

The broad clinical spectrum of myotonic dystrophy type 1 (DM1) creates particular challenges for both medical care and design of clinical trials. Clinical onset spans a continuum from birth to late adulthood, with symptoms that are highly variable in both severity and nature of the affected organ systems. In the literature, this complex phenotype is divided into three grades (mild, classic, and severe) and four or five main clinical categories (congenital, infantile/juvenile, adult-onset and late-onset forms), according to symptom severity and age of onset, respectively. However, these classifications are still under discussion with no consensus thus far. While some specific clinical features have been primarily reported in some forms of the disease, there are no clear distinctions. As a consequence, no modifications in the management of healthcare or the design of clinical studies have been proposed based on the clinical form of DM1. The present study has used the DM-Scope registry to assess, in a large cohort of DM1 patients, the robustness of a classification divided into five clinical forms. Our main aim was to describe the disease spectrum and investigate features of each clinical form. The five subtypes were compared by distribution of CTG expansion size, and the occurrence and onset of the main symptoms of DM1. Analyses validated the relevance of a five-grade model for DM1 classification. Patients were classified as: congenital (n=93, 4.5%); infantile (n=303, 14.8%); juvenile (n=628, 30.7%); adult (n=694, 34.0%); and late-onset (n=326, 15.9%). Our data show that the assumption of a continuum from congenital to the late-onset form is valid, and also highlights disease features specific to individual clinical forms of DM1 in terms of symptom occurrence and chronology throughout the disease course. These results support the use of the five-grade model for disease classification, and the distinct clinical profiles suggest that age of onset and clinical form may be key criteria in the design of clinical trials when considering DM1 health management and research. Copyright © 2016 Elsevier Masson SAS. All rights reserved.

Noncoding sequence classification based on wavelet transform analysis: part I

NASA Astrophysics Data System (ADS)

Paredes, O.; Strojnik, M.; Romo-Vázquez, R.; Vélez Pérez, H.; Ranta, R.; Garcia-Torales, G.; Scholl, M. K.; Morales, J. A.

2017-09-01

DNA sequences in human genome can be divided into the coding and noncoding ones. Coding sequences are those that are read during the transcription. The identification of coding sequences has been widely reported in literature due to its much-studied periodicity. Noncoding sequences represent the majority of the human genome. They play an important role in gene regulation and differentiation among the cells. However, noncoding sequences do not exhibit periodicities that correlate to their functions. The ENCODE (Encyclopedia of DNA elements) and Epigenomic Roadmap Project projects have cataloged the human noncoding sequences into specific functions. We study characteristics of noncoding sequences with wavelet analysis of genomic signals.

Use of theory in computer-based interventions to reduce alcohol use among adolescents and young adults: a systematic review.

PubMed

Tebb, Kathleen P; Erenrich, Rebecca K; Jasik, Carolyn Bradner; Berna, Mark S; Lester, James C; Ozer, Elizabeth M

2016-06-17

Alcohol use and binge drinking among adolescents and young adults remain frequent causes of preventable injuries, disease, and death, and there has been growing attention to computer-based modes of intervention delivery to prevent/reduce alcohol use. Research suggests that health interventions grounded in established theory are more effective than those with no theoretical basis. The goal of this study was to conduct a literature review of computer-based interventions (CBIs) designed to address alcohol use among adolescents and young adults (aged 12-21 years) and examine the extent to which CBIs use theories of behavior change in their development and evaluations. This study also provides an update on extant CBIs addressing alcohol use among youth and their effectiveness. Between November and December of 2014, a literature review of CBIs aimed at preventing or reducing alcohol in PsychINFO, PubMed, and Google Scholar was conducted. The use of theory in each CBI was examined using a modified version of the classification system developed by Painter et al. (Ann Behav Med 35:358-362, 2008). The search yielded 600 unique articles, 500 were excluded because they did not meet the inclusion criteria. The 100 remaining articles were retained for analyses. Many articles were written about a single intervention; thus, the search revealed a total of 42 unique CBIs. In examining the use of theory, 22 CBIs (52 %) explicitly named one or more theoretical frameworks. Primary theories mentioned were social cognitive theory, transtheoretical model, theory of planned behavior and reasoned action, and health belief model. Less than half (48 %), did not use theory, but mentioned either use of a theoretical construct (such as self-efficacy) or an intervention technique (e.g., manipulating social norms). Only a few articles provided detailed information about how the theory was applied to the CBI; the vast majority included little to no information. Given the importance of theory in guiding interventions, greater emphasis on the selection and application of theory is needed. The classification system used in this review offers a guiding framework for reporting how theory based principles can be applied to computer based interventions.

Prediction of cell penetrating peptides by support vector machines.

