Muscle Injuries in Sports: A New Evidence-Informed and Expert Consensus-Based Classification with Clinical Application.

PubMed

Valle, Xavier; Alentorn-Geli, Eduard; Tol, Johannes L; Hamilton, Bruce; Garrett, William E; Pruna, Ricard; Til, Lluís; Gutierrez, Josep Antoni; Alomar, Xavier; Balius, Ramón; Malliaropoulos, Nikos; Monllau, Joan Carles; Whiteley, Rodney; Witvrouw, Erik; Samuelsson, Kristian; Rodas, Gil

2017-07-01

Muscle injuries are among the most common injuries in sport and continue to be a major concern because of training and competition time loss, challenging decision making regarding treatment and return to sport, and a relatively high recurrence rate. An adequate classification of muscle injury is essential for a full understanding of the injury and to optimize its management and return-to-play process. The ongoing failure to establish a classification system with broad acceptance has resulted from factors such as limited clinical applicability, and the inclusion of subjective findings and ambiguous terminology. The purpose of this article was to describe a classification system for muscle injuries with easy clinical application, adequate grouping of injuries with similar functional impairment, and potential prognostic value. This evidence-informed and expert consensus-based classification system for muscle injuries is based on a four-letter initialism system: MLG-R, respectively referring to the mechanism of injury (M), location of injury (L), grading of severity (G), and number of muscle re-injuries (R). The goal of the classification is to enhance communication between healthcare and sports-related professionals and facilitate rehabilitation and return-to-play decision making.

The history of female genital tract malformation classifications and proposal of an updated system.

PubMed

Acién, Pedro; Acién, Maribel I

2011-01-01

A correct classification of malformations of the female genital tract is essential to prevent unnecessary and inadequate surgical operations and to compare reproductive results. An ideal classification system should be based on aetiopathogenesis and should suggest the appropriate therapeutic strategy. We conducted a systematic review of relevant articles found in PubMed, Scopus, Scirus and ISI webknowledge, and analysis of historical collections of 'female genital malformations' and 'classifications'. Of 124 full-text articles assessed for eligibility, 64 were included because they contained original general, partial or modified classifications. All the existing classifications were analysed and grouped. The unification of terms and concepts was also analysed. Traditionally, malformations of the female genital tract have been catalogued and classified as Müllerian malformations due to agenesis, lack of fusion, the absence of resorption and lack of posterior development of the Müllerian ducts. The American Fertility Society classification of the late 1980s included seven basic groups of malformations also considering the Müllerian development and the relationship of the malformations to fertility. Other classifications are based on different aspects: functional, defects in vertical fusion, embryological or anatomical (Vagina, Cervix, Uterus, Adnex and Associated Malformation: VCUAM classification). However, an embryological-clinical classification system seems to be the most appropriate. Accepting the need for a new classification system of genitourinary malformations that considers the experience gained from the application of the current classification systems, the aetiopathogenesis and that also suggests the appropriate treatment, we proposed an update of our embryological-clinical classification as a new system with six groups of female genitourinary anomalies.

Poststernotomy mediastinitis: a classification to initiate and evaluate reconstructive management based on evidence from a structured review.

PubMed

van Wingerden, Jan J; Ubbink, Dirk T; van der Horst, Chantal M A M; de Mol, Bas A J M

2014-11-23

Early recognition and, where possible, avoidance of risk factors that contribute to the development of poststernotomy mediastinitis (PSM) form the basis for successful prevention. Once the presence of PSM is diagnosed, the known risk factors have been shown to have limited influence on management decisions. Evidence-based knowledge on treatment decisions, which include the extent and type of surgical intervention (other than debridement), timing and others is available but has not yet been incorporated into a classification on management decisions regarding PSM. Ours is a first attempt at developing a classification system for management of PSM, taking the various evidence-based reconstructive options into consideration. The classification is simple to introduce (there are four Types) and relies on the careful establishment of two variables (sternal stability and sternal bone viability and stock) prior to deciding on the best available reconstructive option. It should allow better insight into why treatment decisions fail or have to be altered and will allow better comparison of treatment outcomes between various institutions.

Intrarater and interrater reliability and validity in the assessment of the mechanism of injury and integrity of the posterior ligamentous complex: a novel injury severity scoring system for thoracolumbar injuries. Invited submission from the Joint Section Meeting On Disorders of the Spine and Peripheral Nerves, March 2005.

PubMed

Harrop, James S; Vaccaro, Alexander R; Hurlbert, R John; Wilsey, Jared T; Baron, Eli M; Shaffrey, Christopher I; Fisher, Charles G; Dvorak, Marcel F; Oner, F C; Wood, Kirkham B; Anand, Neel; Anderson, D Greg; Lim, Moe R; Lee, Joon Y; Bono, Christopher M; Arnold, Paul M; Rampersaud, Y Raja; Fehlings, Michael G

2006-02-01

A new classification and treatment algorithm for thoracolumbar injuries was recently introduced by Vaccaro and colleagues in 2005. A thoracolumbar injury severity scale (TLISS) was proposed for grading and guiding treatment for these injuries. The scale is based on the following: 1) the mechanism of injury; 2) the integrity of the posterior ligamentous complex (PLC); and 3) the patient's neurological status. The reliability and validity of assessing injury mechanism and the integrity of the PLC was assessed. Forty-eight spine surgeons, consisting of neurosurgeons and orthopedic surgeons, reviewed 56 clinical thoracolumbar injury case histories. Each was classified and scored to determine treatment recommendations according to a novel classification system. After 3 months the case histories were reordered and the physicians repeated the exercise. Validity of this classification was good among reviewers; the vast majority (> 90%) agreed with the system's treatment recommendations. Surgeons were unclear as to a cogent description of PLC disruption and fracture mechanism. The TLISS demonstrated acceptable reliability in terms of intra- and interobserver agreement on the algorithm's treatment recommendations. Replacing injury mechanism with a description of injury morphology and better definition of PLC injury will improve inter- and intraobserver reliability of this injury classification system.

Outpatient Treatment of the Sexually Motivated Murderer and Potential Murderer.

ERIC Educational Resources Information Center

Schlesinger, Louis B.; Revitch, Eugene

1990-01-01

Introduces the psychopathology and psychodynamics of sex murderer (and potential sex murderer) with emphasis on treatment in outpatient setting. Reviews system of classification of murder based on motivational dynamics of the act itself. Presents three cases that demonstrate a treatment failure, successful treatment of a catathymic sex murderer,…

Developing a dementia-specific health state classification system for a new preference-based instrument AD-5D.

PubMed

Nguyen, Kim-Huong; Mulhern, Brendan; Kularatna, Sanjeewa; Byrnes, Joshua; Moyle, Wendy; Comans, Tracy

2017-01-25

With an ageing population, the number of people with dementia is rising. The economic impact on the health care system is considerable and new treatment methods and approaches to dementia care must be cost effective. Economic evaluation requires valid patient reported outcome measures, and this study aims to develop a dementia-specific health state classification system based on the Quality of Life for Alzheimer's disease (QOL-AD) instrument (nursing home version). This classification system will subsequently be valued to generate a preference-based measure for use in the economic evaluation of interventions for people with dementia. We assessed the dimensionality of the QOL-AD to develop a new classification system. This was done using exploratory and confirmatory factor analysis and further assessment of the structure of the measure to ensure coverage of the key areas of quality of life. Secondly, we used Rasch analysis to test the psychometric performance of the items, and select item(s) to describe each dimension. This was done on 13 items of the QOL-AD (excluding two general health items) using a sample of 284 residents living in long-term care facilities in Australia who had a diagnosis of dementia. A five dimension classification system is proposed resulting from the three factor structure (defined as 'interpersonal environment', 'physical health' and 'self-functioning') derived from the factor analysis and two factors ('memory' and 'mood') from the accompanying review. For the first three dimensions, Rasch analysis selected three questions of the QOL-AD ('living situation', 'physical health', and 'do fun things') with memory and mood questions representing their own dimensions. The resulting classification system (AD-5D) includes many of the health-related quality of life dimensions considered important to people with dementia, including mood, global function and skill in daily living. The development of the AD-5D classification system is an important step in the future application of the widely used QOL-AD in economic evaluations. Future valuation studies will enable this tool to be used to calculate quality adjusted life years to evaluate treatments and interventions for people diagnosed with mild to moderate dementia.

Osteochondritis dissecans of the humeral capitellum: reliability of four classification systems using radiographs and computed tomography.

PubMed

Claessen, Femke M A P; van den Ende, Kimberly I M; Doornberg, Job N; Guitton, Thierry G; Eygendaal, Denise; van den Bekerom, Michel P J

2015-10-01

The radiographic appearance of osteochondritis dissecans (OCD) of the humeral capitellum varies according to the stage of the lesion. It is important to evaluate the stage of OCD lesion carefully to guide treatment. We compared the interobserver reliability of currently used classification systems for OCD of the humeral capitellum to identify the most reliable classification system. Thirty-two musculoskeletal radiologists and orthopaedic surgeons specialized in elbow surgery from several countries evaluated anteroposterior and lateral radiographs and corresponding computed tomography (CT) scans of 22 patients to classify the stage of OCD of the humeral capitellum according to the classification systems developed by (1) Minami, (2) Berndt and Harty, (3) Ferkel and Sgaglione, and (4) Anderson on a Web-based study platform including a Digital Imaging and Communications in Medicine viewer. Magnetic resonance imaging was not evaluated as part of this study. We measured agreement among observers using the Siegel and Castellan multirater κ. All OCD classification systems, except for Berndt and Harty, which had poor agreement among observers (κ = 0.20), had fair interobserver agreement: κ was 0.27 for the Minami, 0.23 for Anderson, and 0.22 for Ferkel and Sgaglione classifications. The Minami Classification was significantly more reliable than the other classifications (P < .001). The Minami Classification was the most reliable for classifying different stages of OCD of the humeral capitellum. However, it is unclear whether radiographic evidence of OCD of the humeral capitellum, as categorized by the Minami Classification, guides treatment in clinical practice as a result of this fair agreement. Copyright © 2015 Journal of Shoulder and Elbow Surgery Board of Trustees. Published by Elsevier Inc. All rights reserved.

Single-Rooted Extraction Sockets: Classification and Treatment Protocol.

PubMed

El Chaar, Edgar; Oshman, Sarah; Fallah Abed, Pooria

2016-09-01

Clinicians have many treatment techniques from which to choose when extracting a failing tooth and replacing it with an implant-supported restoration and when successful management of an extraction socket during the course of tooth replacement is necessary to achieve predictable and esthetic outcomes. This article presents a straightforward, yet thorough, classification for extraction sockets of single-rooted teeth and provides guidance to clinicians in the selection of appropriate and predictable treatment. The presented classification of extraction sockets for single-rooted teeth focuses on the topography of the extraction socket, while the protocol for treatment of each socket type factors in the shape of the remaining bone, the biotype, and the location of the socket whether it be in the mandible or maxilla. This system is based on the biologic foundations of wound healing and can help guide clinicians to successful treatment outcomes.

Intra- and interobserver agreement in the classification and treatment of distal third clavicle fractures.

PubMed

Bishop, Julie Y; Jones, Grant L; Lewis, Brian; Pedroza, Angela

2015-04-01

In treatment of distal third clavicle fractures, the Neer classification system, based on the location of the fracture in relation to the coracoclavicular ligaments, has traditionally been used to determine fracture pattern stability. To determine the intra- and interobserver reliability in the classification of distal third clavicle fractures via standard plain radiographs and the intra- and interobserver agreement in the preferred treatment of these fractures. Cohort study (Diagnosis); Level of evidence, 3. Thirty radiographs of distal clavicle fractures were randomly selected from patients treated for distal clavicle fractures between 2006 and 2011. The radiographs were distributed to 22 shoulder/sports medicine fellowship-trained orthopaedic surgeons. Fourteen surgeons responded and took part in the study. The evaluators were asked to measure the size of the distal fragment, classify the fracture pattern as stable or unstable, assign the Neer classification, and recommend operative versus nonoperative treatment. The radiographs were reordered and redistributed 3 months later. Inter- and intrarater agreement was determined for the distal fragment size, stability of the fracture, Neer classification, and decision to operate. Single variable logistic regression was performed to determine what factors could most accurately predict the decision for surgery. Interrater agreement was fair for distal fragment size, moderate for stability, fair for Neer classification, slight for type IIB and III fractures, and moderate for treatment approach. Intrarater agreement was moderate for distal fragment size categories (κ = 0.50, P < .001) and Neer classification (κ = 0.42, P < .001) and substantial for stable fracture (κ = 0.65, P < .001) and decision to operate (κ = 0.65, P < .001). Fracture stability was the best predictor of treatment, with 89% accuracy (P < .001). Fracture stability determination and the decision to operate had the highest interobserver agreement. Fracture stability was the key determinant of treatment, rather than the Neer classification system or the size of the distal fragment. © 2015 The Author(s).

Microcomputer-based classification of environmental data in municipal areas

NASA Astrophysics Data System (ADS)

Thiergärtner, H.

1995-10-01

Multivariate data-processing methods used in mineral resource identification can be used to classify urban regions. Using elements of expert systems, geographical information systems, as well as known classification and prognosis systems, it is possible to outline a single model that consists of resistant and of temporary parts of a knowledge base including graphical input and output treatment and of resistant and temporary elements of a bank of methods and algorithms. Whereas decision rules created by experts will be stored in expert systems directly, powerful classification rules in form of resistant but latent (implicit) decision algorithms may be implemented in the suggested model. The latent functions will be transformed into temporary explicit decision rules by learning processes depending on the actual task(s), parameter set(s), pixels selection(s), and expert control(s). This takes place both at supervised and nonsupervised classification of multivariately described pixel sets representing municipal subareas. The model is outlined briefly and illustrated by results obtained in a target area covering a part of the city of Berlin (Germany).

MR Imaging Based Treatment Planning for Radiotherapy of Prostate Cancer

DTIC Science & Technology

2008-02-01

Radiotherapy, MR-based treatment planning, dosimetry, Monte Carlo dose verification, Prostate Cancer, MRI -based DRRs 16. SECURITY CLASSIFICATION...AcQPlan system Version 5 was used for the study , which is capable of performing dose calculation on both CT and MRI . A four field 3D conformal planning...prostate motion studies for 3DCRT and IMRT of prostate cancer; (2) to investigate and improve the accuracy of MRI -based treatment planning dose calculation

Diagnostic criteria, severity classification and guidelines of systemic sclerosis.

PubMed

Asano, Yoshihide; Jinnin, Masatoshi; Kawaguchi, Yasushi; Kuwana, Masataka; Goto, Daisuke; Sato, Shinichi; Takehara, Kazuhiko; Hatano, Masaru; Fujimoto, Manabu; Mugii, Naoki; Ihn, Hironobu

2018-06-01

Several effective drugs have been identified for the treatment of systemic sclerosis (SSc). However, in advanced cases, not only their effectiveness is reduced but they may be also harmful due to their side-effects. Therefore, early diagnosis and early treatment is most important for the treatment of SSc. We established diagnostic criteria for SSc in 2003 and early diagnostic criteria for SSc in 2011, for the purpose of developing evaluation of each organ in SSc. Moreover, in November 2013, the American College of Rheumatology and the European Rheumatology Association jointly developed new diagnostic criteria for increasing their sensitivity and specificity, so we revised our diagnostic criteria and severity classification of SSc. Furthermore, we have revised the clinical guideline based on the newest evidence. In particular, the clinical guideline was established by clinical questions based on evidence-based medicine according to the New Minds Clinical Practice Guideline Creation Manual (version 1.0). We aimed to make the guideline easy to use and reliable based on the newest evidence, and to present guidance as specific as possible for various clinical problems in treatment of SSc. © 2018 Japanese Dermatological Association.

[The questionnaire survey on glaucoma diagnosis and treatment in China (2016)].

PubMed

Zhang, Q; Cao, K; Kang, M T; Sun, Y X; Gan, J H; Tian, J X; Ran, A R; Zhang, X; Su, Y D; Li, S N

2017-02-11

Objective: To investigate the present situation of diagnosis and treatment for primary angle-closure glaucoma (PACG) and primary open-angle glaucoma (POAG) and awareness of the relevant progress among Chinese ophthalmologists. Methods: This study was a cross-sectional, non-randomized sampling survey. Participants were ophthalmologists who attended the 11st Chinese Glaucoma Society Congress during November 11 to 12, 2016. They were invited to fill out a questionnaire. The questionnaire included participants' basic information and their knowledge about glaucoma diagnosis and treatment. The data collected through questionnaire were analyzed with SAS9.4. Results: A total of 450 questionnaires were distributed and 372 valid questionnaires were retrieved, with a response rate of 82. 7%(372/450). ISGEO classification system was adopted by 58.9% (219/372) of the participants as the diagnostic criteria for PACG. Of the respondents, 48.1% (179/372) of the participants believed that "anterior chamber angle closure mechanism-based PACG classification system" was more instructive for treatment, the percentage was higher than ISGEO classification system (42.2%, 157/372). Most (72.3%, 269/372) of the participants knew the 3-minute dark room prone test, but only 27.7%(103/372) of them applied it in clinical practice. A total of 83.4%(310/372) of the participants believed that low cerebrospinal fluid pressure is a risk factor for POAG. In all, 71.8% (267/372) of the participants reported that their institutes had applied compound trabeculectomy with adjustable suture, with 76.9%(286/372) of the participants agreeing that the adjustable suture reduced the rate of complications after trabeculectomy. Conclusions: Currently, both ISGEO classification system and anterior chamber angle closure mechanism-based PACG classification system were adopted in the diagnosis and treatment of glaucoma. Low cerebrospinal fluid pressure as new risk factors for POAG has been widely acknowledged and given attentions by Chinese ophthalmologists. The 3-minute darkroom prone test and compound trabeculectomy with adjustable suture still need to be promoted. (Chin J Ophthalmol, 2017, 53: 115-120) .

Congenital Differences of the Upper Extremity: Classification and Treatment Principles

PubMed Central

2011-01-01

For hand surgeons, the treatment of children with congenital differences of the upper extremity is challenging because of the diverse spectrum of conditions encountered, but the task is also rewarding because it provides surgeons with the opportunity to impact a child's growth and development. An ideal classification of congenital differences of the upper extremity would reflect the full spectrum of morphologic abnormalities and encompass etiology, a guide to treatment, and provide prognoses. In this report, I review current classification systems and discuss their contradictions and limitations. In addition, I present a modified classification system and provide treatment principles. As our understanding of the etiology of congenital differences of the upper extremity increases and as experience of treating difficult cases accumulates, even an ideal classification system and optimal treatment strategies will undoubtedly continue to evolve. PMID:21909463

Comments on new classification, treatment algorithm and prognosis-estimating systems for sigmoid volvulus and ileosigmoid knotting: necessity and utility.