PubMed

Sanders, William S; Johnston, C Ian; Bridges, Susan M; Burgess, Shane C; Willeford, Kenneth O

2011-07-01

Cell penetrating peptides (CPPs) are those peptides that can transverse cell membranes to enter cells. Once inside the cell, different CPPs can localize to different cellular components and perform different roles. Some generate pore-forming complexes resulting in the destruction of cells while others localize to various organelles. Use of machine learning methods to predict potential new CPPs will enable more rapid screening for applications such as drug delivery. We have investigated the influence of the composition of training datasets on the ability to classify peptides as cell penetrating using support vector machines (SVMs). We identified 111 known CPPs and 34 known non-penetrating peptides from the literature and commercial vendors and used several approaches to build training data sets for the classifiers. Features were calculated from the datasets using a set of basic biochemical properties combined with features from the literature determined to be relevant in the prediction of CPPs. Our results using different training datasets confirm the importance of a balanced training set with approximately equal number of positive and negative examples. The SVM based classifiers have greater classification accuracy than previously reported methods for the prediction of CPPs, and because they use primary biochemical properties of the peptides as features, these classifiers provide insight into the properties needed for cell-penetration. To confirm our SVM classifications, a subset of peptides classified as either penetrating or non-penetrating was selected for synthesis and experimental validation. Of the synthesized peptides predicted to be CPPs, 100% of these peptides were shown to be penetrating.

Considerations for a Pediatric Biopharmaceutics Classification System (BCS): application to five drugs.

PubMed

Gandhi, Shivani V; Rodriguez, William; Khan, Mansoor; Polli, James E

2014-06-01

It has been advocated that biopharmaceutic risk assessment should be conducted early in pediatric product development and synchronized with the adult product development program. However, we are unaware of efforts to classify drugs into a Biopharmaceutics Classification System (BCS) framework for pediatric patients. The objective was to classify five drugs into a potential BCS. These five drugs were selected since both oral and intravenous pharmacokinetic data were available for each drug, and covered the four BCS classes in adults. Literature searches for each drug were conducted using Medline and applied to classify drugs with respect to solubility and permeability in pediatric subpopulations. Four pediatric subpopulations were considered: neonates, infants, children, and adolescents. Regarding solubility, dose numbers were calculated using a volume for each subpopulation based on body surface area (BSA) relative to 250 ml for a 1.73 m(2) adult. Dose numbers spanned a range of values, depending upon the pediatric dose formula and subpopulation. Regarding permeability, pharmacokinetic literature data required assumptions and decisions about data collection. Using a devised pediatric BCS framework, there was agreement in adult and pediatric BCS class for two drugs, azithromycin (class 3) and ciprofloxacin (class 4). There was discordance for the three drugs that have high adult permeability since all pediatric permeabilities were low: dolasetron (class 3 in pediatric), ketoprofen (class 4 in pediatric), and voriconazole (class 4 in pediatric). A main contribution of this work is the identification of critical factors required for a pediatric BCS.

Innovative vehicle classification strategies : using LIDAR to do more for less.

DOT National Transportation Integrated Search

2012-06-23

This study examines LIDAR (light detection and ranging) based vehicle classification and classification : performance monitoring. First, we develop a portable LIDAR based vehicle classification system that can : be rapidly deployed, and then we use t...

[The possible drawbacks of applying the DRG classification].

PubMed

Huber, Zofia Swinarski

2006-09-06

The objective of this article is to present the difficulties linked to the measure and use of the Diagnosis Related Group (DRG) as part of a hospital's production and management accounting evaluation system. We will present here all the criticisms brought forth in management literature against DRG classifications. The article isn't intended to argue against and to push people to reconsider the tool but rather to attract the attention of politicians and hospital managers to all the possible difficulties and outcomes that could be generated by the DRG, this in terms of either the AP-DRG or the German-DRG, the latter being the classification that has been adopted in Switzerland as the basis for the construction of the future Swiss-DRG.

Classification of Computer-Aided Design-Computer-Aided Manufacturing Applications for the Reconstruction of Cranio-Maxillo-Facial Defects.

PubMed

Wauters, Lauri D J; Miguel-Moragas, Joan San; Mommaerts, Maurice Y

2015-11-01

To gain insight into the methodology of different computer-aided design-computer-aided manufacturing (CAD-CAM) applications for the reconstruction of cranio-maxillo-facial (CMF) defects. We reviewed and analyzed the available literature pertaining to CAD-CAM for use in CMF reconstruction. We proposed a classification system of the techniques of implant and cutting, drilling, and/or guiding template design and manufacturing. The system consisted of 4 classes (I-IV). These classes combine techniques used for both the implant and template to most accurately describe the methodology used. Our classification system can be widely applied. It should facilitate communication and immediate understanding of the methodology of CAD-CAM applications for the reconstruction of CMF defects.

Temporomandibular Disorders (TMD) in Edentulous Patients: A Review and Proposed Classification (Dr. Bader’s Classification).

PubMed Central

2015-01-01

Temporomandibular disorders (TMD) are a collective term given to a number of clinical problems that involve the masticatory musculature, the temporomandibular joints and associated structures, or both. Although the aetiology of TMD has not been fully understood, in general it is considered to be multifactorial. The signs and symptoms of TMD which present in patients with natural teeth may also occur in edentulous patients. These symptoms may appear in various combinations and degrees. TMD has attained a prominent role within the context of dental care due to its high prevalence. The present paper is a review of the current literature on TMD in edentulous patients; with an attempt to propose a classification for the same. PMID:26023660

Molecular classifications of breast carcinoma with similar terminology and different definitions: are they the same?

PubMed

Tang, Ping; Wang, Jianmin; Bourne, Patria

2008-04-01

There are 4 major molecular classifications in the literature that divide breast carcinoma into basal and nonbasal subtypes, with basal subtypes associated with poor prognosis. Basal subtype is defined as positive for cytokeratin (CK) 5/6, CK14, and/or CK17 in CK classification; negative for ER, PR, and HER2 in triple negative (TN) classification; negative for ER and negative or positive for HER2 in ER/HER2 classification; and positive for CK5/6, CK14, CK17, and/or EGFR; and negative for ER, PR, and HER2 in CK/TN classification. These classifications use similar terminology but different definitions; it is critical to understand the precise relationship between them. We compared these 4 classifications in 195 breast carcinomas and found that (1) the rates of basal subtypes varied from 5% to 36% for ductal carcinoma in situ and 14% to 40% for invasive ductal carcinoma. (2) The rates of basal subtypes varied from 19% to 76% for HG carcinoma and 1% to 7% for NHG carcinoma. (3) The rates of basal subtypes were strongly associated with tumor grades (P < .001) in all classifications and associated with tumor types (in situ versus invasive ductal carcinomas) in TN (P < .001) and CK/TN classifications (P = .035). (4) These classifications were related but not interchangeable (kappa ranges from 0.140 to 0.658 for HG carcinoma and from 0.098 to 0.654 for NHG carcinoma). In conclusion, although these classifications all divide breast carcinoma into basal and nonbasal subtypes, they are not interchangeable. More studies are needed to evaluate to their values in predicting prognosis and guiding individualized therapy.

Proposed Core Competencies and Empirical Validation Procedure in Competency Modeling: Confirmation and Classification

PubMed Central

Baczyńska, Anna K.; Rowiński, Tomasz; Cybis, Natalia

2016-01-01

Competency models provide insight into key skills which are common to many positions in an organization. Moreover, there is a range of competencies that is used by many companies. Researchers have developed core competency terminology to underline their cross-organizational value. The article presents a theoretical model of core competencies consisting of two main higher-order competencies called performance and entrepreneurship. Each of them consists of three elements: the performance competency includes cooperation, organization of work and goal orientation, while entrepreneurship includes innovativeness, calculated risk-taking and pro-activeness. However, there is lack of empirical validation of competency concepts in organizations and this would seem crucial for obtaining reliable results from organizational research. We propose a two-step empirical validation procedure: (1) confirmation factor analysis, and (2) classification of employees. The sample consisted of 636 respondents (M = 44.5; SD = 15.1). Participants were administered a questionnaire developed for the study purpose. The reliability, measured by Cronbach’s alpha, ranged from 0.60 to 0.83 for six scales. Next, we tested the model using a confirmatory factor analysis. The two separate, single models of performance and entrepreneurial orientations fit quite well to the data, while a complex model based on the two single concepts needs further research. In the classification of employees based on the two higher order competencies we obtained four main groups of employees. Their profiles relate to those found in the literature, including so-called niche finders and top performers. Some proposal for organizations is discussed. PMID:27014111

New classification system for indications for endoscopic retrograde cholangiopancreatography predicts diagnoses and adverse events.

PubMed

Yuen, Nicholas; O'Shaughnessy, Pauline; Thomson, Andrew

2017-12-01

Indications for endoscopic retrograde cholangiopancreatography (ERCP) have received little attention, especially in scientific or objective terms. To review the prevailing ERCP indications in the literature, and to propose and evaluate a new ERCP indication system, which relies on more objective pre-procedure parameters. An analysis was conducted on 1758 consecutive ERCP procedures, in which contemporaneous use was made of an a-priori indication system. Indications were based on the objective pre-procedure parameters and divided into primary [cholangitis, clinical evidence of biliary leak, acute (biliary) pancreatitis, abnormal intraoperative cholangiogram (IOC), or change/removal of stent for benign/malignant disease] and secondary [combination of two or three of: pain attributable to biliary disease ('P'), imaging evidence of biliary disease ('I'), and abnormal liver function tests (LFTs) ('L')]. A secondary indication was only used if a primary indication was not present. The relationship between this newly developed classification system and ERCP findings and adverse events was examined. The indications of cholangitis and positive IOC were predictive of choledocholithiasis at ERCP (101/154 and 74/141 procedures, respectively). With respect to secondary indications, only if all three of 'P', 'I', and 'L' were present there was a statistically significant association with choledocholithiasis (χ 2 (1) = 35.3, p < .001). Adverse events were associated with an unusual indication leading to greater risk of unplanned hospitalization (χ 2 (1) = 17.0, p < .001). An a-priori-based indication system for ERCP, which relies on pre-ERCP objective parameters, provides a more useful and scientific classification system than is available currently.