PubMed

Aksungur, N; Korkut, E

2018-05-24

We read Atamanalp classification, treatment algorithm and prognosis-estimating systems for sigmoid volvulus (SV) and ileosigmoid knotting (ISK) in Colorectal Disease [1,2]. Our comments relate to necessity and utility of these new classification systems. Classification or staging systems are generally used in malignant or premalignant pathologies such as colorectal cancers [3] or polyps [4]. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Bladder cancer treatment response assessment with radiomic, clinical, and radiologist semantic features

NASA Astrophysics Data System (ADS)

Gordon, Marshall N.; Cha, Kenny H.; Hadjiiski, Lubomir M.; Chan, Heang-Ping; Cohan, Richard H.; Caoili, Elaine M.; Paramagul, Chintana; Alva, Ajjai; Weizer, Alon Z.

2018-02-01

We are developing a decision support system for assisting clinicians in assessment of response to neoadjuvant chemotherapy for bladder cancer. Accurate treatment response assessment is crucial for identifying responders and improving quality of life for non-responders. An objective machine learning decision support system may help reduce variability and inaccuracy in treatment response assessment. We developed a predictive model to assess the likelihood that a patient will respond based on image and clinical features. With IRB approval, we retrospectively collected a data set of pre- and post- treatment CT scans along with clinical information from surgical pathology from 98 patients. A linear discriminant analysis (LDA) classifier was used to predict the likelihood that a patient would respond to treatment based on radiomic features extracted from CT urography (CTU), a radiologist's semantic feature, and a clinical feature extracted from surgical and pathology reports. The classification accuracy was evaluated using the area under the ROC curve (AUC) with a leave-one-case-out cross validation. The classification accuracy was compared for the systems based on radiomic features, clinical feature, and radiologist's semantic feature. For the system based on only radiomic features the AUC was 0.75. With the addition of clinical information from examination under anesthesia (EUA) the AUC was improved to 0.78. Our study demonstrated the potential of designing a decision support system to assist in treatment response assessment. The combination of clinical features, radiologist semantic features and CTU radiomic features improved the performance of the classifier and the accuracy of treatment response assessment.

Vascular Anomalies (Part I): Classification and Diagnostics of Vascular Anomalies.

PubMed

Sadick, Maliha; Müller-Wille, René; Wildgruber, Moritz; Wohlgemuth, Walter A

2018-06-06

 Vascular anomalies are a diagnostic and therapeutic challenge. They require dedicated interdisciplinary management. Optimal patient care relies on integral medical evaluation and a classification system established by experts in the field, to provide a better understanding of these complex vascular entities.  A dedicated classification system according to the International Society for the Study of Vascular Anomalies (ISSVA) and the German Interdisciplinary Society of Vascular Anomalies (DiGGefA) is presented. The vast spectrum of diagnostic modalities, ranging from ultrasound with color Doppler, conventional X-ray, CT with 4 D imaging and MRI as well as catheter angiography for appropriate assessment is discussed.  Congenital vascular anomalies are comprised of vascular tumors, based on endothelial cell proliferation and vascular malformations with underlying mesenchymal and angiogenetic disorder. Vascular tumors tend to regress with patient's age, vascular malformations increase in size and are subdivided into capillary, venous, lymphatic, arterio-venous and combined malformations, depending on their dominant vasculature. According to their appearance, venous malformations are the most common representative of vascular anomalies (70 %), followed by lymphatic malformations (12 %), arterio-venous malformations (8 %), combined malformation syndromes (6 %) and capillary malformations (4 %).  The aim is to provide an overview of the current classification system and diagnostic characterization of vascular anomalies in order to facilitate interdisciplinary management of vascular anomalies.   · Vascular anomalies are comprised of vascular tumors and vascular malformations, both considered to be rare diseases.. · Appropriate treatment depends on correct classification and diagnosis of vascular anomalies, which is based on established national and international classification systems, recommendations and guidelines.. · In the classification, diagnosis and treatment of congenital vascular anomalies, radiology plays an integral part in patient management.. · Sadick M, Müller-Wille R, Wildgruber M et al. Vascular Anomalies (Part I): Classification and Diagnostics of Vascular Anomalies. Fortschr Röntgenstr 2018; DOI: 10.1055/a-0620-8925. © Georg Thieme Verlag KG Stuttgart · New York.

From Classification to Epilepsy Ontology and Informatics

PubMed Central

Zhang, Guo-Qiang; Sahoo, Satya S; Lhatoo, Samden D

2012-01-01

Summary The 2010 International League Against Epilepsy (ILAE) classification and terminology commission report proposed a much needed departure from previous classifications to incorporate advances in molecular biology, neuroimaging, and genetics. It proposed an interim classification and defined two key requirements that need to be satisfied. The first is the ability to classify epilepsy in dimensions according to a variety of purposes including clinical research, patient care, and drug discovery. The second is the ability of the classification system to evolve with new discoveries. Multi-dimensionality and flexibility are crucial to the success of any future classification. In addition, a successful classification system must play a central role in the rapidly growing field of epilepsy informatics. An epilepsy ontology, based on classification, will allow information systems to facilitate data-intensive studies and provide a proven route to meeting the two foregoing key requirements. Epilepsy ontology will be a structured terminology system that accommodates proposed and evolving ILAE classifications, the NIH/NINDS Common Data Elements, the ICD systems and explicitly specifies all known relationships between epilepsy concepts in a proper framework. This will aid evidence based epilepsy diagnosis, investigation, treatment and research for a diverse community of clinicians and researchers. Benefits range from systematization of electronic patient records to multi-modal data repositories for research and training manuals for those involved in epilepsy care. Given the complexity, heterogeneity and pace of research advances in the epilepsy domain, such an ontology must be collaboratively developed by key stakeholders in the epilepsy community and experts in knowledge engineering and computer science. PMID:22765502

Recommendations for the classification of HIV associated neuromanifestations in the German DRG system.

PubMed

Evers, Stefan; Fiori, W; Brockmeyer, N; Arendt, G; Husstedt, I-W

2005-09-12

HIV associated neuromanifestations are of growing importance in the in-patient treatment of HIV infected patients. In Germany, all in-patients have to be coded according to the ICD-10 classification and the German DRG-system. We present recommendations how to code the different primary and secondary neuromanifestations of HIV infection. These recommendations are based on the commentary of the German DRG procedures and are aimed to establish uniform coding of neuromanifestations.

Classification of Normal and Pathological Gait in Young Children Based on Foot Pressure Data.

PubMed

Guo, Guodong; Guffey, Keegan; Chen, Wenbin; Pergami, Paola

2017-01-01

Human gait recognition, an active research topic in computer vision, is generally based on data obtained from images/videos. We applied computer vision technology to classify pathology-related changes in gait in young children using a foot-pressure database collected using the GAITRite walkway system. As foot positioning changes with children's development, we also investigated the possibility of age estimation based on this data. Our results demonstrate that the data collected by the GAITRite system can be used for normal/pathological gait classification. Combining age information and normal/pathological gait classification increases the accuracy of the classifier. This novel approach could support the development of an accurate, real-time, and economic measure of gait abnormalities in children, able to provide important feedback to clinicians regarding the effect of rehabilitation interventions, and to support targeted treatment modifications.

Correlation-based pattern recognition for implantable defibrillators.

PubMed Central

Wilkins, J.

1996-01-01

An estimated 300,000 Americans die each year from cardiac arrhythmias. Historically, drug therapy or surgery were the only treatment options available for patients suffering from arrhythmias. Recently, implantable arrhythmia management devices have been developed. These devices allow abnormal cardiac rhythms to be sensed and corrected in vivo. Proper arrhythmia classification is critical to selecting the appropriate therapeutic intervention. The classification problem is made more challenging by the power/computation constraints imposed by the short battery life of implantable devices. Current devices utilize heart rate-based classification algorithms. Although easy to implement, rate-based approaches have unacceptably high error rates in distinguishing supraventricular tachycardia (SVT) from ventricular tachycardia (VT). Conventional morphology assessment techniques used in ECG analysis often require too much computation to be practical for implantable devices. In this paper, a computationally-efficient, arrhythmia classification architecture using correlation-based morphology assessment is presented. The architecture classifies individuals heart beats by assessing similarity between an incoming cardiac signal vector and a series of prestored class templates. A series of these beat classifications are used to make an overall rhythm assessment. The system makes use of several new results in the field of pattern recognition. The resulting system achieved excellent accuracy in discriminating SVT and VT. PMID:8947674

Response monitoring using quantitative ultrasound methods and supervised dictionary learning in locally advanced breast cancer

NASA Astrophysics Data System (ADS)

Gangeh, Mehrdad J.; Fung, Brandon; Tadayyon, Hadi; Tran, William T.; Czarnota, Gregory J.

2016-03-01

A non-invasive computer-aided-theragnosis (CAT) system was developed for the early assessment of responses to neoadjuvant chemotherapy in patients with locally advanced breast cancer. The CAT system was based on quantitative ultrasound spectroscopy methods comprising several modules including feature extraction, a metric to measure the dissimilarity between "pre-" and "mid-treatment" scans, and a supervised learning algorithm for the classification of patients to responders/non-responders. One major requirement for the successful design of a high-performance CAT system is to accurately measure the changes in parametric maps before treatment onset and during the course of treatment. To this end, a unified framework based on Hilbert-Schmidt independence criterion (HSIC) was used for the design of feature extraction from parametric maps and the dissimilarity measure between the "pre-" and "mid-treatment" scans. For the feature extraction, HSIC was used to design a supervised dictionary learning (SDL) method by maximizing the dependency between the scans taken from "pre-" and "mid-treatment" with "dummy labels" given to the scans. For the dissimilarity measure, an HSIC-based metric was employed to effectively measure the changes in parametric maps as an indication of treatment effectiveness. The HSIC-based feature extraction and dissimilarity measure used a kernel function to nonlinearly transform input vectors into a higher dimensional feature space and computed the population means in the new space, where enhanced group separability was ideally obtained. The results of the classification using the developed CAT system indicated an improvement of performance compared to a CAT system with basic features using histogram of intensity.

Promising personalized therapeutic options for diffuse large B-cell Lymphoma Subtypes with oncogene addictions.

PubMed

Steinhardt, James J; Gartenhaus, Ronald B

2012-09-01

Currently, two major classification systems segregate diffuse large B-cell lymphoma (DLBCL) into subtypes based on gene expression profiles and provide great insights about the oncogenic mechanisms that may be crucial for lymphomagenesis as well as prognostic information regarding response to current therapies. However, these current classification systems primarily look at expression and not dependency and are thus limited to inductive or probabilistic reasoning when evaluating alternative therapeutic options. The development of a deductive classification system that identifies subtypes in which all patients with a given phenotype require the same oncogenic drivers, and would therefore have a similar response to a rational therapy targeting the essential drivers, would significantly advance the treatment of DLBCL. This review highlights the putative drivers identified as well as the work done to identify potentially dependent populations. These studies integrated genomic analysis and functional screens to provide a rationale for targeted therapies within defined populations. Personalizing treatments by identifying patients with oncogenic dependencies via genotyping and specifically targeting the responsible drivers may constitute a novel approach for the treatment of DLBCL. ©2012 AACR.

The Molecular Pathology of Myelodysplastic Syndrome.

PubMed

Haferlach, Torsten

2018-05-23

The diagnosis and classification of myelodysplastic syndromes (MDS) are based on cytomorphology and cytogenetics (WHO classification). Prognosis is best defined by the Revised International Prognostic Scoring System (IPSS-R). In recent years, an increasing number of molecular aberrations have been discovered. They are already included in the classification (e.g., SF3B1) and, more importantly, have emerged as valuable markers for better classification, particularly for defining risk groups. Mutations in genes such as SF3B1 and IDH1/2 have already had an impact on targeted treatment approaches in MDS. © 2018 S. Karger AG, Basel.

Toward an endovascular internal carotid artery classification system.

PubMed

Shapiro, M; Becske, T; Riina, H A; Raz, E; Zumofen, D; Jafar, J J; Huang, P P; Nelson, P K

2014-02-01

Does the world need another ICA classification scheme? We believe so. The purpose of proposed angiography-driven classification is to optimize description of the carotid artery from the endovascular perspective. A review of existing, predominantly surgically-driven classifications is performed, and a new scheme, based on the study of NYU aneurysm angiographic and cross-sectional databases is proposed. Seven segments - cervical, petrous, cavernous, paraophthlamic, posterior communicating, choroidal, and terminus - are named. This nomenclature recognizes intrinsic uncertainty in precise angiographic and cross-sectional localization of aneurysms adjacent to the dural rings, regarding all lesions distal to the cavernous segment as potentially intradural. Rather than subdividing various transitional, ophthalmic, and hypophyseal aneurysm subtypes, as necessitated by their varied surgical approaches and risks, the proposed classification emphasizes their common endovascular treatment features, while recognizing that many complex, trans-segmental, and fusiform aneurysms not readily classifiable into presently available, saccular aneurysm-driven schemes, are being increasingly addressed by endovascular means. We believe this classification may find utility in standardizing nomenclature for outcome tracking, treatment trials and physician communication.

Annehurst Curriculum Classification System Variables as Dimensions of Aptitude Treatment Interactions.

ERIC Educational Resources Information Center

Clark, Ginny; Grady, M. Tim

The objective of this study was to determine if the Annehurst Curriculum Classification System (ACCS) learner characteristics and curriculum materials classifications among elementary mathematics students, can be used as the dimensions of an aptitude-treatment interaction analysis. The subjects were 34 fourth and fifth graders in three open-space…

Group Treatment in Acquired Brain Injury Rehabilitation

ERIC Educational Resources Information Center

Bertisch, Hilary; Rath, Joseph F.; Langenbahn, Donna M.; Sherr, Rose Lynn; Diller, Leonard

2011-01-01

The current article describes critical issues in adapting traditional group-treatment methods for working with individuals with reduced cognitive capacity secondary to acquired brain injury. Using the classification system based on functional ability developed at the NYU Rusk Institute of Rehabilitation Medicine (RIRM), we delineate the cognitive…

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.

Auto-simultaneous laser treatment and Ohshiro's classification of laser treatment

NASA Astrophysics Data System (ADS)

Ohshiro, Toshio

2005-07-01

When the laser was first applied in medicine and surgery in the late 1960"s and early 1970"s, early adopters reported better wound healing and less postoperative pain with laser procedures compared with the same procedure performed with the cold scalpel or with electrothermy, and multiple surgical effects such as incision, vaporization and hemocoagulation could be achieved with the same laser beam. There was thus an added beneficial component which was associated only with laser surgery. This was first recognized as the `?-effect", was then classified by the author as simultaneous laser therapy, but is now more accurately classified by the author as part of the auto-simultaneous aspect of laser treatment. Indeed, with the dramatic increase of the applications of the laser in surgery and medicine over the last 2 decades there has been a parallel increase in the need for a standardized classification of laser treatment. Some classifications have been machine-based, and thus inaccurate because at appropriate parameters, a `low-power laser" can produce a surgical effect and a `high power laser", a therapeutic one . A more accurate classification based on the tissue reaction is presented, developed by the author. In addition to this, the author has devised a graphical representation of laser surgical and therapeutic beams whereby the laser type, parameters, penetration depth, and tissue reaction can all be shown in a single illustration, which the author has termed the `Laser Apple", due to the typical pattern generated when a laser beam is incident on tissue. Laser/tissue reactions fall into three broad groups. If the photoreaction in the tissue is irreversible, then it is classified as high-reactive level laser treatment (HLLT). If some irreversible damage occurs together with reversible photodamage, as in tissue welding, the author refers to this as mid-reactive level laser treatment (MLLT). If the level of reaction in the target tissue is lower than the cells" survival threshold, then this is low reactive-level laser therapy (LLLT). All three of these classifications can occur simultaneously in the one target, and fall under the umbrella of laser treatment (LT). LT is further subdivided into three main types: mono-type LT (Mo-LT, treatment with a single laser system; multi-type LT (Mu-LT, treatment with multiple laser systems); and concomitant LT (Cc-LT), laser treatment in combination, each of which is further subdivided by tissue reaction to give an accurate, treatment-based categorization of laser treatment. When this effect-based classification is combined with and illustrated by the appropriate laser apple pattern, an accurate and simple method of classifying laser/tissue reactions by the reaction, rather than by the laser used to produce the reaction, is achieved. Examples will be given to illustrate the author"s new approach to this important concept.

[Implementation of cytology images classification--the Bethesda 2001 System--in a group of screened women from Podlaskie region--effect evaluation].

PubMed

Zbroch, Tomasz; Knapp, Paweł Grzegorz; Knapp, Piotr Andrzej

2007-09-01

Increasing knowledge concerning carcinogenesis within cervical epithelium has forced us to make continues modifications of cytology classification of the cervical smears. Eventually, new descriptions of the submicroscopic cytomorphological abnormalities have enabled the implementation of Bethesda System which was meant to take place of the former Papanicolaou classification although temporarily both are sometimes used simultaneously. The aim of this study was to compare results of these two classification systems in the aspect of diagnostic accuracy verified by further tests of the diagnostic algorithm for the cervical lesion evaluation. The study was conducted in the group of women selected from general population, the criteria being the place of living and cervical cancer age risk group, in the consecutive periods of mass screening in Podlaski region. The performed diagnostic tests have been based on the commonly used algorithm, as well as identical laboratory and methodological conditions. Performed assessment revealed comparable diagnostic accuracy of both analyzing classifications, verified by histological examination, although with marked higher specificity for dysplastic lesions with decreased number of HSIL results and increased diagnosis of LSILs. Higher number of performed colposcopies and biopsies were an additional consequence of TBS classification. Results based on Bethesda System made it possible to find the sources and reasons of abnormalities with much greater precision, which enabled causing agent treatment. Two evaluated cytology classification systems, although not much different, depicted higher potential of TBS and better, more effective communication between cytology laboratory and gynecologist, making reasonable implementation of The Bethesda System in the daily cytology screening work.

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.

Computer-aided Prognosis of Neuroblastoma on Whole-slide Images: Classification of Stromal Development

PubMed Central

Sertel, O.; Kong, J.; Shimada, H.; Catalyurek, U.V.; Saltz, J.H.; Gurcan, M.N.