Functional gastroduodenal disorders

PubMed Central

Talley, N; Stanghellini, V; Heading, R; Koch, K; Malagelada, J; Tytgat, G

1999-01-01

While widely used in research, the 1991 Rome criteria for the gastroduodenal disorders, especially symptom subgroups in dyspepsia, remain contentious. After a comprehensive literature search, a consensus-based approach was applied, supplemented by input from international experts who reviewed the report. Three functional gastroduodenal disorders are defined. Functional dyspepsia is persistent or recurrent pain or discomfort centered in the upper abdomen; evidence of organic disease likely to explain the symptoms is absent, including at upper endoscopy. Discomfort refers to a subjective, negative feeling that may be characterized by or associated with a number of non-painful symptoms including upper abdominal fullness, early satiety, bloating, or nausea. A dyspepsia subgroup classification is proposed for research purposes, based on the predominant (most bothersome) symptom: (a) ulcer-like dyspepsia when pain (from mild to severe) is the predominant symptom, and (b) dysmotility-like dyspepsia when discomfort (not pain) is the predominant symptom. This classification is supported by recent evidence suggesting that predominant symptoms, but not symptom clusters, identify subgroups with distinct underlying pathophysiological disturbances and responses to treatment. Aerophagia is an unusual complaint characterized by air swallowing that is objectively observed and troublesome repetitive belching. Functional vomiting refers to frequent episodes of recurrent vomiting that is not self-induced nor medication induced, and occurs in the absence of eating disorders, major psychiatric diseases, abnormalities in the gut or central nervous system, or metabolic diseases that can explain the symptom. The current classification requires careful validation but the criteria should be of value in future research.


Keywords: dyspepsia; functional dyspepsia; aerophagia; psychogenic vomiting; Rome II PMID:10457043

Posture Detection Based on Smart Cushion for Wheelchair Users

PubMed Central

Ma, Congcong; Li, Wenfeng; Gravina, Raffaele; Fortino, Giancarlo

2017-01-01

The postures of wheelchair users can reveal their sitting habit, mood, and even predict health risks such as pressure ulcers or lower back pain. Mining the hidden information of the postures can reveal their wellness and general health conditions. In this paper, a cushion-based posture recognition system is used to process pressure sensor signals for the detection of user’s posture in the wheelchair. The proposed posture detection method is composed of three main steps: data level classification for posture detection, backward selection of sensor configuration, and recognition results compared with previous literature. Five supervised classification techniques—Decision Tree (J48), Support Vector Machines (SVM), Multilayer Perceptron (MLP), Naive Bayes, and k-Nearest Neighbor (k-NN)—are compared in terms of classification accuracy, precision, recall, and F-measure. Results indicate that the J48 classifier provides the highest accuracy compared to other techniques. The backward selection method was used to determine the best sensor deployment configuration of the wheelchair. Several kinds of pressure sensor deployments are compared and our new method of deployment is shown to better detect postures of the wheelchair users. Performance analysis also took into account the Body Mass Index (BMI), useful for evaluating the robustness of the method across individual physical differences. Results show that our proposed sensor deployment is effective, achieving 99.47% posture recognition accuracy. Our proposed method is very competitive for posture recognition and robust in comparison with other former research. Accurate posture detection represents a fundamental basic block to develop several applications, including fatigue estimation and activity level assessment. PMID:28353684

Should the Gross Motor Function Classification System be used for children who do not have cerebral palsy?

PubMed

Towns, Megan; Rosenbaum, Peter; Palisano, Robert; Wright, F Virginia

2018-02-01

This literature review addressed four questions. (1) In which populations other than cerebral palsy (CP) has the Gross Motor Function Classification System (GMFCS) been applied? (2) In what types of study, and why was it used? (3) How was it modified to facilitate these applications? (4) What justifications and evidence of psychometric adequacy were used to support its application? A search of PubMed, MEDLINE, and Embase databases (January 1997 to April 2017) using the terms: 'GMFCS' OR 'Gross Motor Function Classification System' yielded 2499 articles. 118 met inclusion criteria and reported children/adults with 133 health conditions/clinical descriptions other than CP. Three broad GMFCS applications were observed: as a categorization tool, independent variable, or outcome measure. While the GMFCS is widely used for children with health conditions/clinical description other than CP, researchers rarely provided adequate justification for these uses. We offer recommendations for development/validation of other condition-specific classification systems and discuss the potential need for a generic gross motor function classification system. The Gross Motor Function Classification System should not be used outside cerebral palsy or as an outcome measure. The authors provide recommendations for development and validation of condition-specific or generic classification systems. © 2017 Mac Keith Press.

A web-based land cover classification system based on ontology model of different classification systems

NASA Astrophysics Data System (ADS)

Lin, Y.; Chen, X.

2016-12-01

Land cover classification systems used in remote sensing image data have been developed to meet the needs for depicting land covers in scientific investigations and policy decisions. However, accuracy assessments of a spate of data sets demonstrate that compared with the real physiognomy, each of the thematic map of specific land cover classification system contains some unavoidable flaws and unintended deviation. This work proposes a web-based land cover classification system, an integrated prototype, based on an ontology model of various classification systems, each of which is assigned the same weight in the final determination of land cover type. Ontology, a formal explication of specific concepts and relations, is employed in this prototype to build up the connections among different systems to resolve the naming conflicts. The process is initialized by measuring semantic similarity between terminologies in the systems and the search key to produce certain set of satisfied classifications, and carries on through searching the predefined relations in concepts of all classification systems to generate classification maps with user-specified land cover type highlighted, based on probability calculated by votes from data sets with different classification system adopted. The present system is verified and validated by comparing the classification results with those most common systems. Due to full consideration and meaningful expression of each classification system using ontology and the convenience that the web brings with itself, this system, as a preliminary model, proposes a flexible and extensible architecture for classification system integration and data fusion, thereby providing a strong foundation for the future work.

Automated Patent Categorization and Guided Patent Search using IPC as Inspired by MeSH and PubMed.

PubMed

Eisinger, Daniel; Tsatsaronis, George; Bundschus, Markus; Wieneke, Ulrich; Schroeder, Michael

2013-04-15

Document search on PubMed, the pre-eminent database for biomedical literature, relies on the annotation of its documents with relevant terms from the Medical Subject Headings ontology (MeSH) for improving recall through query expansion. Patent documents are another important information source, though they are considerably less accessible. One option to expand patent search beyond pure keywords is the inclusion of classification information: Since every patent is assigned at least one class code, it should be possible for these assignments to be automatically used in a similar way as the MeSH annotations in PubMed. In order to develop a system for this task, it is necessary to have a good understanding of the properties of both classification systems. This report describes our comparative analysis of MeSH and the main patent classification system, the International Patent Classification (IPC). We investigate the hierarchical structures as well as the properties of the terms/classes respectively, and we compare the assignment of IPC codes to patents with the annotation of PubMed documents with MeSH terms.Our analysis shows a strong structural similarity of the hierarchies, but significant differences of terms and annotations. The low number of IPC class assignments and the lack of occurrences of class labels in patent texts imply that current patent search is severely limited. To overcome these limits, we evaluate a method for the automated assignment of additional classes to patent documents, and we propose a system for guided patent search based on the use of class co-occurrence information and external resources.

Chronic Mastitis in Egypt and Morocco: differentiating between idiopathic granulomatous mastitis and IgG4-related disease

PubMed Central

Allen, Steven G.; Soliman, Amr S.; Toy, Kathleen; Omar, Omar S.; Youssef, Tamer; Karkouri, Mehdi; Ayad, Essam; Abdel-Aziz, Azza; Hablas, Ahmed; Tahri, Ali; Oltean, Hanna N.; Kleer, Celina G.; Merajver, Sofia D.

2016-01-01

Idiopathic granulomatous mastitis (IGM) is a benign, frequently severe chronic inflammatory lesion of the breast. Its etiology remains unknown and reported cases vary in their presentation and histologic findings with an optimal treatment algorithm yet to be described owing mainly to the disease’s heterogeneity. IgG4-related disease (IgG4-RD) is a newly recognized systemic fibroinflammatory condition characterized by a dense lymphoplasmacytic infiltrate with many IgG4-positive plasma cells, storiform fibrosis, and obliterative phlebitis. Immunosuppressive therapy is considered to be an effective first-line therapy for IgG4-RD. We sought to clarify and classify chronic mastitis according to the histologic findings of IgG4-RD mastitis with respect to IGM and to develop a robust diagnostic framework to help select patients for optimal treatment strategies. Using the largest collection to date (43 cases from Egypt and Morocco), we show that despite sharing many features, IGM and IgG4-RD mastitis are separate diseases. To diagnostically separate the diseases, we created a classification schema – termed the Michigan Classification – based upon our large series of cases, the consensus statement on IgG4-RD, and the histologic description of IGM in the literature. Using our classification, we discerned 17 cases of IgG4-RD and 8 cases of IGM among the 43 chronic mastitis cases, with 18 indeterminate cases. Thus our Michigan Classification can form the basis of rational stratification of chronic mastitis patients between these two clinically and histopathologically heterogeneous diseases. PMID:27279578

Automated Patent Categorization and Guided Patent Search using IPC as Inspired by MeSH and PubMed

PubMed Central

2013-01-01

Document search on PubMed, the pre-eminent database for biomedical literature, relies on the annotation of its documents with relevant terms from the Medical Subject Headings ontology (MeSH) for improving recall through query expansion. Patent documents are another important information source, though they are considerably less accessible. One option to expand patent search beyond pure keywords is the inclusion of classification information: Since every patent is assigned at least one class code, it should be possible for these assignments to be automatically used in a similar way as the MeSH annotations in PubMed. In order to develop a system for this task, it is necessary to have a good understanding of the properties of both classification systems. This report describes our comparative analysis of MeSH and the main patent classification system, the International Patent Classification (IPC). We investigate the hierarchical structures as well as the properties of the terms/classes respectively, and we compare the assignment of IPC codes to patents with the annotation of PubMed documents with MeSH terms. Our analysis shows a strong structural similarity of the hierarchies, but significant differences of terms and annotations. The low number of IPC class assignments and the lack of occurrences of class labels in patent texts imply that current patent search is severely limited. To overcome these limits, we evaluate a method for the automated assignment of additional classes to patent documents, and we propose a system for guided patent search based on the use of class co-occurrence information and external resources. PMID:23734562

Anorexia Nervosa and Bulimia.