2009-01-01

We are developing a computer-aided prognosis system for neuroblastoma (NB), a cancer of the nervous system and one of the most malignant tumors affecting children. Histopathological examination is an important stage for further treatment planning in routine clinical diagnosis of NB. According to the International Neuroblastoma Pathology Classification (the Shimada system), NB patients are classified into favorable and unfavorable histology based on the tissue morphology. In this study, we propose an image analysis system that operates on digitized H&E stained whole-slide NB tissue samples and classifies each slide as either stroma-rich or stroma-poor based on the degree of Schwannian stromal development. Our statistical framework performs the classification based on texture features extracted using co-occurrence statistics and local binary patterns. Due to the high resolution of digitized whole-slide images, we propose a multi-resolution approach that mimics the evaluation of a pathologist such that the image analysis starts from the lowest resolution and switches to higher resolutions when necessary. We employ an offine feature selection step, which determines the most discriminative features at each resolution level during the training step. A modified k-nearest neighbor classifier is used to determine the confidence level of the classification to make the decision at a particular resolution level. The proposed approach was independently tested on 43 whole-slide samples and provided an overall classification accuracy of 88.4%. PMID:20161324

Imaging evaluation of traumatic thoracolumbar spine injuries: Radiological review

PubMed Central

Gamanagatti, Shivanand; Rathinam, Deepak; Rangarajan, Krithika; Kumar, Atin; Farooque, Kamran; Sharma, Vijay

2015-01-01

Spine fractures account for a large portion of musculoskeletal injuries worldwide. A classification of spine fractures is necessary in order to develop a common language for treatment indications and outcomes. Several classification systems have been developed based on injury anatomy or mechanisms of action, but they have demonstrated poor reliability, have yielded little prognostic information, and have not been widely used. For this reason, the Arbeitsgemeinschaftfür Osteosynthesefragen (AO) committee has classified thorocolumbar spine injuries based on the pathomorphological criteria into3 types (A: Compression; B: Distraction; C: Axial torque and rotational deformity). Each of these types is further divided into 3 groups and 3 subgroups reflecting progressive scale of morphological damage and the degree of instability. Because of its highly detailed sub classifications, the AO system has shown limited interobserver variability. It is similar to its predecessors in that it does not incorporate the patient’s neurologic status.The need for a reliable, reproducible, clinically relevant, prognostic classification system with an optimal balance of ease of use and detail of injury description contributed to the development of a new classification system, the thoracolumbar injury classification and severity score (TLICS). The TLICS defines injury based on three clinical characteristics: injury morphology, integrity of the posterior ligamentous complex, and neurologic status of the patient. The severity score offers prognostic information and is helpful in decision making about surgical vs nonsurgical management. PMID:26435776

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.

Does the Modified Gartland Classification Clarify Decision Making?

PubMed

Leung, Sophia; Paryavi, Ebrahim; Herman, Martin J; Sponseller, Paul D; Abzug, Joshua M

2018-01-01

The modified Gartland classification system for pediatric supracondylar fractures is often utilized as a communication tool to aid in determining whether or not a fracture warrants operative intervention. This study sought to determine the interobserver and intraobserver reliability of the Gartland classification system, as well as to determine whether there was agreement that a fracture warranted operative intervention regardless of the classification system. A total of 200 anteroposterior and lateral radiographs of pediatric supracondylar humerus fractures were retrospectively reviewed by 3 fellowship-trained pediatric orthopaedic surgeons and 2 orthopaedic residents and then classified as type I, IIa, IIb, or III. The surgeons then recorded whether they would treat the fracture nonoperatively or operatively. The κ coefficients were calculated to determine interobserver and intraobserver reliability. Overall, the Wilkins-modified Gartland classification has low-moderate interobserver reliability (κ=0.475) and high intraobserver reliability (κ=0.777). A low interobserver reliability was found when differentiating between type IIa and IIb (κ=0.240) among attendings. There was moderate-high interobserver reliability for the decision to operate (κ=0.691) and high intraobserver reliability (κ=0.760). Decreased interobserver reliability was present for decision to operate among residents. For fractures classified as type I, the decision to operate was made 3% of the time and 27% for type IIa. The decision was made to operate 99% of the time for type IIb and 100% for type III. There is almost full agreement for the nonoperative treatment of Type I fractures and operative treatment for type III fractures. There is agreement that type IIb fractures should be treated operatively and that the majority of type IIa fractures should be treated nonoperatively. However, the interobserver reliability for differentiating between type IIa and IIb fractures is low. Our results validate the Gartland classfication system as a method to help direct treatment of pediatric supracondylar humerus fractures, although the modification of the system, IIa versus IIb, seems to have limited reliability and utility. Terminology based on decision to treat may lead to a more clinically useful classification system in the evaluation and treatment of pediatric supracondylar humerus fractures. Level III-diagnostic studies.

[Surgical treatment of chronic pancreatitis based on classification of M. Buchler and coworkers].

PubMed

Krivoruchko, I A; Boĭko, V V; Goncharova, N N; Andreeshchev, S A

2011-08-01

The results of surgical treatment of 452 patients, suffering chronic pancreatitis (CHP), were analyzed. The CHP classification, elaborated by M. Buchler and coworkers (2009), based on clinical signs, morphological peculiarities and pancreatic function analysis, contains scientifically substantiated recommendations for choice of diagnostic methods and complex treatment of the disease. The classification proposed is simple in application and constitutes an instrument for studying and comparison of the CHP course severity, the patients prognosis and treatment.

Computerized decision support system for mass identification in breast using digital mammogram: a study on GA-based neuro-fuzzy approaches.

PubMed

Das, Arpita; Bhattacharya, Mahua

2011-01-01

In the present work, authors have developed a treatment planning system implementing genetic based neuro-fuzzy approaches for accurate analysis of shape and margin of tumor masses appearing in breast using digital mammogram. It is obvious that a complicated structure invites the problem of over learning and misclassification. In proposed methodology, genetic algorithm (GA) has been used for searching of effective input feature vectors combined with adaptive neuro-fuzzy model for final classification of different boundaries of tumor masses. The study involves 200 digitized mammograms from MIAS and other databases and has shown 86% correct classification rate.

Treatment-Based Classification versus Usual Care for Management of Low Back Pain

DTIC Science & Technology

2017-10-01

AWARD NUMBER: W81XWH-11-1-0657 TITLE: Treatment-Based Classification versus Usual Care for Management of Low Back Pain PRINCIPAL INVESTIGATOR...Treatment-Based Classification versus Usual Care for Management of Low Back Pain 5b. GRANT NUMBER W81XWH-11-1-0657 5c. PROGRAM ELEMENT NUMBER 6...AUTHOR(S) MAJ Daniel Rhon – daniel_rhon@baylor.edu 5d. PROJECT NUMBER 5e. TASK NUMBER 5f. WORK UNIT NUMBER 7. PERFORMING ORGANIZATION NAME(S

Comparison of simple screening criteria with the International Caries Detection and Assessment System classification in determining restorative treatment need.

PubMed

Kämppi, Antti; Tanner, Tarja; Päkkilä, Jari; Patinen, Pertti; Tjäderhane, Leo; Anttonen, Vuokko

2016-04-01

The Finnish Defence Forces' unique oral health-screening protocol (FDFsp) has been in use for decades. In FDFsp, restorative treatment need is determined based on the World Health Organization (WHO) criteria. The aim of this study was to compare the outcome of screening restorative treatment need with the outcome of using the International Caries Detection and Assessment System (ICDAS) classification at both individual and tooth levels. Our hypothesis was that the outcome of screening with FDFsp agrees with the outcome of using the ICDAS classification. In this study, a trained, calibrated examiner estimated, in a visual-tactile manner the restorative treatment need of 337 young healthy adults using the FDFsp. During the screening, 74 conscripts were selected for a thorough inspection. The inclusion criteria for those selected were: having no, having one to five, or having six or more caries lesions needing restorative treatment. In the thorough inspection, the participants were inspected in a visual-tactile manner using the ICDAS classification. The association of the outcomes achieved using the two different methods was analysed at individual and tooth levels. Sensitivity, specificity, and kappa values were calculated. Wisdom teeth were excluded. At the individual level, the agreement between the outcomes of using FDFsp and ICDAS ≥4 was excellent: sensitivity, 94.1%; specificity, 97.5%; and kappa = 0.92. When ICDAS ≥3 was used, the values were 72.7%, 96.7%, and 0.66%, respectively. Screening performed by a trained examiner using specific criteria is a reliable method for detecting individuals with restorative treatment need. The outcome of screening agrees strongly with results using the ICDAS classification. © 2015 FDI World Dental Federation.

Suggestions for Lymph Node Classification of UICC/AJCC Staging System: A Retrospective Study Based on 1197 Nasopharyngeal Carcinoma Patients Treated With Intensity-Modulated Radiation Therapy

PubMed Central

Guo, Qiaojuan; Pan, Jianji; Zong, Jingfeng; Zheng, Wei; Zhang, Chun; Tang, Linbo; Chen, Bijuan; Cui, Xiaofei; Xiao, Youping; Chen, Yunbin; Lin, Shaojun

2015-01-01

Abstract This article provides suggestions for N classification of Union for International Cancer Control/American Joint Committee on Cancer (UICC/AJCC) staging system of nasopharyngeal carcinoma (NPC), purely based on magnetic resonance imaging (MRI) in intensity-modulated radiation therapy (IMRT) era. A total of 1197 nonmetastatic NPC patients treated with IMRT were enrolled, and all were scanned by MRI at nasopharynx and neck before treatment. MRI-based nodal variables including level, laterality, maximal axial diameter (MAD), extracapsular spread (ECS), and necrosis were analyzed as potential prognostic factors. Modifications of N classification were then proposed and verified. Only nodal level and laterality were considered to be significant variables affecting the treatment outcome. N classification was thus proposed accordingly: N0, no regional lymph node (LN) metastasis; N1, retropharyngeal LNs involvement (regardless of laterality), and/or unilateral levels I, II, III, and/or Va involvement; N2, bilateral levels I, II, III, and/or Va involvement; and N3, levels IV, Vb, and Vc involvement. This proposal showed significant predicting value in multivariate analysis. N3 patients indicated relatively inferior overall survival (OS) and distant metastasis-free survival (DMFS) than N2 patients; however, the difference showed no statistical significance (P = 0.673 and 0.265 for OS and DMFS, respectively), and this was considered to be correlated with the small sample sizes of N3 patients (79 patients, 6.6%). Nodal level and laterality, but not MAD, ECS, and necrosis, were considered to be significant predicting factors for NPC. The proposed N classification was proved to be powerfully predictive in our cohort; however, treatment outcome of the proposed N2 and N3 patients could not differ significantly from each other. This insignificance may be because of the small sample sizes of N3 patients. Our results are based on a single-center data, to develop a new N classification that is universally acceptable; further verification by data from multicenter is warranted. PMID:25997052

The 7th lung cancer TNM classification and staging system: Review of the changes and implications.

PubMed

Mirsadraee, Saeed; Oswal, Dilip; Alizadeh, Yalda; Caulo, Andrea; van Beek, Edwin

2012-04-28

Lung cancer is the most common cause of death from cancer in males, accounting for more than 1.4 million deaths in 2008. It is a growing concern in China, Asia and Africa as well. Accurate staging of the disease is an important part of the management as it provides estimation of patient's prognosis and identifies treatment sterategies. It also helps to build a database for future staging projects. A major revision of lung cancer staging has been announced with effect from January 2010. The new classification is based on a larger surgical and non-surgical cohort of patients, and thus more accurate in terms of outcome prediction compared to the previous classification. There are several original papers regarding this new classification which give comprehensive description of the methodology, the changes in the staging and the statistical analysis. This overview is a simplified description of the changes in the new classification and their potential impact on patients' treatment and prognosis.

Treatment of Children with Speech Oral Placement Disorders (OPDs): A Paradigm Emerges

ERIC Educational Resources Information Center

Bahr, Diane; Rosenfeld-Johnson, Sara

2010-01-01

Epidemiological research was used to develop the Speech Disorders Classification System (SDCS). The SDCS is an important speech diagnostic paradigm in the field of speech-language pathology. This paradigm could be expanded and refined to also address treatment while meeting the standards of evidence-based practice. The article assists that process…

Cancer classification in the genomic era: five contemporary problems.

PubMed

Song, Qingxuan; Merajver, Sofia D; Li, Jun Z

2015-10-19

Classification is an everyday instinct as well as a full-fledged scientific discipline. Throughout the history of medicine, disease classification is central to how we develop knowledge, make diagnosis, and assign treatment. Here, we discuss the classification of cancer and the process of categorizing cancer subtypes based on their observed clinical and biological features. Traditionally, cancer nomenclature is primarily based on organ location, e.g., "lung cancer" designates a tumor originating in lung structures. Within each organ-specific major type, finer subgroups can be defined based on patient age, cell type, histological grades, and sometimes molecular markers, e.g., hormonal receptor status in breast cancer or microsatellite instability in colorectal cancer. In the past 15+ years, high-throughput technologies have generated rich new data regarding somatic variations in DNA, RNA, protein, or epigenomic features for many cancers. These data, collected for increasingly large tumor cohorts, have provided not only new insights into the biological diversity of human cancers but also exciting opportunities to discover previously unrecognized cancer subtypes. Meanwhile, the unprecedented volume and complexity of these data pose significant challenges for biostatisticians, cancer biologists, and clinicians alike. Here, we review five related issues that represent contemporary problems in cancer taxonomy and interpretation. (1) How many cancer subtypes are there? (2) How can we evaluate the robustness of a new classification system? (3) How are classification systems affected by intratumor heterogeneity and tumor evolution? (4) How should we interpret cancer subtypes? (5) Can multiple classification systems co-exist? While related issues have existed for a long time, we will focus on those aspects that have been magnified by the recent influx of complex multi-omics data. Exploration of these problems is essential for data-driven refinement of cancer classification and the successful application of these concepts in precision medicine.

Validation of a new classification for periprosthetic shoulder fractures.

PubMed

Kirchhoff, Chlodwig; Beirer, Marc; Brunner, Ulrich; Buchholz, Arne; Biberthaler, Peter; Crönlein, Moritz

2018-06-01

Successful treatment of periprosthetic shoulder fractures depends on the right strategy, starting with a well-structured classification of the fracture. Unfortunately, clinically relevant factors for treatment planning are missing in the pre-existing classifications. Therefore, the aim of the present study was to describe a new specific classification system for periprosthetic shoulder fractures including a structured treatment algorithm for this important fragility fracture issue. The classification was established, focussing on five relevant items, naming the prosthesis type, the fracture localisation, the rotator cuff status, the anatomical fracture region and the stability of the implant. After considering each single item, the individual treatment concept can be assessed in one last step. To evaluate the introduced classification, a retrospective analysis of pre- and post-operative data of patients, treated with periprosthetic shoulder fractures, was conducted by two board certified trauma surgery consultants. The data of 19 patients (8 male, 11 female) with a mean age of 74 ± five years have been analysed in our study. The suggested treatment algorithm was proven to be reliable, detected by good clinical outcome in 15 of 16 (94%) cases, where the suggested treatment was maintained. Only one case resulted in poor outcome due to post-operative wound infection and had to be revised. The newly developed six-step classification is easy to utilise and extends the pre-existing classification systems in terms of clinically-relevant information. This classification should serve as a simple tool for the surgeon to consider the optimal treatment for his patients.

Does the Spine Surgeon’s Experience Affect Fracture Classification, Assessment of Stability, and Treatment Plan in Thoracolumbar Injuries?

PubMed Central

Kanna, Rishi Mugesh; Schroeder, Gregory D.; Oner, Frank Cumhur; Vialle, Luiz; Chapman, Jens; Dvorak, Marcel; Fehlings, Michael; Shetty, Ajoy Prasad; Schnake, Klaus; Kandziora, Frank; Vaccaro, Alexander R.

2017-01-01

Study Design: Prospective survey-based study. Objectives: The AO Spine thoracolumbar injury classification has been shown to have good reproducibility among clinicians. However, the influence of spine surgeons’ clinical experience on fracture classification, stability assessment, and decision on management based on this classification has not been studied. Furthermore, the usefulness of varying imaging modalities including radiographs, computed tomography (CT) and magnetic resonance imaging (MRI) in the decision process was also studied. Methods: Forty-one spine surgeons from different regions, acquainted with the AOSpine classification system, were provided with 30 thoracolumbar fractures in a 3-step assessment: first radiographs, followed by CT and MRI. Surgeons classified the fracture, evaluated stability, chose management, and identified reasons for any changes. The surgeons were divided into 2 groups based on years of clinical experience as <10 years (n = 12) and >10 years (n = 29). Results: There were no significant differences between the 2 groups in correctly classifying A1, B2, and C type fractures. Surgeons with less experience had more correct diagnosis in classifying A3 (47.2% vs 38.5% in step 1, 73.6% vs 60.3% in step 2 and 77.8% vs 65.5% in step 3), A4 (16.7% vs 24.1% in step 1, 72.9% vs 57.8% in step 2 and 70.8% vs 56.0% in step3) and B1 injuries (31.9% vs 20.7% in step 1, 41.7% vs 36.8% in step 2 and 38.9% vs 33.9% in step 3). In the assessment of fracture stability and decision on treatment, the less and more experienced surgeons performed equally. The selection of a particular treatment plan varied in all subtypes except in A1 and C type injuries. Conclusion: Surgeons’ experience did not significantly affect overall fracture classification, evaluating stability and planning the treatment. Surgeons with less experience had a higher percentage of correct classification in A3 and A4 injuries. Despite variations between them in classification, the assessment of overall stability and management decisions were similar between the 2 groups. PMID:28815158

Does the Spine Surgeon's Experience Affect Fracture Classification, Assessment of Stability, and Treatment Plan in Thoracolumbar Injuries?