ERIC Educational Resources Information Center

Csapo, Marg

1987-01-01

The article reviews the literature on anorexia nervosa, with or without bulimia, and presents a comprehensive picture of this eating disorder, focusing on terminology, historical references, prevalence, prognosis, classification, diagnostic criteria, physical and psychological characteristics, evolution of the disability, etiology, treatment, and…

A Method of Spatial Mapping and Reclassification for High-Spatial-Resolution Remote Sensing Image Classification

PubMed Central

Wang, Guizhou; Liu, Jianbo; He, Guojin

2013-01-01

This paper presents a new classification method for high-spatial-resolution remote sensing images based on a strategic mechanism of spatial mapping and reclassification. The proposed method includes four steps. First, the multispectral image is classified by a traditional pixel-based classification method (support vector machine). Second, the panchromatic image is subdivided by watershed segmentation. Third, the pixel-based multispectral image classification result is mapped to the panchromatic segmentation result based on a spatial mapping mechanism and the area dominant principle. During the mapping process, an area proportion threshold is set, and the regional property is defined as unclassified if the maximum area proportion does not surpass the threshold. Finally, unclassified regions are reclassified based on spectral information using the minimum distance to mean algorithm. Experimental results show that the classification method for high-spatial-resolution remote sensing images based on the spatial mapping mechanism and reclassification strategy can make use of both panchromatic and multispectral information, integrate the pixel- and object-based classification methods, and improve classification accuracy. PMID:24453808

Compliance monitoring in business processes: Functionalities, application, and tool-support.

PubMed

Ly, Linh Thao; Maggi, Fabrizio Maria; Montali, Marco; Rinderle-Ma, Stefanie; van der Aalst, Wil M P

2015-12-01

In recent years, monitoring the compliance of business processes with relevant regulations, constraints, and rules during runtime has evolved as major concern in literature and practice. Monitoring not only refers to continuously observing possible compliance violations, but also includes the ability to provide fine-grained feedback and to predict possible compliance violations in the future. The body of literature on business process compliance is large and approaches specifically addressing process monitoring are hard to identify. Moreover, proper means for the systematic comparison of these approaches are missing. Hence, it is unclear which approaches are suitable for particular scenarios. The goal of this paper is to define a framework for Compliance Monitoring Functionalities (CMF) that enables the systematic comparison of existing and new approaches for monitoring compliance rules over business processes during runtime. To define the scope of the framework, at first, related areas are identified and discussed. The CMFs are harvested based on a systematic literature review and five selected case studies. The appropriateness of the selection of CMFs is demonstrated in two ways: (a) a systematic comparison with pattern-based compliance approaches and (b) a classification of existing compliance monitoring approaches using the CMFs. Moreover, the application of the CMFs is showcased using three existing tools that are applied to two realistic data sets. Overall, the CMF framework provides powerful means to position existing and future compliance monitoring approaches.

Compliance monitoring in business processes: Functionalities, application, and tool-support

PubMed Central

Ly, Linh Thao; Maggi, Fabrizio Maria; Montali, Marco; Rinderle-Ma, Stefanie; van der Aalst, Wil M.P.

2015-01-01

In recent years, monitoring the compliance of business processes with relevant regulations, constraints, and rules during runtime has evolved as major concern in literature and practice. Monitoring not only refers to continuously observing possible compliance violations, but also includes the ability to provide fine-grained feedback and to predict possible compliance violations in the future. The body of literature on business process compliance is large and approaches specifically addressing process monitoring are hard to identify. Moreover, proper means for the systematic comparison of these approaches are missing. Hence, it is unclear which approaches are suitable for particular scenarios. The goal of this paper is to define a framework for Compliance Monitoring Functionalities (CMF) that enables the systematic comparison of existing and new approaches for monitoring compliance rules over business processes during runtime. To define the scope of the framework, at first, related areas are identified and discussed. The CMFs are harvested based on a systematic literature review and five selected case studies. The appropriateness of the selection of CMFs is demonstrated in two ways: (a) a systematic comparison with pattern-based compliance approaches and (b) a classification of existing compliance monitoring approaches using the CMFs. Moreover, the application of the CMFs is showcased using three existing tools that are applied to two realistic data sets. Overall, the CMF framework provides powerful means to position existing and future compliance monitoring approaches. PMID:26635430

Recent revisions of phosphate rock reserves and resources: a critique

NASA Astrophysics Data System (ADS)

Edixhoven, J. D.; Gupta, J.; Savenije, H. H. G.

2014-12-01

Phosphate rock (PR) is a finite mineral indispensable for fertilizer production, while P (phosphorus) is a major pollutant if applied or discharged in excess, causing widespread eutrophication (Carpenter and Bennet, 2011). High-grade PR is obtained from deposits which took millions of years to form and which are gradually being depleted. Recently, global PR reserves as reported by the US Geological Survey (USGS) have increased from 16 000 Mt PR in 2010 to 65 000 Mt PR in 2011 and further to 67 000 Mt PR in 2014. The majority of this 4-fold increase is based on a 2010 report by the International Fertilizer Development Center (IFDC), which increased Moroccan reserves from 5700 Mt PR as reported by USGS, to 51 000 Mt PR, reported as upgraded ("beneficiated") concentrate. The report also increased global resources from 163 000 Mt PR reported in the literature in 1989 to 290 000 Mt PR. IFDC used a simplified resource terminology which does not use the underlying thresholds for reserves and resources used in the USGS classification. IFDC proposed that agreement should be reached on PR resource terminology which should be as simple as possible. The report has profoundly influenced the PR scarcity debate, shifting the emphasis from resource scarcity to the pollution angle of the phosphate problem. In view of the high dependence of food production on PR and the importance of data on PR reserves and resources for scientific analysis and policy making, data on PR deposits should be transparent, comparable, reliable, and credible. We analyze (i) how IFDC's simplified terminology compares to international best practice in resource classification and whether it is likely to yield data that meet these requirements, (ii) whether the difference in volume between raw PR ore and upgraded PR concentrate is sufficiently noted in the literature, and (iii) whether the IFDC report presents an accurate picture of PR reserves and resources. We conclude that, while there is a global development toward common criteria in resource reporting, IFDC's lack of clear thresholds for reserves and resources contravenes this and that the vagueness of its definitions for reserves and resources may allow deposits to be termed reserves or resources which could not be recognized as such under leading mineral resource classifications. The difference between PR ore and PR concentrate is barely noted in the literature, causing pervasive confusion and a significant degree of error in many assessments. Finally, we find that the report most likely presents an inflated picture of global reserves, in particular those of Morocco, where the aggregate resources of three of the four Moroccan/Western Saharan major PR deposits appear to have been simply converted to "reserves". Following the release of the IFDC report, various analysts have concluded or suggested that the available PR deposits or even the currently reported resources would likely last several thousands of years at current consumption rates. However, the data on which these statements were based do not appear to warrant such a conclusion. Further research is required as to the quantity of PR deposits and their viability for future extraction, using uniform and transparent classification terminology.

Classification of weld defect based on information fusion technology for radiographic testing system

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jiang, Hongquan; Liang, Zeming, E-mail: heavenlzm@126.com; Gao, Jianmin

Improving the efficiency and accuracy of weld defect classification is an important technical problem in developing the radiographic testing system. This paper proposes a novel weld defect classification method based on information fusion technology, Dempster–Shafer evidence theory. First, to characterize weld defects and improve the accuracy of their classification, 11 weld defect features were defined based on the sub-pixel level edges of radiographic images, four of which are presented for the first time in this paper. Second, we applied information fusion technology to combine different features for weld defect classification, including a mass function defined based on the weld defectmore » feature information and the quartile-method-based calculation of standard weld defect class which is to solve a sample problem involving a limited number of training samples. A steam turbine weld defect classification case study is also presented herein to illustrate our technique. The results show that the proposed method can increase the correct classification rate with limited training samples and address the uncertainties associated with weld defect classification.« less

Classification of weld defect based on information fusion technology for radiographic testing system.

PubMed

Jiang, Hongquan; Liang, Zeming; Gao, Jianmin; Dang, Changying

2016-03-01

Improving the efficiency and accuracy of weld defect classification is an important technical problem in developing the radiographic testing system. This paper proposes a novel weld defect classification method based on information fusion technology, Dempster-Shafer evidence theory. First, to characterize weld defects and improve the accuracy of their classification, 11 weld defect features were defined based on the sub-pixel level edges of radiographic images, four of which are presented for the first time in this paper. Second, we applied information fusion technology to combine different features for weld defect classification, including a mass function defined based on the weld defect feature information and the quartile-method-based calculation of standard weld defect class which is to solve a sample problem involving a limited number of training samples. A steam turbine weld defect classification case study is also presented herein to illustrate our technique. The results show that the proposed method can increase the correct classification rate with limited training samples and address the uncertainties associated with weld defect classification.

An Evaluative Study of the Navy Medical Department’s Patient Classification System and Staffing Allocation.

DTIC Science & Technology

1984-08-01

the greatest impact on the modern patient classification system were conducted by R.J. Connor in the late 50’s and early 60’s at Johns *Hopkins...Administration 10 (December 1980): 25-31. Bartko, John J., and Carpenter, W.T. "On the Method and Theory of Reliability." The Journal of Nervous and Mental...Staffing in Acute Care Hospitals: A Review and A Critique of the Literature by J. Young.- P. Giovannetti, D. Lewison , and M.L. Thomas. DHEW Publication

A Computerized English-Spanish Correlation Index to Five Biomedical Library Classification Schemes Based on MeSH*

PubMed Central

Muench, Eugene V.