PubMed

Rajasekaran, Shanmuganathan; Kanna, Rishi Mugesh; Schroeder, Gregory D; Oner, Frank Cumhur; Vialle, Luiz; Chapman, Jens; Dvorak, Marcel; Fehlings, Michael; Shetty, Ajoy Prasad; Schnake, Klaus; Kandziora, Frank; Vaccaro, Alexander R

2017-06-01

Prospective survey-based study. The AO Spine thoracolumbar injury classification has been shown to have good reproducibility among clinicians. However, the influence of spine surgeons' clinical experience on fracture classification, stability assessment, and decision on management based on this classification has not been studied. Furthermore, the usefulness of varying imaging modalities including radiographs, computed tomography (CT) and magnetic resonance imaging (MRI) in the decision process was also studied. Forty-one spine surgeons from different regions, acquainted with the AOSpine classification system, were provided with 30 thoracolumbar fractures in a 3-step assessment: first radiographs, followed by CT and MRI. Surgeons classified the fracture, evaluated stability, chose management, and identified reasons for any changes. The surgeons were divided into 2 groups based on years of clinical experience as <10 years (n = 12) and >10 years (n = 29). There were no significant differences between the 2 groups in correctly classifying A1, B2, and C type fractures. Surgeons with less experience had more correct diagnosis in classifying A3 (47.2% vs 38.5% in step 1, 73.6% vs 60.3% in step 2 and 77.8% vs 65.5% in step 3), A4 (16.7% vs 24.1% in step 1, 72.9% vs 57.8% in step 2 and 70.8% vs 56.0% in step3) and B1 injuries (31.9% vs 20.7% in step 1, 41.7% vs 36.8% in step 2 and 38.9% vs 33.9% in step 3). In the assessment of fracture stability and decision on treatment, the less and more experienced surgeons performed equally. The selection of a particular treatment plan varied in all subtypes except in A1 and C type injuries. Surgeons' experience did not significantly affect overall fracture classification, evaluating stability and planning the treatment. Surgeons with less experience had a higher percentage of correct classification in A3 and A4 injuries. Despite variations between them in classification, the assessment of overall stability and management decisions were similar between the 2 groups.

Validation of a new classification system for interprosthetic femoral fractures.

PubMed

Pires, Robinson Esteves Santos; Silveira, Marcelo Peixoto Sena; Resende, Alessandra Regina da Silva; Junior, Egidio Oliveira Santana; Campos, Tulio Vinicius Oliveira; Santos, Leandro Emilio Nascimento; Balbachevsky, Daniel; Andrade, Marco Antônio Percope de

2017-07-01

Interprosthetic femoral fracture (IFF) incidence is gradually increasing as the population is progressively ageing. However, treatment remains challenging due to several contributing factors, such as poor bone quality, patient comorbidities, small interprosthetic fragment, and prostheses instability. An effective and specific classification system is essential to optimize treatment management, therefore diminishing complication rates. This study aims to validate a previously described classification system for interprosthetic femoral fractures. Copyright © 2017 Elsevier Ltd. All rights reserved.

New decision support tool for acute lymphoblastic leukemia classification

NASA Astrophysics Data System (ADS)

Madhukar, Monica; Agaian, Sos; Chronopoulos, Anthony T.

2012-03-01

In this paper, we build up a new decision support tool to improve treatment intensity choice in childhood ALL. The developed system includes different methods to accurately measure furthermore cell properties in microscope blood film images. The blood images are exposed to series of pre-processing steps which include color correlation, and contrast enhancement. By performing K-means clustering on the resultant images, the nuclei of the cells under consideration are obtained. Shape features and texture features are then extracted for classification. The system is further tested on the classification of spectra measured from the cell nuclei in blood samples in order to distinguish normal cells from those affected by Acute Lymphoblastic Leukemia. The results show that the proposed system robustly segments and classifies acute lymphoblastic leukemia based on complete microscopic blood images.

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.

Subacute and non-acute casemix in Australia.

PubMed

Lee, L A; Eagar, K M; Smith, M C

1998-10-19

The costs of subacute care (palliative care, rehabilitation medicine, psychogeriatrics, and geriatric evaluation and management) and non-acute care (nursing home, convalescent and planned respite care) are not adequately described by existing casemix classifications. The predominant treatment goals in subacute care are enhancement of quality of life and/or improvement in functional status and, in non-acute care, maintenance of current health and functional status. A national classification system for this area has now been developed--the Australian National Sub-Acute and Non-Acute Patient Classification System (AN-SNAP). The AN-SNAP system, based on analysis of over 30,000 episodes of care, defines four case types of subacute care (palliative care, rehabilitation, psychogeriatric care, and geriatric evaluation and management and one case type of non-acute care (maintenance care), and classifies both overnight and ambulatory care. The AN-SNAP system reflects the goal of management--a change in functional status or improvement in quality of life--rather than the patient's diagnosis. It will complement the existing AN-DRG classification.

78 FR 18252 - Prevailing Rate Systems; North American Industry Classification System Based Federal Wage System...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-03-26

...-AM78 Prevailing Rate Systems; North American Industry Classification System Based Federal Wage System... 2007 North American Industry Classification System (NAICS) codes currently used in Federal Wage System... (OPM) issued a final rule (73 FR 45853) to update the 2002 North American Industry Classification...

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.

Resources planning for radiological incidents management

NASA Astrophysics Data System (ADS)

Hamid, Amy Hamijah binti Ab.; Rozan, Mohd Zaidi Abd; Ibrahim, Roliana; Deris, Safaai; Yunus, Muhd. Noor Muhd.

2017-01-01

Disastrous radiation and nuclear meltdown require an intricate scale of emergency health and social care capacity planning framework. In Malaysia, multiple agencies are responsible for implementing radiological and nuclear safety and security. This research project focused on the Radiological Trauma Triage (RTT) System. This system applies patient's classification based on their injury and level of radiation sickness. This classification prioritizes on the diagnostic and treatment of the casualties which include resources estimation of the medical delivery system supply and demand. Also, this system consists of the leading rescue agency organization and disaster coordinator, as well as the technical support and radiological medical response teams. This research implemented and developed the resources planning simulator for radiological incidents management. The objective of the simulator is to assist the authorities in planning their resources while managing the radiological incidents within the Internal Treatment Area (ITA), Reception Area Treatment (RAT) and Hospital Care Treatment (HCT) phases. The majority (75%) of the stakeholders and experts, who had been interviewed, witnessed and accepted that the simulator would be effective to resolve various types of disaster and resources management issues.

[Pay attention to the application of the international intraocular retinoblastoma classification and sequential multiple modality treatment].

PubMed

Fan, X Q

2017-08-11

Retinoblastoma (RB) is the most common intraocular malignancy in childhood. It may seriously affect vision, and even threaten the life. The early diagnosis rate of RB in China remains low, and the majority of patients are at late phase with high rates of enucleation and mortality. The International Intraocular Retinoblastoma Classification and TNM staging system are guidances for therapeutic choices and bases for prognosis evaluation. Based on the sequential multi-method treatment modality, chemotherapy combined with local therapy is the mainstream in dealing with RB, which may maximize the results of eye saving and even vision retaining. New therapeutic techniques including supra-selective ophthalmic artery interventional chemotherapy and intravitreal chemotherapy can further improve the efficacy of treatment, especially the eye salvage rate. The overall level of RB treatment should be improved by promoting the international staging, new therapeutic techniques, and the sequential multiple modality treatment. (Chin J Ophthalmol, 2017, 53: 561 - 565) .

A 3-tier classification of cerebral arteriovenous malformations. Clinical article.

PubMed

Spetzler, Robert F; Ponce, Francisco A

2011-03-01

The authors propose a 3-tier classification for cerebral arteriovenous malformations (AVMs). The classification is based on the original 5-tier Spetzler-Martin grading system, and reflects the treatment paradigm for these lesions. The implications of this modification in the literature are explored. Class A combines Grades I and II AVMs, Class B are Grade III AVMs, and Class C combines Grades IV and V AVMs. Recommended management is surgery for Class A AVMs, multimodality treatment for Class B, and observation for Class C, with exceptions to the latter including recurrent hemorrhages and progressive neurological deficits. To evaluate whether combining grades is warranted from the perspective of surgical outcomes, the 3-tier system was applied to 1476 patients from 7 surgical series in which results were stratified according to Spetzler-Martin grades. Pairwise comparisons of individual Spetzler-Martin grades in the series analyzed showed the fewest significant differences (p < 0.05) in outcomes between Grades I and II AVMs and between Grades IV and V AVMs. In the pooled data analysis, significant differences in outcomes were found between all grades except IV and V (p = 0.38), and the lowest relative risks were found between Grades I and II (1.066) and between Grades IV and V (1.095). Using the pooled data, the predictive accuracies for surgical outcomes of the 5-tier and 3-tier systems were equivalent (receiver operating characteristic curve area 0.711 and 0.713, respectively). Combining Grades I and II AVMs and combining Grades IV and V AVMs is justified in part because the differences in surgical results between these respective pairs are small. The proposed 3-tier classification of AVMs offers simplification of the Spetzler-Martin system, provides a guide to treatment, and is predictive of outcome. The revised classification not only simplifies treatment recommendations; by placing patients into 3 as opposed to 5 groups, statistical power is markedly increased for series comparisons.

The International Neuroblastoma Risk Group (INRG) Classification System: An INRG Task Force Report

PubMed Central

Cohn, Susan L.; Pearson, Andrew D.J.; London, Wendy B.; Monclair, Tom; Ambros, Peter F.; Brodeur, Garrett M.; Faldum, Andreas; Hero, Barbara; Iehara, Tomoko; Machin, David; Mosseri, Veronique; Simon, Thorsten; Garaventa, Alberto; Castel, Victoria; Matthay, Katherine K.

2009-01-01

Purpose Because current approaches to risk classification and treatment stratification for children with neuroblastoma (NB) vary greatly throughout the world, it is difficult to directly compare risk-based clinical trials. The International Neuroblastoma Risk Group (INRG) classification system was developed to establish a consensus approach for pretreatment risk stratification. Patients and Methods The statistical and clinical significance of 13 potential prognostic factors were analyzed in a cohort of 8,800 children diagnosed with NB between 1990 and 2002 from North America and Australia (Children's Oncology Group), Europe (International Society of Pediatric Oncology Europe Neuroblastoma Group and German Pediatric Oncology and Hematology Group), and Japan. Survival tree regression analyses using event-free survival (EFS) as the primary end point were performed to test the prognostic significance of the 13 factors. Results Stage, age, histologic category, grade of tumor differentiation, the status of the MYCN oncogene, chromosome 11q status, and DNA ploidy were the most highly statistically significant and clinically relevant factors. A new staging system (INRG Staging System) based on clinical criteria and tumor imaging was developed for the INRG Classification System. The optimal age cutoff was determined to be between 15 and 19 months, and 18 months was selected for the classification system. Sixteen pretreatment groups were defined on the basis of clinical criteria and statistically significantly different EFS of the cohort stratified by the INRG criteria. Patients with 5-year EFS more than 85%, more than 75% to ≤ 85%, ≥ 50% to ≤ 75%, or less than 50% were classified as very low risk, low risk, intermediate risk, or high risk, respectively. Conclusion By defining homogenous pretreatment patient cohorts, the INRG classification system will greatly facilitate the comparison of risk-based clinical trials conducted in different regions of the world and the development of international collaborative studies. PMID:19047291

76 FR 59901 - Isaria fumosorosea Apopka Strain 97; Exemption From the Requirement of a Tolerance

Federal Register 2010, 2011, 2012, 2013, 2014

2011-09-28

... persist, it would not survive the conditions water is subjected to in wastewater treatment systems or... Classification System (NAICS) codes have been provided to assist you and others in determining whether this... notice of filing. Based upon review of the data supporting the petition, EPA has modified the...

[Systematization of diseases and lesions of the endometrium by etiological and pathogenetical mechanisms of development to choose an optimal treatment].

PubMed

Boroda, A M

2004-03-01

Current clinical gynecology considers pathological states of endometrium (PSE) as one of the most challenging issue of the day. Many questions of etiology, pathogenesis, diagnostics, and treatment of PSE are still under discussion. Nowadays there isn't a whole agreed classification of PSE. Morphological classification remains the most widely used one, but morphological changes occurring in the endometrium don't show a wide variety of disorders related to these pathological states. A new clinicopathogenetic classification of PSE was proposed, which is based on choosing the optimal treatment with functional state of the disease taken into account. This classification helps us to perceive the problem as a whole with choosing functionally based treatment for each patient.

History of the FIGO cancer staging system.

PubMed

Odicino, Franco; Pecorelli, Sergio; Zigliani, Lucia; Creasman, William T

2008-05-01

The main objectives of any good staging system - essential to an evidence-based approach to cancer - are: to aid the clinician in planning treatment; to provide indication of prognosis; to assist the physician in evaluating the results of treatment; to facilitate the exchange of information between treatment centers, thus disseminating knowledge; and to contribute to continuing investigations into human malignancies. A good staging system must have 3 basic characteristics: it must be valid, reliable, and practical. The first staging system for gynecological cancers appeared around the turn of the 20th century and applied to the carcinoma of the cervix uteri-the most common cancer affecting women in high income countries at that time. The classification and staging of the other gynecological malignancies was not put forward until the 1950s. Over the years, these staging classifications - with the exception of cervical cancer and gestational trophoblastic neoplasia - have shifted from a clinical to a surgical-pathological basis. This paper reviews the history of the International Federation of Gynecology and Obstetrics (FIGO) cancer staging system, how it was developed, and why.

Advances in Risk Classification and Treatment Strategies for Neuroblastoma

PubMed Central

Pinto, Navin R.; Applebaum, Mark A.; Volchenboum, Samuel L.; Matthay, Katherine K.; London, Wendy B.; Ambros, Peter F.; Nakagawara, Akira; Berthold, Frank; Schleiermacher, Gudrun; Park, Julie R.; Valteau-Couanet, Dominique; Pearson, Andrew D.J.

2015-01-01

Risk-based treatment approaches for neuroblastoma have been ongoing for decades. However, the criteria used to define risk in various institutional and cooperative groups were disparate, limiting the ability to compare clinical trial results. To mitigate this problem and enhance collaborative research, homogenous pretreatment patient cohorts have been defined by the International Neuroblastoma Risk Group classification system. During the past 30 years, increasingly intensive, multimodality approaches have been developed to treat patients who are classified as high risk, whereas patients with low- or intermediate-risk neuroblastoma have received reduced therapy. This treatment approach has resulted in improved outcome, although survival for high-risk patients remains poor, emphasizing the need for more effective treatments. Increased knowledge regarding the biology and genetic basis of neuroblastoma has led to the discovery of druggable targets and promising, new therapeutic approaches. Collaborative efforts of institutions and international cooperative groups have led to advances in our understanding of neuroblastoma biology, refinements in risk classification, and stratified treatment strategies, resulting in improved outcome. International collaboration will be even more critical when evaluating therapies designed to treat small cohorts of patients with rare actionable mutations. PMID:26304901

The Unified Classification System (UCS): improving our understanding of periprosthetic fractures.

PubMed

Duncan, C P; Haddad, F S

2014-06-01

Periprosthetic fractures are an increasingly common complication following joint replacement. The principles which underpin their evaluation and treatment are common across the musculoskeletal system. The Unified Classification System proposes a rational approach to treatment, regardless of the bone that is broken or the joint involved. ©2014 The British Editorial Society of Bone & Joint Surgery.

The groningen laryngomalacia classification system--based on systematic review and dynamic airway changes.

PubMed

van der Heijden, Martijn; Dikkers, Frederik G; Halmos, Gyorgy B

2015-12-01

Laryngomalacia is the most common cause of dyspnea and stridor in newborn infants. Laryngomalacia is a dynamic change of the upper airway based on abnormally pliable supraglottic structures, which causes upper airway obstruction. In the past, different classification systems have been introduced. Until now no classification system is widely accepted and applied. Our goal is to provide a simple and complete classification system based on systematic literature search and our experiences. Retrospective cohort study with literature review. All patients with laryngomalacia under the age of 5 at time of diagnosis were included. Photo and video documentation was used to confirm diagnosis and characteristics of dynamic airway change. Outcome was compared with available classification systems in literature. Eighty-five patients were included. In contrast to other classification systems, only three typical different dynamic changes have been identified in our series. Two existing classification systems covered 100% of our findings, but there was an unnecessary overlap between different types in most of the systems. Based on our finding, we propose a new a classification system for laryngomalacia, which is purely based on dynamic airway changes. The groningen laryngomalacia classification is a new, simplified classification system with three types, based on purely dynamic laryngeal changes, tested in a tertiary referral center: Type 1: inward collapse of arytenoids cartilages, Type 2: medial displacement of aryepiglottic folds, and Type 3: posterocaudal displacement of epiglottis against the posterior pharyngeal wall. © 2015 Wiley Periodicals, Inc.

A proposal for a CT driven classification of left colon acute diverticulitis.

PubMed

Sartelli, Massimo; Moore, Frederick A; Ansaloni, Luca; Di Saverio, Salomone; Coccolini, Federico; Griffiths, Ewen A; Coimbra, Raul; Agresta, Ferdinando; Sakakushev, Boris; Ordoñez, Carlos A; Abu-Zidan, Fikri M; Karamarkovic, Aleksandar; Augustin, Goran; Costa Navarro, David; Ulrych, Jan; Demetrashvili, Zaza; Melo, Renato B; Marwah, Sanjay; Zachariah, Sanoop K; Wani, Imtiaz; Shelat, Vishal G; Kim, Jae Il; McFarlane, Michael; Pintar, Tadaja; Rems, Miran; Bala, Miklosh; Ben-Ishay, Offir; Gomes, Carlos Augusto; Faro, Mario Paulo; Pereira, Gerson Alves; Catani, Marco; Baiocchi, Gianluca; Bini, Roberto; Anania, Gabriele; Negoi, Ionut; Kecbaja, Zurabs; Omari, Abdelkarim H; Cui, Yunfeng; Kenig, Jakub; Sato, Norio; Vereczkei, Andras; Skrovina, Matej; Das, Koray; Bellanova, Giovanni; Di Carlo, Isidoro; Segovia Lohse, Helmut A; Kong, Victor; Kok, Kenneth Y; Massalou, Damien; Smirnov, Dmitry; Gachabayov, Mahir; Gkiokas, Georgios; Marinis, Athanasios; Spyropoulos, Charalampos; Nikolopoulos, Ioannis; Bouliaris, Konstantinos; Tepp, Jaan; Lohsiriwat, Varut; Çolak, Elif; Isik, Arda; Rios-Cruz, Daniel; Soto, Rodolfo; Abbas, Ashraf; Tranà, Cristian; Caproli, Emanuele; Soldatenkova, Darija; Corcione, Francesco; Piazza, Diego; Catena, Fausto

2015-01-01

Computed tomography (CT) imaging is the most appropriate diagnostic tool to confirm suspected left colonic diverticulitis. However, the utility of CT imaging goes beyond accurate diagnosis of diverticulitis; the grade of severity on CT imaging may drive treatment planning of patients presenting with acute diverticulitis. The appropriate management of left colon acute diverticulitis remains still debated because of the vast spectrum of clinical presentations and different approaches to treatment proposed. The authors present a new simple classification system based on both CT scan results driving decisions making management of acute diverticulitis that may be universally accepted for day to day practice.

Classifications of Acute Scaphoid Fractures: A Systematic Literature Review.

PubMed

Ten Berg, Paul W; Drijkoningen, Tessa; Strackee, Simon D; Buijze, Geert A

2016-05-01

Background In the lack of consensus, surgeon-based preference determines how acute scaphoid fractures are classified. There is a great variety of classification systems with considerable controversies. Purposes The purpose of this study was to provide an overview of the different classification systems, clarifying their subgroups and analyzing their popularity by comparing citation indexes. The intention was to improve data comparison between studies using heterogeneous fracture descriptions. Methods We performed a systematic review of the literature based on a search of medical literature from 1950 to 2015, and a manual search using the reference lists in relevant book chapters. Only original descriptions of classifications of acute scaphoid fractures in adults were included. Popularity was based on citation index as reported in the databases of Web of Science (WoS) and Google Scholar. Articles that were cited <10 times in WoS were excluded. Results Our literature search resulted in 308 potentially eligible descriptive reports of which 12 reports met the inclusion criteria. We distinguished 13 different (sub) classification systems based on (1) fracture location, (2) fracture plane orientation, and (3) fracture stability/displacement. Based on citations numbers, the Herbert classification was most popular, followed by the Russe and Mayo classifications. All classification systems were based on plain radiography. Conclusions Most classification systems were based on fracture location, displacement, or stability. Based on the controversy and limited reliability of current classification systems, suggested research areas for an updated classification include three-dimensional fracture pattern etiology and fracture fragment mobility assessed by dynamic imaging.

Refining Measurement of Substance Use Disorders among Women of Child-bearing Age Using Hospital Records: The Development of the Explicit-Mention Substance Abuse Need for Treatment in Women (EMSANT-W) Algorithm

PubMed Central

Derrington, Taletha Mae; Bernstein, Judith; Belanoff, Candice; Cabral, Howard J.; Babakhanlou-Chase, Hermik; Diop, Hafsatou; Evans, Stephen R.; Kotelchuck, Milton

2015-01-01

Substance use disorder (SUD) in women of reproductive age is associated with adverse health consequences for both women and their offspring. US states need a feasible population-based, case-identification tool to generate better approximations of SUD prevalence, treatment use, and treatment outcomes among women. This article presents the development of the Explicit Mention Substance Abuse Need for Treatment in Women (EMSANT-W), a gender-tailored tool based upon existing International Classification of Diseases, 9th Edition, Clinical Modification diagnostic code-based groupers that can be applied to hospital administrative data. Gender-tailoring entailed the addition of codes related to infants, pregnancy, and prescription drug abuse, as well as the creation of inclusion/exclusion rules based on other conditions present in the diagnostic record. Among 1,728,027 women and associated infants who accessed hospital care from January 1, 2002 to December 31, 2008 in Massachusetts, EMSANT-W identified 103,059 women with probable SUD. EMSANT-W identified 4,116 women who were not identified by the widely used Clinical Classifications Software for Mental Health and Substance Abuse (CCS-MHSA) and did not capture 853 women identified by CCS-MHSA. Content and approach innovations in EMSANT-W address potential limitations of the Clinical Classifications Software, and create a methodologically sound, gender-tailored and feasible population-based tool for identifying women of reproductive age in need of further evaluation for SUD treatment. Rapid changes in health care service infrastructure, delivery systems and policies require tools such as the EMSANT-W that provide more precise identification methods for sub-populations and can serve as the foundation for analyses of treatment use and outcomes. PMID:25680703

Refining Measurement of Substance Use Disorders Among Women of Child-Bearing Age Using Hospital Records: The Development of the Explicit-Mention Substance Abuse Need for Treatment in Women (EMSANT-W) Algorithm.

PubMed

Derrington, Taletha Mae; Bernstein, Judith; Belanoff, Candice; Cabral, Howard J; Babakhanlou-Chase, Hermik; Diop, Hafsatou; Evans, Stephen R; Kotelchuck, Milton

2015-10-01

Substance use disorder (SUD) in women of reproductive age is associated with adverse health consequences for both women and their offspring. US states need a feasible population-based, case-identification tool to generate better approximations of SUD prevalence, treatment use, and treatment outcomes among women. This article presents the development of the Explicit Mention Substance Abuse Need for Treatment in Women (EMSANT-W), a gender-tailored tool based upon existing International Classification of Diseases, 9th Edition, Clinical Modification diagnostic code-based groupers that can be applied to hospital administrative data. Gender-tailoring entailed the addition of codes related to infants, pregnancy, and prescription drug abuse, as well as the creation of inclusion/exclusion rules based on other conditions present in the diagnostic record. Among 1,728,027 women and associated infants who accessed hospital care from January 1, 2002 to December 31, 2008 in Massachusetts, EMSANT-W identified 103,059 women with probable SUD. EMSANT-W identified 4,116 women who were not identified by the widely used Clinical Classifications Software for Mental Health and Substance Abuse (CCS-MHSA) and did not capture 853 women identified by CCS-MHSA. Content and approach innovations in EMSANT-W address potential limitations of the Clinical Classifications Software, and create a methodologically sound, gender-tailored and feasible population-based tool for identifying women of reproductive age in need of further evaluation for SUD treatment. Rapid changes in health care service infrastructure, delivery systems and policies require tools such as the EMSANT-W that provide more precise identification methods for sub-populations and can serve as the foundation for analyses of treatment use and outcomes.

Web-based triage in a college health setting.

PubMed

Sole, Mary Lou; Stuart, Patricia L; Deichen, Michael

2006-01-01

The authors describe the initiation and use of a Web-based triage system in a college health setting. During the first 4 months of implementation, the system recorded 1,290 encounters. More women accessed the system (70%); the average age was 21.8 years. The Web-based triage system advised the majority of students to seek care within 24 hours; however, it recommended self-care management in 22.7% of encounters. Sore throat was the most frequent chief complaint (14.2%). A subset of 59 students received treatment at student health services after requesting an appointment via e-mail. The authors used kappa statistics to compare congruence between chief complaint and 24/7 WebMed classification (kappa = .94), between chief complaint and student health center diagnosis (kappa = .91), and between 24/7 WebMed classification and student health center diagnosis (kappa = .89). Initial evaluation showed high use and good accuracy of Web-based triage. This service provides education and advice to students about their health care concerns.

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.

Critical evaluation of the PALM-COEIN classification system among women with abnormal uterine bleeding in low-resource settings.

PubMed

Shubham, Divya; Kawthalkar, Anjali S

2018-05-01

To assess the feasibility of the PALM-COEIN system for the classification of abnormal uterine bleeding (AUB) in low-resource settings and to suggest modifications. A prospective study was conducted among women with AUB who were admitted to the gynecology ward of a tertiary care hospital and research center in central India between November 2014 and October 2016. All patients were managed as per department protocols. The causes of AUB were classified before treatment using the PALM-COEIN system (classification I) and on the basis of the histopathology reports of the hysterectomy specimens (classification II); the results were compared using classification II as the gold standard. The study included 200 women with AUB; hysterectomy was performed in 174 women. Preoperative classification of AUB per the PALM-COEIN system was correct in 130 (65.0%) women. Adenomyosis (evaluated by transvaginal ultrasonography) and endometrial hyperplasia (evaluated by endometrial curettage) were underdiagnosed. The PALM-COEIN classification system helps in deciding the best treatment modality for women with AUB on a case-by-case basis. The incorporation of suggested modifications will further strengthen its utility as a pretreatment classification system in low-resource settings. © 2017 International Federation of Gynecology and Obstetrics.

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).

Effect of classification-specific treatment on lumbopelvic motion during hip rotation in people with low back pain

PubMed Central

Hoffman, Shannon L; Johnson, Molly B; Zou, Dequan; Harris-Hayes, Marcie; Van Dillen, Linda R

2010-01-01

Increased and early lumbopelvic motion during trunk and limb movements is thought to contribute to low back pain (LBP). Therefore, reducing lumbopelvic motion could be an important component of physical therapy treatment. Our purpose was to examine the effects of classification-specific physical therapy treatment (Specific) based on the Movement System Impairment (MSI) model and non-specific treatment (Non-Specific) on lumbopelvic movement patterns during hip rotation in people with chronic LBP. We hypothesized that following treatment people in the Specific group would display decreased lumbopelvic rotation and achieve more hip rotation before lumbopelvic rotation began. We hypothesized that people in the Non-Specific group would display no change in these variables. Kinematic data collected before and after treatment for hip lateral and medial rotation in prone were analyzed. The Specific group (N=16) demonstrated significantly decreased lumbopelvic rotation and achieved greater hip rotation before the onset of lumbopelvic rotation after treatment with both hip lateral and medial rotation. The Non-Specific group (N=16) demonstrated significantly increased lumbopelvic rotation and no change in hip rotation achieved before the onset of lumbopelvic rotation. People who received treatment specific to their MSI LBP classification displayed decreased and later lumbopelvic motion with hip rotation, whereas people who received generalized non-specific treatment did not. PMID:21256073

The Use of the Mayo Clinic System for Differential Diagnosis of Dysarthria.

ERIC Educational Resources Information Center

Simmons, Katharine C.; Mayo, Robert

1997-01-01

A survey of 100 speech-language pathologists involved in the assessment and treatment of patients with dysarthria investigated their attitudes toward the Darley, Aronson, and Brown (DAB) method of classification. Results indicated that most clinicians, believing it helps in the design of a treatment protocol, used the DAB classification system.…

Breast Imaging-Reporting and Data System (BI-RADS) classification in 51 excised palpable pediatric breast masses.

PubMed

Koning, Jeffrey L; Davenport, Katherine P; Poole, Patricia S; Kruk, Peter G; Grabowski, Julia E

2015-10-01

The American College of Radiology Breast Imaging Reporting and Data System (BI-RADS) classification was developed to risk stratify breast lesions and guide surgical management based on imaging. Previous studies validating BI-RADS for US do not include pediatric patients. Most pediatric breast masses present as palpable lesions and frequently undergo ultrasound, which is often accompanied with a BI-RADS classification. Our study aimed to correlate BI-RADS with pathology findings to assess applicability of the classification system to pediatric patients. We performed a retrospective review of all patients who underwent excision of a breast mass at a single center from July 2010 to November 2013. We identified all patients who underwent preoperative ultrasound with BI-RADS classification. Demographic data, imaging results, and surgical pathology were analyzed and correlated. A total of 119 palpable masses were excised from 105 pediatric patients during the study period. Of 119 masses, 81 had preoperative ultrasound, and BI-RADS categories were given to 51 masses. Of these 51, all patients were female and the average age was 15.9 years. BI-RADS 4 was given to 25 of 51 masses (49%), and 100% of these lesions had benign pathology, the most common being fibroadenoma. Treatment algorithm based on BI-RADS classification may not be valid in pediatric patients. In this study, all patients with a BI-RADS 4 lesion had benign pathology. BI-RADS classification may overstate the risk of malignancy or need for biopsy in this population. Further validation of BI-RADS classification with large scale studies is needed in pediatric and adolescent patients. Copyright © 2015 Elsevier Inc. All rights reserved.

The Predictive Validity of a Gender-Responsive Needs Assessment: An Exploratory Study

ERIC Educational Resources Information Center

Salisbury, Emily J.; Van Voorhis, Patricia; Spiropoulos, Georgia V.

2009-01-01

Risk assessment and classification systems for women have been largely derived from male-based systems. As a result, many of the needs unique to women are not formally assessed or treated. Emerging research advocating a gender-responsive approach to the supervision and treatment of women offenders suggests that needs such as abuse, mental health,…

Bayesian classification for the selection of in vitro human embryos using morphological and clinical data.

PubMed

Morales, Dinora Araceli; Bengoetxea, Endika; Larrañaga, Pedro; García, Miguel; Franco, Yosu; Fresnada, Mónica; Merino, Marisa

2008-05-01

In vitro fertilization (IVF) is a medically assisted reproduction technique that enables infertile couples to achieve successful pregnancy. Given the uncertainty of the treatment, we propose an intelligent decision support system based on supervised classification by Bayesian classifiers to aid to the selection of the most promising embryos that will form the batch to be transferred to the woman's uterus. The aim of the supervised classification system is to improve overall success rate of each IVF treatment in which a batch of embryos is transferred each time, where the success is achieved when implantation (i.e. pregnancy) is obtained. Due to ethical reasons, different legislative restrictions apply in every country on this technique. In Spain, legislation allows a maximum of three embryos to form each transfer batch. As a result, clinicians prefer to select the embryos by non-invasive embryo examination based on simple methods and observation focused on morphology and dynamics of embryo development after fertilization. This paper proposes the application of Bayesian classifiers to this embryo selection problem in order to provide a decision support system that allows a more accurate selection than with the actual procedures which fully rely on the expertise and experience of embryologists. For this, we propose to take into consideration a reduced subset of feature variables related to embryo morphology and clinical data of patients, and from this data to induce Bayesian classification models. Results obtained applying a filter technique to choose the subset of variables, and the performance of Bayesian classifiers using them, are presented.

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.

Diagnosis and Management of Systemic Sclerosis: A Practical Approach.

PubMed

Lee, Jason J; Pope, Janet E

2016-02-01

Systemic sclerosis is a devastating multisystem rheumatologic condition that is characterized by autoimmunity, tissue fibrosis, obliterative vasculopathy and inflammation. Clinical presentation and course of the condition vary greatly, which complicates both diagnosis and corresponding treatment. In this regard, recent advances in disease understanding, both clinically and biochemically, have led to newer classification criteria for systemic sclerosis that are more inclusive than ever before. Still, significant disease modifying therapies do not yet exist for most patients. Therefore, organ-based management strategies are employed and research has been directed within this paradigm focusing on either the most debilitating symptoms, such as Raynaud's phenomenon, digital ulcers and cutaneous sclerosis, or life-threatening organ involvement such as interstitial lung disease and pulmonary arterial hypertension. The current trends in systemic sclerosis diagnosis, evidence-based treatment recommendations and potential future directions in systemic sclerosis treatment are discussed.

Mapping Fuels on the Okanogan and Wenatchee National Forests

Treesearch

Crystal L. Raymond; Lara-Karena B. Kellogg; Donald McKenzie

2006-01-01

Resource managers need spatially explicit fuels data to manage fire hazard and evaluate the ecological effects of wildland fires and fuel treatments. For this study, fuels were mapped on the Okanogan and Wenatchee National Forests (OWNF) using a rule-based method and the Fuels Characteristic Classification System (FCCS). The FCCS classifies fuels based on their...

Classification of patients with low back-related leg pain: a systematic review.

PubMed

Stynes, Siobhán; Konstantinou, Kika; Dunn, Kate M

2016-05-23

The identification of clinically relevant subgroups of low back pain (LBP) is considered the number one LBP research priority in primary care. One subgroup of LBP patients are those with back related leg pain. Leg pain frequently accompanies LBP and is associated with increased levels of disability and higher health costs than simple low back pain. Distinguishing between different types of low back-related leg pain (LBLP) is important for clinical management and research applications, but there is currently no clear agreement on how to define and identify LBLP due to nerve root involvement. The aim of this systematic review was to identify, describe and appraise papers that classify or subgroup populations with LBLP, and summarise how leg pain due to nerve root involvement is described and diagnosed in the various systems. The search strategy involved nine electronic databases including Medline and Embase, reference lists of eligible studies and relevant reviews. Selected papers were appraised independently by two reviewers using a standardised scoring tool. Of 13,358 initial potential eligible citations, 50 relevant papers were identified that reported on 22 classification systems. Papers were grouped according to purpose and criteria of the classification systems. Five themes emerged: (i) clinical features (ii) pathoanatomy (iii) treatment-based approach (iv) screening tools and prediction rules and (v) pain mechanisms. Three of the twenty two systems focused specifically on LBLP populations. Systems that scored highest following quality appraisal were ones where authors generally included statistical methods to develop their classifications, and supporting work had been published on the systems' validity, reliability and generalisability. There was lack of consistency in how LBLP due to nerve root involvement was described and diagnosed within the systems. Numerous classification systems exist that include patients with leg pain, a minority of them focus specifically on distinguishing between different presentations of leg pain. Further work is needed to identify clinically meaningful subgroups of LBLP patients, ideally based on large primary care cohort populations and using recommended methods for classification system development.

Eight months of clinical experience with the Self-Adjusting File system.

PubMed

Solomonov, Michael

2011-06-01

The Self-Adjusting File (SAF) system (ReDent-Nova, Ra'anana, Israel) has been recently introduced for the simultaneous instrumentation and irrigation of root canals. The SAF is claimed to adapt itself three dimensionally to the root canal, including its cross-section. It is operated with a continuous flow of sodium hypochlorite that is delivered into the root canal through the hollow file and claimed to be activated by sonic agitation of the irrigant. Our aim was to present for the first time clinical cases prepared with the SAF system and to describe a clinical classification of canals, according to their difficulty, with recommendations for endodontic treatment sequences for each category. This report is based on the experience of a single endodontist, who used the system to treat more than 50 consecutive primary endodontic cases over the prior 8 months. A clinical classification was developed which enabled the operator to select a treatment protocol for easy and optimal glide path preparation to be effectively used with the SAF file in the various root canals encountered in the clinical environment. Clinical classification of canal difficulty makes root canal treatment sequences with the SAF simple and predictable. Many types of cases can be treated with the SAF system although a novice user is advised to advance slowly along the learning curve from simpler to more complicated canals. Copyright © 2011 American Association of Endodontists. Published by Elsevier Inc. All rights reserved.

[Vasculitic neuropathy: novel classification, diagnosis and treatment].

PubMed

Kanda, Takashi

2014-01-01

The international standard of nomenclature and classification in vasculitis, CHCC 1994,was revised as CHCC 2012. In the first part of this review article I briefly summarized the CHCC 2012 and pointed out the changes in this revision, especially on the disorders related to vasculitic neuropathy. Notable changes include the introduction of new terms such as granulomatosis with polyangiitis and eosinophilic granulomatosis with polyangiitis. In the second part, I mentioned the tips for the diagnosis and treatment of vasculitic neuropathy. Because most of the vasculitic neuropathy patients require rigorous, long-standing immunosuppressive therapy, the accurate diagnosis based on the pathological detection of vasculitic changes is mandatory. In this regard, the value of sural nerve biopsy is still not ignorable. In the treatment of vascultic neuropathy, there are no controlled treatment trials and clinical practice is guided by experience from case series and indirectly by analogy with systemic vasculitis. Although combined therapy using prednisolone and cyclophosphamide is usually recommended by experts, tailor-made treatment regimen based on the conditions of each patient would produce the best outcome in vasculitic neuropathy.