1971-01-01

A computerized English/Spanish correlation index to five biomedical library classification schemes and a computerized English/Spanish, Spanish/English listings of MeSH are described. The index was accomplished by supplying appropriate classification numbers of five classification schemes (National Library of Medicine; Library of Congress; Dewey Decimal; Cunningham; Boston Medical) to MeSH and a Spanish translation of MeSH The data were keypunched, merged on magnetic tape, and sorted in a computer alphabetically by English and Spanish subject headings and sequentially by classification number. Some benefits and uses of the index are: a complete index to classification schemes based on MeSH terms; a tool for conversion of classification numbers when reclassifying collections; a Spanish index and a crude Spanish translation of five classification schemes; a data base for future applications, e.g., automatic classification. Other classification schemes, such as the UDC, and translations of MeSH into other languages can be added. PMID:5172471

[Land cover classification of Four Lakes Region in Hubei Province based on MODIS and ENVISAT data].

PubMed

Xue, Lian; Jin, Wei-Bin; Xiong, Qin-Xue; Liu, Zhang-Yong

2010-03-01

Based on the differences of back scattering coefficient in ENVISAT ASAR data, a classification was made on the towns, waters, and vegetation-covered areas in the Four Lakes Region of Hubei Province. According to the local cropping systems and phenological characteristics in the region, and by using the discrepancies of the MODIS-NDVI index from late April to early May, the vegetation-covered areas were classified into croplands and non-croplands. The classification results based on the above-mentioned procedure was verified by the classification results based on the ETM data with high spatial resolution. Based on the DEM data, the non-croplands were categorized into forest land and bottomland; and based on the discrepancies of mean NDVI index per month, the crops were identified as mid rice, late rice, and cotton, and the croplands were identified as paddy field and upland field. The land cover classification based on the MODIS data with low spatial resolution was basically consistent with that based on the ETM data with high spatial resolution, and the total error rate was about 13.15% when the classification results based on ETM data were taken as the standard. The utilization of the above-mentioned procedures for large scale land cover classification and mapping could make the fast tracking of regional land cover classification.

Comparison of hand-craft feature based SVM and CNN based deep learning framework for automatic polyp classification.

PubMed

Younghak Shin; Balasingham, Ilangko

2017-07-01

Colonoscopy is a standard method for screening polyps by highly trained physicians. Miss-detected polyps in colonoscopy are potential risk factor for colorectal cancer. In this study, we investigate an automatic polyp classification framework. We aim to compare two different approaches named hand-craft feature method and convolutional neural network (CNN) based deep learning method. Combined shape and color features are used for hand craft feature extraction and support vector machine (SVM) method is adopted for classification. For CNN approach, three convolution and pooling based deep learning framework is used for classification purpose. The proposed framework is evaluated using three public polyp databases. From the experimental results, we have shown that the CNN based deep learning framework shows better classification performance than the hand-craft feature based methods. It achieves over 90% of classification accuracy, sensitivity, specificity and precision.

14 CFR 1203.412 - Classification guides.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 14 Aeronautics and Space 5 2013-01-01 2013-01-01 false Classification guides. 1203.412 Section... PROGRAM Guides for Original Classification § 1203.412 Classification guides. (a) General. A classification guide, based upon classification determinations made by appropriate program and classification...

14 CFR 1203.412 - Classification guides.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 14 Aeronautics and Space 5 2012-01-01 2012-01-01 false Classification guides. 1203.412 Section... PROGRAM Guides for Original Classification § 1203.412 Classification guides. (a) General. A classification guide, based upon classification determinations made by appropriate program and classification...

14 CFR 1203.412 - Classification guides.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 14 Aeronautics and Space 5 2011-01-01 2010-01-01 true Classification guides. 1203.412 Section 1203... Guides for Original Classification § 1203.412 Classification guides. (a) General. A classification guide, based upon classification determinations made by appropriate program and classification authorities...

McTwo: a two-step feature selection algorithm based on maximal information coefficient.

PubMed

Ge, Ruiquan; Zhou, Manli; Luo, Youxi; Meng, Qinghan; Mai, Guoqin; Ma, Dongli; Wang, Guoqing; Zhou, Fengfeng

2016-03-23

High-throughput bio-OMIC technologies are producing high-dimension data from bio-samples at an ever increasing rate, whereas the training sample number in a traditional experiment remains small due to various difficulties. This "large p, small n" paradigm in the area of biomedical "big data" may be at least partly solved by feature selection algorithms, which select only features significantly associated with phenotypes. Feature selection is an NP-hard problem. Due to the exponentially increased time requirement for finding the globally optimal solution, all the existing feature selection algorithms employ heuristic rules to find locally optimal solutions, and their solutions achieve different performances on different datasets. This work describes a feature selection algorithm based on a recently published correlation measurement, Maximal Information Coefficient (MIC). The proposed algorithm, McTwo, aims to select features associated with phenotypes, independently of each other, and achieving high classification performance of the nearest neighbor algorithm. Based on the comparative study of 17 datasets, McTwo performs about as well as or better than existing algorithms, with significantly reduced numbers of selected features. The features selected by McTwo also appear to have particular biomedical relevance to the phenotypes from the literature. McTwo selects a feature subset with very good classification performance, as well as a small feature number. So McTwo may represent a complementary feature selection algorithm for the high-dimensional biomedical datasets.