Clinical staging: its importance in therapeutic decisions and clinical trials.

PubMed

Denis, L J

1992-02-01

International collaboration has resulted in a revised and unified 1987 formulation for the TNM classification in solid tumors. The simplification and eliminations of most variables caused difficulties for the clinical use of the system in some tumors such as bladder cancer. The approval of the proposed adaptation covering the tumor mass, subdividing the T4 category and adapting the stage grouping, resolves these difficulties. Published reports demonstrate support for the TNM system as a clinical base for treatment decisions and prognosis. The TNMG stage and grade are important basic prognostic factors, but other prognostic factors, especially biologic tumor activity, are under clinical investigation. The TNM classification is the initial evaluation after histologic confirmation of cancer to guide treatment and prognosis. The quality of the evaluation is enhanced by precise communication on the employed methodology.

Tissue classification and segmentation of pressure injuries using convolutional neural networks.

PubMed

Zahia, Sofia; Sierra-Sosa, Daniel; Garcia-Zapirain, Begonya; Elmaghraby, Adel

2018-06-01

This paper presents a new approach for automatic tissue classification in pressure injuries. These wounds are localized skin damages which need frequent diagnosis and treatment. Therefore, a reliable and accurate systems for segmentation and tissue type identification are needed in order to achieve better treatment results. Our proposed system is based on a Convolutional Neural Network (CNN) devoted to performing optimized segmentation of the different tissue types present in pressure injuries (granulation, slough, and necrotic tissues). A preprocessing step removes the flash light and creates a set of 5x5 sub-images which are used as input for the CNN network. The network output will classify every sub-image of the validation set into one of the three classes studied. The metrics used to evaluate our approach show an overall average classification accuracy of 92.01%, an average total weighted Dice Similarity Coefficient of 91.38%, and an average precision per class of 97.31% for granulation tissue, 96.59% for necrotic tissue, and 77.90% for slough tissue. Our system has been proven to make recognition of complicated structures in biomedical images feasible. Copyright © 2018 Elsevier B.V. All rights reserved.

Designing and Implementation of River Classification Assistant Management System

NASA Astrophysics Data System (ADS)

Zhao, Yinjun; Jiang, Wenyuan; Yang, Rujun; Yang, Nan; Liu, Haiyan

2018-03-01

In an earlier publication, we proposed a new Decision Classifier (DCF) for Chinese river classification based on their structures. To expand, enhance and promote the application of the DCF, we build a computer system to support river classification named River Classification Assistant Management System. Based on ArcEngine and ArcServer platform, this system implements many functions such as data management, extraction of river network, river classification, and results publication under combining Client / Server with Browser / Server framework.

Cancer Pain: A Critical Review of Mechanism-based Classification and Physical Therapy Management in Palliative Care

PubMed Central

Kumar, Senthil P

2011-01-01

Mechanism-based classification and physical therapy management of pain is essential to effectively manage painful symptoms in patients attending palliative care. The objective of this review is to provide a detailed review of mechanism-based classification and physical therapy management of patients with cancer pain. Cancer pain can be classified based upon pain symptoms, pain mechanisms and pain syndromes. Classification based upon mechanisms not only addresses the underlying pathophysiology but also provides us with an understanding behind patient's symptoms and treatment responses. Existing evidence suggests that the five mechanisms – central sensitization, peripheral sensitization, sympathetically maintained pain, nociceptive and cognitive-affective – operate in patients with cancer pain. Summary of studies showing evidence for physical therapy treatment methods for cancer pain follows with suggested therapeutic implications. Effective palliative physical therapy care using a mechanism-based classification model should be tailored to suit each patient's findings, using a biopsychosocial model of pain. PMID:21976851

Advances in Risk Classification and Treatment Strategies for Neuroblastoma.

PubMed

Pinto, Navin R; Applebaum, Mark A; Volchenboum, Samuel L; Matthay, Katherine K; London, Wendy B; Ambros, Peter F; Nakagawara, Akira; Berthold, Frank; Schleiermacher, Gudrun; Park, Julie R; Valteau-Couanet, Dominique; Pearson, Andrew D J; Cohn, Susan L

2015-09-20

Risk-based treatment approaches for neuroblastoma have been ongoing for decades. However, the criteria used to define risk in various institutional and cooperative groups were disparate, limiting the ability to compare clinical trial results. To mitigate this problem and enhance collaborative research, homogenous pretreatment patient cohorts have been defined by the International Neuroblastoma Risk Group classification system. During the past 30 years, increasingly intensive, multimodality approaches have been developed to treat patients who are classified as high risk, whereas patients with low- or intermediate-risk neuroblastoma have received reduced therapy. This treatment approach has resulted in improved outcome, although survival for high-risk patients remains poor, emphasizing the need for more effective treatments. Increased knowledge regarding the biology and genetic basis of neuroblastoma has led to the discovery of druggable targets and promising, new therapeutic approaches. Collaborative efforts of institutions and international cooperative groups have led to advances in our understanding of neuroblastoma biology, refinements in risk classification, and stratified treatment strategies, resulting in improved outcome. International collaboration will be even more critical when evaluating therapies designed to treat small cohorts of patients with rare actionable mutations. © 2015 by American Society of Clinical Oncology.

[Nursing care systematization for outpatient treatment care of patients with multiple sclerosis].

PubMed

Corso, Nair Assunta Antônia; Gondim, Ana Paula Soares; Dalmeida, Patrícia Chagas Rocha; Albuquerque, Maria Girlene de Freitas

2013-06-01

An experience report of nurses in the implementation of care systematization in ambulatory care in an interdisciplinary care center for patients with multiple sclerosis of a public hospital in Fortaleza, Ceará, Brazil. This implementation is based on the NANDA International, Inc., Nursing Interventions Classification, and Nursing Outcomes Classifications. One of the results concerns systemized nursing care, which has enabled the identification and understanding of the responses of MS patients to potential and current health problems. Systematization entails expanding knowledge through a practice based on approach and encourage further research scientific evidence, in addition to promoting the role of the nurse in acomprehensive approachand encourage further research.

Proposed new classification scheme for chemical injury to the human eye.

PubMed

Bagley, Daniel M; Casterton, Phillip L; Dressler, William E; Edelhauser, Henry F; Kruszewski, Francis H; McCulley, James P; Nussenblatt, Robert B; Osborne, Rosemarie; Rothenstein, Arthur; Stitzel, Katherine A; Thomas, Karluss; Ward, Sherry L

2006-07-01

Various ocular alkali burn classification schemes have been published and used to grade human chemical eye injuries for the purpose of identifying treatments and forecasting outcomes. The ILSI chemical eye injury classification scheme was developed for the additional purpose of collecting detailed human eye injury data to provide information on the mechanisms associated with chemical eye injuries. This information will have clinical application, as well as use in the development and validation of new methods to assess ocular toxicity. A panel of ophthalmic researchers proposed the new classification scheme based upon current knowledge of the mechanisms of eye injury, and their collective clinical and research experience. Additional ophthalmologists and researchers were surveyed to critique the scheme. The draft scheme was revised, and the proposed scheme represents the best consensus from at least 23 physicians and scientists. The new scheme classifies chemical eye injury into five categories based on clinical signs, symptoms, and expected outcomes. Diagnostic classification is based primarily on two clinical endpoints: (1) the extent (area) of injury at the limbus, and (2) the degree of injury (area and depth) to the cornea. The new classification scheme provides a uniform system for scoring eye injury across chemical classes, and provides enough detail for the clinician to collect data that will be relevant to identifying the mechanisms of ocular injury.

3P: Personalized Pregnancy Prediction in IVF Treatment Process

NASA Astrophysics Data System (ADS)

Uyar, Asli; Ciray, H. Nadir; Bener, Ayse; Bahceci, Mustafa

We present an intelligent learning system for improving pregnancy success rate of IVF treatment. Our proposed model uses an SVM based classification system for training a model from past data and making predictions on implantation outcome of new embryos. This study employs an embryo-centered approach. Each embryo is represented with a data feature vector including 17 features related to patient characteristics, clinical diagnosis, treatment method and embryo morphological parameters. Our experimental results demonstrate a prediction accuracy of 82.7%. We have obtained the IVF dataset from Bahceci Women Health, Care Centre, in Istanbul, Turkey.

Analysis of dual tree M-band wavelet transform based features for brain image classification.

PubMed

Ayalapogu, Ratna Raju; Pabboju, Suresh; Ramisetty, Rajeswara Rao

2018-04-29

The most complex organ in the human body is the brain. The unrestrained growth of cells in the brain is called a brain tumor. The cause of a brain tumor is still unknown and the survival rate is lower than other types of cancers. Hence, early detection is very important for proper treatment. In this study, an efficient computer-aided diagnosis (CAD) system is presented for brain image classification by analyzing MRI of the brain. At first, the MRI brain images of normal and abnormal categories are modeled by using the statistical features of dual tree m-band wavelet transform (DTMBWT). A maximum margin classifier, support vector machine (SVM) is then used for the classification and validated with k-fold approach. Results show that the system provides promising results on a repository of molecular brain neoplasia data (REMBRANDT) with 97.5% accuracy using 4 th level statistical features of DTMBWT. Viewing the experimental results, we conclude that the system gives a satisfactory performance for the brain image classification. © 2018 International Society for Magnetic Resonance in Medicine.

CHANGING OUR DIAGNOSTIC PARADIGM: MOVEMENT SYSTEM DIAGNOSTIC CLASSIFICATION

PubMed Central

Kamonseki, Danilo H.; Staker, Justin L.; Lawrence, Rebekah L.; Braman, Jonathan P.

2017-01-01

Proper diagnosis is a first step in applying best available treatments, and prognosticating outcomes for clients. Currently, the majority of musculoskeletal diagnoses are classified according to pathoanatomy. However, the majority of physical therapy treatments are applied toward movement system impairments or pain. While advocated within the physical therapy profession for over thirty years, diagnostic classification within a movement system framework has not been uniformly developed or adopted. We propose a basic framework and rationale for application of a movement system diagnostic classification for atraumatic shoulder pain conditions, as a case for the broader development of movement system diagnostic labels. Shifting our diagnostic paradigm has potential to enhance communication, improve educational efficiency, facilitate research, directly link to function, improve clinical care, and accelerate preventive interventions. PMID:29158950

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.

42 CFR 412.513 - Patient classification system.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 42 Public Health 2 2010-10-01 2010-10-01 false Patient classification system. 412.513 Section 412... Long-Term Care Hospitals § 412.513 Patient classification system. (a) Classification methodology. CMS...-DRGs. (1) The classification of a particular discharge is based, as appropriate, on the patient's age...

42 CFR 412.513 - Patient classification system.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 42 Public Health 2 2011-10-01 2011-10-01 false Patient classification system. 412.513 Section 412... Long-Term Care Hospitals § 412.513 Patient classification system. (a) Classification methodology. CMS...-DRGs. (1) The classification of a particular discharge is based, as appropriate, on the patient's age...

Reliability of McConnell's classification of patellar orientation in symptomatic and asymptomatic subjects.

PubMed

Watson, C J; Propps, M; Galt, W; Redding, A; Dobbs, D

1999-07-01

Test-retest reliability study with blinded testers. To determine the intratester reliability of the McConnell classification system and to determine whether the intertester reliability of this system would be improved by one-on-one training of the testers, increasing the variability and numbers of subjects, blinding the testers to the absence or presence of patellofemoral pain syndrome, and adhering to the McConnell classification system as it is taught in the "McConnell Patellofemoral Treatment Plan" continuing education course. The McConnell classification system is currently used by physical therapy clinicians to quantify static patellar orientation. The measurements generated from this system purportedly guide the therapist in the application of patellofemoral tape and in assessment of the efficacy of treatment interventions on changing patellar orientation. Fifty-six subjects (age range, 21-65 years) provided a total of 101 knees for assessment. Seventy-six knees did not produce symptoms. A researcher who did not participate in the measuring process determined that 17 subjects had patellofemoral pain syndrome in 25 knees. Two testers concurrently measured static patellar orientation (anterior/posterior and medial/lateral tilt, medial/lateral glide, and patellar rotation) on subjects, using the McConnell classification system. Repeat measures were performed 3-7 days later. A kappa (kappa) statistic was used to assess the degree of agreement within each tester and between testers. The kappa coefficients for intratester reliability varied from -0.06 to 0.35. Intertester reliability ranged from -0.03 to 0.19. The McConnell classification system, in its current form, does not appear to be very reliable. Intratester reliability ranged from poor to fair, and intertester reliability was poor to slight. This system should not be used as a measurement tool or as a basis for treatment decisions.

The ESHRE/ESGE consensus on the classification of female genital tract congenital anomalies.

PubMed

Grimbizis, Grigoris F; Gordts, Stephan; Di Spiezio Sardo, Attilio; Brucker, Sara; De Angelis, Carlo; Gergolet, Marco; Li, Tin-Chiu; Tanos, Vasilios; Brölmann, Hans; Gianaroli, Luca; Campo, Rudi

2013-08-01

What classification system is more suitable for the accurate, clear, simple and related to the clinical management categorization of female genital anomalies? The new ESHRE/ESGE classification system of female genital anomalies is presented. Congenital malformations of the female genital tract are common miscellaneous deviations from normal anatomy with health and reproductive consequences. Until now, three systems have been proposed for their categorization but all of them are associated with serious limitations. The European Society of Human Reproduction and Embryology (ESHRE) and the European Society for Gynaecological Endoscopy (ESGE) have established a common Working Group, under the name CONUTA (CONgenital UTerine Anomalies), with the goal of developing a new updated classification system. A scientific committee (SC) has been appointed to run the project, looking also for consensus within the scientists working in the field. The new system is designed and developed based on (i) scientific research through critical review of current proposals and preparation of an initial proposal for discussion between the experts, (ii) consensus measurement among the experts through the use of the DELPHI procedure and (iii) consensus development by the SC, taking into account the results of the DELPHI procedure and the comments of the experts. Almost 90 participants took part in the process of development of the ESHRE/ESGE classification system, contributing with their structured answers and comments. The ESHRE/ESGE classification system is based on anatomy. Anomalies are classified into the following main classes, expressing uterine anatomical deviations deriving from the same embryological origin: U0, normal uterus; U1, dysmorphic uterus; U2, septate uterus; U3, bicorporeal uterus; U4, hemi-uterus; U5, aplastic uterus; U6, for still unclassified cases. Main classes have been divided into sub-classes expressing anatomical varieties with clinical significance. Cervical and vaginal anomalies are classified independently into sub-classes having clinical significance. The ESHRE/ESGE classification of female genital anomalies seems to fulfill the expectations and the needs of the experts in the field, but its clinical value needs to be proved in everyday practice. The ESHRE/ESGE classification system of female genital anomalies could be used as a starting point for the development of guidelines for their diagnosis and treatment. None.

A domains-based taxonomy of supported accommodation for people with severe and persistent mental illness.

PubMed

Siskind, Dan; Harris, Meredith; Pirkis, Jane; Whiteford, Harvey

2013-06-01

A lack of definitional clarity in supported accommodation and the absence of a widely accepted system for classifying supported accommodation models creates barriers to service planning and evaluation. We undertook a systematic review of existing supported accommodation classification systems. Using a structured system for qualitative data analysis, we reviewed the stratification features in these classification systems, identified the key elements of supported accommodation and arranged them into domains and dimensions to create a new taxonomy. The existing classification systems were mapped onto the new taxonomy to verify the domains and dimensions. Existing classification systems used either a service-level characteristic or programmatic approach. We proposed a taxonomy based around four domains: duration of tenure; patient characteristics; housing characteristics; and service characteristics. All of the domains in the taxonomy were drawn from the existing classification structures; however, none of the existing classification structures covered all of the domains in the taxonomy. Existing classification systems are regionally based, limited in scope and lack flexibility. A domains-based taxonomy can allow more accurate description of supported accommodation services, aid in identifying the service elements likely to improve outcomes for specific patient populations, and assist in service planning.

Experiments with a novel content-based image retrieval software: can we eliminate classification systems in adolescent idiopathic scoliosis?

PubMed

Menon, K Venugopal; Kumar, Dinesh; Thomas, Tessamma

2014-02-01

Study Design Preliminary evaluation of new tool. Objective To ascertain whether the newly developed content-based image retrieval (CBIR) software can be used successfully to retrieve images of similar cases of adolescent idiopathic scoliosis (AIS) from a database to help plan treatment without adhering to a classification scheme. Methods Sixty-two operated cases of AIS were entered into the newly developed CBIR database. Five new cases of different curve patterns were used as query images. The images were fed into the CBIR database that retrieved similar images from the existing cases. These were analyzed by a senior surgeon for conformity to the query image. Results Within the limits of variability set for the query system, all the resultant images conformed to the query image. One case had no similar match in the series. The other four retrieved several images that were matching with the query. No matching case was left out in the series. The postoperative images were then analyzed to check for surgical strategies. Broad guidelines for treatment could be derived from the results. More precise query settings, inclusion of bending films, and a larger database will enhance accurate retrieval and better decision making. Conclusion The CBIR system is an effective tool for accurate documentation and retrieval of scoliosis images. Broad guidelines for surgical strategies can be made from the postoperative images of the existing cases without adhering to any classification scheme.

Clinically orientated classification incorporating shoulder balance for the surgical treatment of adolescent idiopathic scoliosis.

PubMed

Elsebaie, H B; Dannawi, Z; Altaf, F; Zaidan, A; Al Mukhtar, M; Shaw, M J; Gibson, A; Noordeen, H

2016-02-01

The achievement of shoulder balance is an important measure of successful scoliosis surgery. No previously described classification system has taken shoulder balance into account. We propose a simple classification system for AIS based on two components which include the curve type and shoulder level. Altogether, three curve types have been defined according to the size and location of the curves, each curve pattern is subdivided into type A or B depending on the shoulder level. This classification was tested for interobserver reproducibility and intraobserver reliability. A retrospective analysis of the radiographs of 232 consecutive cases of AIS patients treated surgically between 2005 and 2009 was also performed. Three major types and six subtypes were identified. Type I accounted for 30 %, type II 28 % and type III 42 %. The retrospective analysis showed three patients developed a decompensation that required extension of the fusion. One case developed worsening of shoulder balance requiring further surgery. This classification was tested for interobserver and intraobserver reliability. The mean kappa coefficients for interobserver reproducibility ranged from 0.89 to 0.952, while the mean kappa value for intraobserver reliability was 0.964 indicating a good-to-excellent reliability. The treatment algorithm guides the spinal surgeon to achieve optimal curve correction and postoperative shoulder balance whilst fusing the smallest number of spinal segments. The high interobserver reproducibility and intraobserver reliability makes it an invaluable tool to describe scoliosis curves in everyday clinical practice.

Application of random forests methods to diabetic retinopathy classification analyses.

PubMed

Casanova, Ramon; Saldana, Santiago; Chew, Emily Y; Danis, Ronald P; Greven, Craig M; Ambrosius, Walter T

2014-01-01

Diabetic retinopathy (DR) is one of the leading causes of blindness in the United States and world-wide. DR is a silent disease that may go unnoticed until it is too late for effective treatment. Therefore, early detection could improve the chances of therapeutic interventions that would alleviate its effects. Graded fundus photography and systemic data from 3443 ACCORD-Eye Study participants were used to estimate Random Forest (RF) and logistic regression classifiers. We studied the impact of sample size on classifier performance and the possibility of using RF generated class conditional probabilities as metrics describing DR risk. RF measures of variable importance are used to detect factors that affect classification performance. Both types of data were informative when discriminating participants with or without DR. RF based models produced much higher classification accuracy than those based on logistic regression. Combining both types of data did not increase accuracy but did increase statistical discrimination of healthy participants who subsequently did or did not have DR events during four years of follow-up. RF variable importance criteria revealed that microaneurysms counts in both eyes seemed to play the most important role in discrimination among the graded fundus variables, while the number of medicines and diabetes duration were the most relevant among the systemic variables. We have introduced RF methods to DR classification analyses based on fundus photography data. In addition, we propose an approach to DR risk assessment based on metrics derived from graded fundus photography and systemic data. Our results suggest that RF methods could be a valuable tool to diagnose DR diagnosis and evaluate its progression.

Evidence and evidence gaps in the treatment of Eustachian tube dysfunction and otitis media

PubMed Central

Teschner, Magnus

2016-01-01

Evidence-based medicine is an approach to medical treatment intended to optimize patient-oriented decision-making on the basis of empirically proven effectiveness. For this purpose, a classification system has been established to categorize studies – and hence therapy options – in respect of associated evidence according to defined criteria. The Eustachian tube connects the nasopharynx with the middle ear cavity. Its key function is to ensure middle ear ventilation. Compromised ventilation results in inflammatory middle ear disorders. Numerous evidence-based therapy options are available for the treatment of impaired middle ear ventilation and otitis media, the main therapeutic approach being antibiotic treatment. More recent procedures such as balloon dilation of the Eustachian tube have also shown initial success but must undergo further evaluation with regard to evidence. There is, as yet, no evidence for some of the other long-established procedures. Owing to the multitude of variables, the classification of evidence levels for various treatment approaches calls for highly diversified assessment. Numerous evidence-based studies are therefore necessary in order to evaluate the evidence pertaining to existing and future therapy solutions for impaired middle ear ventilation and otitis media. If this need is addressed, a wealth of implications can be expected for therapeutic approaches in the years to come. PMID:28025605

Prostate segmentation by sparse representation based classification

PubMed Central

Gao, Yaozong; Liao, Shu; Shen, Dinggang

2012-01-01

Purpose: The segmentation of prostate in CT images is of essential importance to external beam radiotherapy, which is one of the major treatments for prostate cancer nowadays. During the radiotherapy, the prostate is radiated by high-energy x rays from different directions. In order to maximize the dose to the cancer and minimize the dose to the surrounding healthy tissues (e.g., bladder and rectum), the prostate in the new treatment image needs to be accurately localized. Therefore, the effectiveness and efficiency of external beam radiotherapy highly depend on the accurate localization of the prostate. However, due to the low contrast of the prostate with its surrounding tissues (e.g., bladder), the unpredicted prostate motion, and the large appearance variations across different treatment days, it is challenging to segment the prostate in CT images. In this paper, the authors present a novel classification based segmentation method to address these problems. Methods: To segment the prostate, the proposed method first uses sparse representation based classification (SRC) to enhance the prostate in CT images by pixel-wise classification, in order to overcome the limitation of poor contrast of the prostate images. Then, based on the classification results, previous segmented prostates of the same patient are used as patient-specific atlases to align onto the current treatment image and the majority voting strategy is finally adopted to segment the prostate. In order to address the limitations of the traditional SRC in pixel-wise classification, especially for the purpose of segmentation, the authors extend SRC from the following four aspects: (1) A discriminant subdictionary learning method is proposed to learn a discriminant and compact representation of training samples for each class so that the discriminant power of SRC can be increased and also SRC can be applied to the large-scale pixel-wise classification. (2) The L1 regularized sparse coding is replaced by the elastic net in order to obtain a smooth and clear prostate boundary in the classification result. (3) Residue-based linear regression is incorporated to improve the classification performance and to extend SRC from hard classification to soft classification. (4) Iterative SRC is proposed by using context information to iteratively refine the classification results. Results: The proposed method has been comprehensively evaluated on a dataset consisting of 330 CT images from 24 patients. The effectiveness of the extended SRC has been validated by comparing it with the traditional SRC based on the proposed four extensions. The experimental results show that our extended SRC can obtain not only more accurate classification results but also smoother and clearer prostate boundary than the traditional SRC. Besides, the comparison with other five state-of-the-art prostate segmentation methods indicates that our method can achieve better performance than other methods under comparison. Conclusions: The authors have proposed a novel prostate segmentation method based on the sparse representation based classification, which can achieve considerably accurate segmentation results in CT prostate segmentation. PMID:23039673

Prostate segmentation by sparse representation based classification.

PubMed

Gao, Yaozong; Liao, Shu; Shen, Dinggang

2012-10-01

The segmentation of prostate in CT images is of essential importance to external beam radiotherapy, which is one of the major treatments for prostate cancer nowadays. During the radiotherapy, the prostate is radiated by high-energy x rays from different directions. In order to maximize the dose to the cancer and minimize the dose to the surrounding healthy tissues (e.g., bladder and rectum), the prostate in the new treatment image needs to be accurately localized. Therefore, the effectiveness and efficiency of external beam radiotherapy highly depend on the accurate localization of the prostate. However, due to the low contrast of the prostate with its surrounding tissues (e.g., bladder), the unpredicted prostate motion, and the large appearance variations across different treatment days, it is challenging to segment the prostate in CT images. In this paper, the authors present a novel classification based segmentation method to address these problems. To segment the prostate, the proposed method first uses sparse representation based classification (SRC) to enhance the prostate in CT images by pixel-wise classification, in order to overcome the limitation of poor contrast of the prostate images. Then, based on the classification results, previous segmented prostates of the same patient are used as patient-specific atlases to align onto the current treatment image and the majority voting strategy is finally adopted to segment the prostate. In order to address the limitations of the traditional SRC in pixel-wise classification, especially for the purpose of segmentation, the authors extend SRC from the following four aspects: (1) A discriminant subdictionary learning method is proposed to learn a discriminant and compact representation of training samples for each class so that the discriminant power of SRC can be increased and also SRC can be applied to the large-scale pixel-wise classification. (2) The L1 regularized sparse coding is replaced by the elastic net in order to obtain a smooth and clear prostate boundary in the classification result. (3) Residue-based linear regression is incorporated to improve the classification performance and to extend SRC from hard classification to soft classification. (4) Iterative SRC is proposed by using context information to iteratively refine the classification results. The proposed method has been comprehensively evaluated on a dataset consisting of 330 CT images from 24 patients. The effectiveness of the extended SRC has been validated by comparing it with the traditional SRC based on the proposed four extensions. The experimental results show that our extended SRC can obtain not only more accurate classification results but also smoother and clearer prostate boundary than the traditional SRC. Besides, the comparison with other five state-of-the-art prostate segmentation methods indicates that our method can achieve better performance than other methods under comparison. The authors have proposed a novel prostate segmentation method based on the sparse representation based classification, which can achieve considerably accurate segmentation results in CT prostate segmentation.

Interplay of biopharmaceutics, biopharmaceutics drug disposition and salivary excretion classification systems

PubMed Central

Idkaidek, Nasir M.

2013-01-01

The aim of this commentary is to investigate the interplay of Biopharmaceutics Classification System (BCS), Biopharmaceutics Drug Disposition Classification System (BDDCS) and Salivary Excretion Classification System (SECS). BCS first classified drugs based on permeability and solubility for the purpose of predicting oral drug absorption. Then BDDCS linked permeability with hepatic metabolism and classified drugs based on metabolism and solubility for the purpose of predicting oral drug disposition. On the other hand, SECS classified drugs based on permeability and protein binding for the purpose of predicting the salivary excretion of drugs. The role of metabolism, rather than permeability, on salivary excretion is investigated and the results are not in agreement with BDDCS. Conclusion The proposed Salivary Excretion Classification System (SECS) can be used as a guide for drug salivary excretion based on permeability (not metabolism) and protein binding. PMID:24493977

The role of T1 perfusion-based classification in magnetic resonance-guided high-intensity focused ultrasound ablation of uterine fibroids.

PubMed

Keserci, Bilgin; Duc, Nguyen Minh

2017-12-01

To comparatively evaluate the role of magnetic resonance (MR) T1 perfusion-based time-signal intensity (SI) curves of fibroid tissue and the myometrium in classification of fibroids for predicting treatment outcomes of high-intensity focused ultrasound (HIFU) treatment. The fibroids of 74 women who underwent MR-HIFU treatment were classified into group A (time-SI curve of fibroid lower than that of the myometrium) and group B (time-SI curve of fibroid equal to or higher than that of the myometrium). Non-perfused volume (NPV) ratios immediately after treatment and fibroid volume reduction ratios and symptom severity scores (SSS) at the 6-month follow-up were retrospectively assessed. The immediate NPV ratios in groups A and B were 95.3 ± 6.3% (n = 62) and 63.8 ± 11% (n = 12), respectively. At the 6-month follow-up, the fibroid volume reduction ratios in groups A and B were 0.52 ± 0.14 (n = 50) and 0.07 ± 0.14 (n = 11), with the corresponding improvement in mean transformed SSS being 0.86 ± 0.14 and 0.19 ± 0.3, respectively. No serious adverse effects were reported. Our novel classification method could play an important role in classifying fibroids for predicting the immediate outcomes of HIFU treatment. • MRI is an important modality for outcome prediction in HIFU treatment • Patient selection is a significant factor for achieving high NPV ratio • NPV ratio is very strongly correlated with T1 perfusion-based classification • T1 perfusion-based classification is a strong predictor of treatment outcome.

Surgeon preferences regarding antibiotic prophylaxis for ballistic fractures.

PubMed

Marecek, Geoffrey S; Earhart, Jeffrey S; Gardner, Michael J; Davis, Jason; Merk, Bradley R

2016-06-01

Scant evidence exists to support antibiotic use for low velocity ballistic fractures (LVBF). We therefore sought to define current practice patterns. We hypothesized that most surgeons prescribe antibiotics for LVBF, prescribing is not driven by institutional protocols, and that decisions are based on protocols utilized for blunt trauma. A web-based questionnaire was emailed to the membership of the Orthopaedic Trauma Association (OTA). The questionnaire included demographic information and questions about LVBF treatment practices. Two hundred and twenty surgeons responded. One hundred and fifty-four (70 %) respondents worked at a Level-1 trauma center, 176 (80 %) had received fellowship education in orthopaedic trauma and 104 (47 %) treated at least 10 ballistic fractures annually. Responses were analyzed with SAS 9.3 for Windows (SAS Institute Inc, Cary, NC). One hundred eighty-six respondents (86 %) routinely provide antibiotics for LVBF. Those who did not were more apt to do so for intra-articular fractures (8/16, 50 %) and pelvic fractures with visceral injury (10/16, 63 %). Most surgeons (167, 76 %) do not believe the Gustilo-Anderson classification applies to ballistic fractures, and (20/29, 70 %) do not base their antibiotic choice on the classification system. Few institutions (58, 26 %) have protocols guiding antibiotic use for LVBF. Routine antibiotic use for LVBF is common; however, practice is not dictated by institutional protocol. Although antibiotic use generally follows current blunt trauma guidelines, surgeons do not base their treatment decisions the Gustilo-Anderson classification. Given the high rate of antibiotic use for LVBF, further study should focus on providing evidence-based treatment guidelines.

Preliminary report on the International Conference for the Development of Standards for the Treatment of Anorectal Malformations.

PubMed

Holschneider, Alexander; Hutson, John; Peña, Albert; Beket, Elhamy; Chatterjee, Subir; Coran, Arnold; Davies, Michael; Georgeson, Keith; Grosfeld, Jay; Gupta, Devendra; Iwai, Naomi; Kluth, Dieter; Martucciello, Giuseppe; Moore, Samuel; Rintala, Risto; Smith, E Durham; Sripathi, D V; Stephens, Douglas; Sen, Sudipta; Ure, Benno; Grasshoff, Sabine; Boemers, Thomas; Murphy, Feilin; Söylet, Yunus; Dübbers, Martin; Kunst, Marc

2005-10-01

Anorectal malformations (ARM) are common congenital anomalies seen throughout the world. Comparison of outcome data has been hindered because of confusion related to classification and assessment systems. The goals of the Krinkenbeck Conference on ARM was to develop standards for an International Classification of ARM based on a modification of fistula type and adding rare and regional variants, and design a system for comparable follow up studies. Lesions were classified into major clinical groups based on the fistula location (perineal, recto-urethral, recto-vesical, vestibular), cloacal lesions, those with no fistula and anal stenosis. Rare and regional variants included pouch colon, rectal atresia or stenosis, rectovaginal fistula, H-fistula and others. Groups would be analyzed according to the type of procedure performed stratified for confounding associated conditions such as sacral anomalies and tethered cord. A standard method for postoperative assessment of continence was determined. A new International diagnostic classification system, operative groupings and a method of postoperative assessment of continence was developed by consensus of a large contingent of participants experienced in the management of patients with ARM. These methods should allow for a common standardization of diagnosis and comparing postoperative results.

TNM: evolution and relation to other prognostic factors.

PubMed

Sobin, Leslie H

2003-01-01

The TNM Classification describes the anatomic extent of cancer. TNM's ability to separately classify the individual tumor (T), node (N), and metastasis (M) elements and then group them into stages differs from other cancer staging classifications (e.g., Dukes), which are only concerned with summarized groups. The objectives of the TNM Classification are to aid the clinician in the planning of treatment, give some indication of prognosis, assist in the evaluation of the results of treatment, and facilitate the exchange of information. During the past 50 years, the TNM system has evolved under the influence of advances in diagnosis and treatment. Radiographic imaging (e.g., endoscopic ultrasound for the depth of invasion of esophageal and rectal tumors) has improved the accuracy of the clinical T, N, and M classifications. Advances in treatment have necessitated more detail in some T4 categories. Developments in multimodality therapy have increased the importance of the "y" symbol and the R (residual tumor) classification. New surgical techniques have resulted in the elaboration of the sentinel node (sn) symbol. The use of immunohistochemistry has resulted in the classification of isolated tumor cells and their distinction from micrometastasis. The most important challenge facing users of the TNM Classification is how it should interface with the large number of non-anatomic prognostic factors that are currently in use or under study. As non-anatomic prognostic factors become widely used, the TNM system provides an inviting foundation upon which to build a prognostic classification; however, this carries a risk that the system will be overwhelmed by a variety of prognostic data. An anatomic extent-of-disease classification is needed to aid practitioners in selecting the initial therapeutic approach, stratifying patients for therapeutic studies, evaluating non-anatomic prognostic factors at specific anatomic stages, comparing the weight of non-anatomic factors with extent of disease, and communicating the extent of disease data in a uniform manner. Methods are needed to express the overall prognosis without losing the vital anatomic content of TNM. These methods should be able to integrate multiple prognostic factors, including TNM, while permitting the TNM system to remain intact and distinct. This article discusses examples of such approaches.

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.

Detection of inter-patient left and right bundle branch block heartbeats in ECG using ensemble classifiers

PubMed Central

2014-01-01

Background Left bundle branch block (LBBB) and right bundle branch block (RBBB) not only mask electrocardiogram (ECG) changes that reflect diseases but also indicate important underlying pathology. The timely detection of LBBB and RBBB is critical in the treatment of cardiac diseases. Inter-patient heartbeat classification is based on independent training and testing sets to construct and evaluate a heartbeat classification system. Therefore, a heartbeat classification system with a high performance evaluation possesses a strong predictive capability for unknown data. The aim of this study was to propose a method for inter-patient classification of heartbeats to accurately detect LBBB and RBBB from the normal beat (NORM). Methods This study proposed a heartbeat classification method through a combination of three different types of classifiers: a minimum distance classifier constructed between NORM and LBBB; a weighted linear discriminant classifier between NORM and RBBB based on Bayesian decision making using posterior probabilities; and a linear support vector machine (SVM) between LBBB and RBBB. Each classifier was used with matching features to obtain better classification performance. The final types of the test heartbeats were determined using a majority voting strategy through the combination of class labels from the three classifiers. The optimal parameters for the classifiers were selected using cross-validation on the training set. The effects of different lead configurations on the classification results were assessed, and the performance of these three classifiers was compared for the detection of each pair of heartbeat types. Results The study results showed that a two-lead configuration exhibited better classification results compared with a single-lead configuration. The construction of a classifier with good performance between each pair of heartbeat types significantly improved the heartbeat classification performance. The results showed a sensitivity of 91.4% and a positive predictive value of 37.3% for LBBB and a sensitivity of 92.8% and a positive predictive value of 88.8% for RBBB. Conclusions A multi-classifier ensemble method was proposed based on inter-patient data and demonstrated a satisfactory classification performance. This approach has the potential for application in clinical practice to distinguish LBBB and RBBB from NORM of unknown patients. PMID:24903422

Detection of inter-patient left and right bundle branch block heartbeats in ECG using ensemble classifiers.

PubMed

Huang, Huifang; Liu, Jie; Zhu, Qiang; Wang, Ruiping; Hu, Guangshu

2014-06-05

Left bundle branch block (LBBB) and right bundle branch block (RBBB) not only mask electrocardiogram (ECG) changes that reflect diseases but also indicate important underlying pathology. The timely detection of LBBB and RBBB is critical in the treatment of cardiac diseases. Inter-patient heartbeat classification is based on independent training and testing sets to construct and evaluate a heartbeat classification system. Therefore, a heartbeat classification system with a high performance evaluation possesses a strong predictive capability for unknown data. The aim of this study was to propose a method for inter-patient classification of heartbeats to accurately detect LBBB and RBBB from the normal beat (NORM). This study proposed a heartbeat classification method through a combination of three different types of classifiers: a minimum distance classifier constructed between NORM and LBBB; a weighted linear discriminant classifier between NORM and RBBB based on Bayesian decision making using posterior probabilities; and a linear support vector machine (SVM) between LBBB and RBBB. Each classifier was used with matching features to obtain better classification performance. The final types of the test heartbeats were determined using a majority voting strategy through the combination of class labels from the three classifiers. The optimal parameters for the classifiers were selected using cross-validation on the training set. The effects of different lead configurations on the classification results were assessed, and the performance of these three classifiers was compared for the detection of each pair of heartbeat types. The study results showed that a two-lead configuration exhibited better classification results compared with a single-lead configuration. The construction of a classifier with good performance between each pair of heartbeat types significantly improved the heartbeat classification performance. The results showed a sensitivity of 91.4% and a positive predictive value of 37.3% for LBBB and a sensitivity of 92.8% and a positive predictive value of 88.8% for RBBB. A multi-classifier ensemble method was proposed based on inter-patient data and demonstrated a satisfactory classification performance. This approach has the potential for application in clinical practice to distinguish LBBB and RBBB from NORM of unknown patients.

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.

Acute pancreatitis.

PubMed

Talukdar, Rupjyoti; Vege, Santhi S

2015-09-01

To summarize recent data on classification systems, cause, risk factors, severity prediction, nutrition, and drug treatment of acute pancreatitis. Comparison of the Revised Atlanta Classification and Determinant Based Classification has shown heterogeneous results. Simvastatin has a protective effect against acute pancreatitis. Young black male, alcohol, smoldering symptoms, and subsequent diagnosis of chronic pancreatitis are risk factors associated with readmissions after acute pancreatitis. A reliable clinical or laboratory marker or a scoring system to predict severity is lacking. The PYTHON trial has shown that oral feeding with on demand nasoenteric tube feeding after 72 h is as good as nasoenteric tube feeding within 24 h in preventing infections in predicted severe acute pancreatitis. Male sex, multiple organ failure, extent of pancreatic necrosis, and heterogeneous collection are factors associated with failure of percutaneous drainage of pancreatic collections. The newly proposed classification systems of acute pancreatitis need to be evaluated more critically. New biomarkers are needed for severity prediction. Further well designed studies are required to assess the type of enteral nutritional formulations for acute pancreatitis. The optimal minimally invasive method or combination to debride the necrotic collections is evolving. There is a great need for a drug to treat the disease early on to prevent morbidity and mortality.

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.

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.

Patient inducement, provider priorities, and resource allocation in public mental health systems.

PubMed

Sinaiko, Anna D; McGuire, Thomas G

2006-12-01

Public mental health systems are increasingly facing demands from the criminal justice system and social services agencies to provide services and support in cases in which mental illness contributes to crime, homelessness, or poverty. In this article we analyze how policies from outside public mental health systems affect resource allocation within these systems, using examples from criminal justice. These policies use two types of mechanisms: inducing patients to consume treatment (by offering rewards or imposing penalties) and inducing clinicians to provide treatment (by creating priorities). We propose a classification of these social policies based on whether they affect demand through rewards or penalties or supply through priorities. We then relate the classification to data on patients treated in public systems to evaluate the current prevalence and potential for growth in these outside demands. These inducements impose a set of nonobvious costs on other patients who are not targeted by the policies. Furthermore, they create incentives for both patients and providers to modify their behavior in order to take advantage of rewards, avoid penalties, or better compete for resources with prioritized patients. We consider some policy implications for avoiding unintended consequences of these policies.

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

Agreement between TOAST and CCS ischemic stroke classification: the NINDS SiGN study.

PubMed

McArdle, Patrick F; Kittner, Steven J; Ay, Hakan; Brown, Robert D; Meschia, James F; Rundek, Tatjana; Wassertheil-Smoller, Sylvia; Woo, Daniel; Andsberg, Gunnar; Biffi, Alessandro; Brenner, David A; Cole, John W; Corriveau, Roderick; de Bakker, Paul I W; Delavaran, Hossein; Dichgans, Martin; Grewal, Raji P; Gwinn, Katrina; Huq, Mohammed; Jern, Christina; Jimenez-Conde, Jordi; Jood, Katarina; Kaplan, Robert C; Katschnig, Petra; Katsnelson, Michael; Labovitz, Daniel L; Lemmens, Robin; Li, Linxin; Lindgren, Arne; Markus, Hugh S; Peddareddygari, Leema R; Pedersén, Annie; Pera, Joanna; Redfors, Petra; Roquer, Jaume; Rosand, Jonathan; Rost, Natalia S; Rothwell, Peter M; Sacco, Ralph L; Sharma, Pankaj; Slowik, Agnieszka; Sudlow, Cathie; Thijs, Vincent; Tiedt, Steffen; Valenti, Raffaella; Worrall, Bradford B

2014-10-28

The objective of this study was to assess the level of agreement between stroke subtype classifications made using the Trial of Org 10172 Acute Stroke Treatment (TOAST) and Causative Classification of Stroke (CCS) systems. Study subjects included 13,596 adult men and women accrued from 20 US and European genetic research centers participating in the National Institute of Neurological Disorders and Stroke (NINDS) Stroke Genetics Network (SiGN). All cases had independently classified TOAST and CCS stroke subtypes. Kappa statistics were calculated for the 5 major ischemic stroke subtypes common to both systems. The overall agreement between TOAST and CCS was moderate (agreement rate, 70%; κ = 0.59, 95% confidence interval [CI] 0.58-0.60). Agreement varied widely across study sites, ranging from 28% to 90%. Agreement on specific subtypes was highest for large-artery atherosclerosis (κ = 0.71, 95% CI 0.69-0.73) and lowest for small-artery occlusion (κ = 0.56, 95% CI 0.54-0.58). Agreement between TOAST and CCS diagnoses was moderate. Caution is warranted when comparing or combining results based on the 2 systems. Replication of study results, for example, genome-wide association studies, should utilize phenotypes determined by the same classification system, ideally applied in the same manner. © 2014 American Academy of Neurology.

A practicable approach for periodontal classification

PubMed Central

Mittal, Vishnu; Bhullar, Raman Preet K.; Bansal, Rachita; Singh, Karanprakash; Bhalodi, Anand; Khinda, Paramjit K.

2013-01-01

The Diagnosis and classification of periodontal diseases has remained a dilemma since long. Two distinct concepts have been used to define diseases: Essentialism and Nominalism. Essentialistic concept implies the real existence of disease whereas; nominalistic concept states that the names of diseases are the convenient way of stating concisely the endpoint of a diagnostic process. It generally advances from assessment of symptoms and signs toward knowledge of causation and gives a feasible option to name the disease for which etiology is either unknown or it is too complex to access in routine clinical practice. Various classifications have been proposed by the American Academy of Periodontology (AAP) in 1986, 1989 and 1999. The AAP 1999 classification is among the most widely used classification. But this classification also has demerits which provide impediment for its use in day to day practice. Hence a classification and diagnostic system is required which can help the clinician to access the patient's need and provide a suitable treatment which is in harmony with the diagnosis for that particular case. Here is an attempt to propose a practicable classification and diagnostic system of periodontal diseases for better treatment outcome. PMID:24379855

The International Neuroblastoma Risk Group (INRG) staging system: an INRG Task Force report.

PubMed

Monclair, Tom; Brodeur, Garrett M; Ambros, Peter F; Brisse, Hervé J; Cecchetto, Giovanni; Holmes, Keith; Kaneko, Michio; London, Wendy B; Matthay, Katherine K; Nuchtern, Jed G; von Schweinitz, Dietrich; Simon, Thorsten; Cohn, Susan L; Pearson, Andrew D J

2009-01-10

The International Neuroblastoma Risk Group (INRG) classification system was developed to establish a consensus approach for pretreatment risk stratification. Because the International Neuroblastoma Staging System (INSS) is a postsurgical staging system, a new clinical staging system was required for the INRG pretreatment risk classification system. To stage patients before any treatment, the INRG Task Force, consisting of neuroblastoma experts from Australia/New Zealand, China, Europe, Japan, and North America, developed a new INRG staging system (INRGSS) based on clinical criteria and image-defined risk factors (IDRFs). To investigate the impact of IDRFs on outcome, survival analyses were performed on 661 European patients with INSS stages 1, 2, or 3 disease for whom IDRFs were known. In the INGRSS, locoregional tumors are staged L1 or L2 based on the absence or presence of one or more of 20 IDRFs, respectively. Metastatic tumors are defined as stage M, except for stage MS, in which metastases are confined to the skin, liver, and/or bone marrow in children younger than 18 months of age. Within the 661-patient cohort, IDRFs were present (ie, stage L2) in 21% of patients with stage 1, 45% of patients with stage 2, and 94% of patients with stage 3 disease. Patients with INRGSS stage L2 disease had significantly lower 5-year event-free survival than those with INRGSS stage L1 disease (78% +/- 4% v 90% +/- 3%; P = .0010). Use of the new staging (INRGSS) and risk classification (INRG) of neuroblastoma will greatly facilitate the comparison of risk-based clinical trials conducted in different regions of the world.

The Influence of Tactile Perception on Classification of Bone Tissue at Dental Implant Insertion.

PubMed

Linck, Gláucia Kelly Silva Barbosa; Ferreira, Geovane Miranda; De Oliveira, Rubelisa Cândido Gomes; Lindh, Christina; Leles, Cláudio Rodrigues; Ribeiro-Rotta, Rejane Faria

2016-06-01

Various ways of using the Lekholm and Zarb (L&Z) classification have added to the lack of scientific evidence of the effectiveness of this clinical method in the evaluation of implant treatment. The study aims to assess subjective jawbone classifications in patients referred for implant treatment, using L&Z classification with and without surgeon's hand perception at implant insertion. The association between bone type classifications and quantitative parameters of primary implant stability was also assessed. One hundred thirty-five implants were inserted using conventional loading protocol. Three surgeons classified bone quality at implant sites using two methods: one based on periapical and panoramic images (modified L&Z) and one based on the same images associated with the surgeon's tactile perception during drilling (original L&Z). Peak insertion torque and implant stability quotient (ISQ) were recorded. The modified and original L&Z were strongly correlated (rho = 0.79; p < .001); Wilcoxon signed-rank test showed no significant difference in the distribution of bone type classification between pairs using the two methods (p = .538). Spearman correlation tested the association between primary stability parameters and bone type classifications (-0.34 to -0.57 [p < .001]). Tactile surgical perception has a minor influence on rating of subjective bone type for dental implant treatment using the L&Z classification. © 2015 Wiley Periodicals, Inc.

C-learning: A new classification framework to estimate optimal dynamic treatment regimes.

PubMed

Zhang, Baqun; Zhang, Min

2017-12-11

A dynamic treatment regime is a sequence of decision rules, each corresponding to a decision point, that determine that next treatment based on each individual's own available characteristics and treatment history up to that point. We show that identifying the optimal dynamic treatment regime can be recast as a sequential optimization problem and propose a direct sequential optimization method to estimate the optimal treatment regimes. In particular, at each decision point, the optimization is equivalent to sequentially minimizing a weighted expected misclassification error. Based on this classification perspective, we propose a powerful and flexible C-learning algorithm to learn the optimal dynamic treatment regimes backward sequentially from the last stage until the first stage. C-learning is a direct optimization method that directly targets optimizing decision rules by exploiting powerful optimization/classification techniques and it allows incorporation of patient's characteristics and treatment history to improve performance, hence enjoying advantages of both the traditional outcome regression-based methods (Q- and A-learning) and the more recent direct optimization methods. The superior performance and flexibility of the proposed methods are illustrated through extensive simulation studies. © 2017, The International Biometric Society.

Patient casemix classification for medicare psychiatric prospective payment.

PubMed

Drozd, Edward M; Cromwell, Jerry; Gage, Barbara; Maier, Jan; Greenwald, Leslie M; Goldman, Howard H

2006-04-01

For a proposed Medicare prospective payment system for inpatient psychiatric facility treatment, the authors developed a casemix classification to capture differences in patients' real daily resource use. Primary data on patient characteristics and daily time spent in various activities were collected in a survey of 696 patients from 40 inpatient psychiatric facilities. Survey data were combined with Medicare claims data to estimate intensity-adjusted daily cost. Classification and Regression Trees (CART) analysis of average daily routine and ancillary costs yielded several hierarchical classification groupings. Regression analysis was used to control for facility and day-of-stay effects in order to compare hierarchical models with models based on the recently proposed payment system of the Centers for Medicare & Medicaid Services. CART analysis identified a small set of patient characteristics strongly associated with higher daily costs, including age, psychiatric diagnosis, deficits in daily living activities, and detox or ECT use. A parsimonious, 16-group, fully interactive model that used five major DSM-IV categories and stratified by age, illness severity, deficits in daily living activities, dangerousness, and use of ECT explained 40% (out of a possible 76%) of daily cost variation not attributable to idiosyncratic daily changes within patients. A noninteractive model based on diagnosis-related groups, age, and medical comorbidity had explanatory power of only 32%. A regression model with 16 casemix groups restricted to using "appropriate" payment variables (i.e., those with clinical face validity and low administrative burden that are easily validated and provide proper care incentives) produced more efficient and equitable payments than did a noninteractive system based on diagnosis-related groups.

Application of Random Forests Methods to Diabetic Retinopathy Classification Analyses

PubMed Central

Casanova, Ramon; Saldana, Santiago; Chew, Emily Y.; Danis, Ronald P.; Greven, Craig M.; Ambrosius, Walter T.

2014-01-01

Background Diabetic retinopathy (DR) is one of the leading causes of blindness in the United States and world-wide. DR is a silent disease that may go unnoticed until it is too late for effective treatment. Therefore, early detection could improve the chances of therapeutic interventions that would alleviate its effects. Methodology Graded fundus photography and systemic data from 3443 ACCORD-Eye Study participants were used to estimate Random Forest (RF) and logistic regression classifiers. We studied the impact of sample size on classifier performance and the possibility of using RF generated class conditional probabilities as metrics describing DR risk. RF measures of variable importance are used to detect factors that affect classification performance. Principal Findings Both types of data were informative when discriminating participants with or without DR. RF based models produced much higher classification accuracy than those based on logistic regression. Combining both types of data did not increase accuracy but did increase statistical discrimination of healthy participants who subsequently did or did not have DR events during four years of follow-up. RF variable importance criteria revealed that microaneurysms counts in both eyes seemed to play the most important role in discrimination among the graded fundus variables, while the number of medicines and diabetes duration were the most relevant among the systemic variables. Conclusions and Significance We have introduced RF methods to DR classification analyses based on fundus photography data. In addition, we propose an approach to DR risk assessment based on metrics derived from graded fundus photography and systemic data. Our results suggest that RF methods could be a valuable tool to diagnose DR diagnosis and evaluate its progression. PMID:24940623

Creating a Canonical Scientific and Technical Information Classification System for NCSTRL+

NASA Technical Reports Server (NTRS)

Tiffany, Melissa E.; Nelson, Michael L.

1998-01-01

The purpose of this paper is to describe the new subject classification system for the NCSTRL+ project. NCSTRL+ is a canonical digital library (DL) based on the Networked Computer Science Technical Report Library (NCSTRL). The current NCSTRL+ classification system uses the NASA Scientific and Technical (STI) subject classifications, which has a bias towards the aerospace, aeronautics, and engineering disciplines. Examination of other scientific and technical information classification systems showed similar discipline-centric weaknesses. Traditional, library-oriented classification systems represented all disciplines, but were too generalized to serve the needs of a scientific and technically oriented digital library. Lack of a suitable existing classification system led to the creation of a lightweight, balanced, general classification system that allows the mapping of more specialized classification schemes into the new framework. We have developed the following classification system to give equal weight to all STI disciplines, while being compact and lightweight.

Treatment based on the type of infected TKA improves infection control.

PubMed

Kim, Young-Hoo; Choi, Yoowang; Kim, Jun-Shik

2011-04-01

A classification system with four types of infected TKAs has been commonly used to determine treatment, especially with regard to whether the prosthesis should be removed or retained. We asked whether (1) the classification-dictated treatment of the four types of infection after TKA would control infection and maintain functional TKA; (2) repeated débridement and two-stage TKA would further improve the infection control rate after initial treatment; and (3) fixation of TKA prosthesis to the host bone was achieved. We retrospectively reviewed 114 patients with 116 infected TKAs. We determined the infection control rate after initial treatment, repeated débridement and two-stage TKA. We evaluated the functional and radiographic results using the Knee Society and Hospital for Special Surgery knee scoring systems. The minimum followup was 2 years (mean, 5.6 years; range, 2-8 years). The overall infection control rate was 100% in all patients. All patients with early superficial postoperative infection, 94% of patients with early deep postoperative infection, 96% of patients with late chronic infection, and 86% of patients with acute hematogenous infection maintained functioning knee prosthesis at the final followup. One hundred nine of the 114 patients could walk with no or only slight pain and maintained functioning knee prostheses. These 109 patients had stable fixation of the TKA prosthesis to host bone. The techniques proposed by the classification effectively controlled infection and maintained functional TKA with firm fixation of the TKA prosthesis in most patients. Repeated débridement and two-stage TKA further improved the control of infection and functional TKA after initial treatment. Level IV, therapeutic study. See the Guidelines for Authors for a complete description of levels of evidence.

Ensemble of random forests One vs. Rest classifiers for MCI and AD prediction using ANOVA cortical and subcortical feature selection and partial least squares.

PubMed

Ramírez, J; Górriz, J M; Ortiz, A; Martínez-Murcia, F J; Segovia, F; Salas-Gonzalez, D; Castillo-Barnes, D; Illán, I A; Puntonet, C G

2018-05-15

Alzheimer's disease (AD) is the most common cause of dementia in the elderly and affects approximately 30 million individuals worldwide. Mild cognitive impairment (MCI) is very frequently a prodromal phase of AD, and existing studies have suggested that people with MCI tend to progress to AD at a rate of about 10-15% per year. However, the ability of clinicians and machine learning systems to predict AD based on MRI biomarkers at an early stage is still a challenging problem that can have a great impact in improving treatments. The proposed system, developed by the SiPBA-UGR team for this challenge, is based on feature standardization, ANOVA feature selection, partial least squares feature dimension reduction and an ensemble of One vs. Rest random forest classifiers. With the aim of improving its performance when discriminating healthy controls (HC) from MCI, a second binary classification level was introduced that reconsiders the HC and MCI predictions of the first level. The system was trained and evaluated on an ADNI datasets that consist of T1-weighted MRI morphological measurements from HC, stable MCI, converter MCI and AD subjects. The proposed system yields a 56.25% classification score on the test subset which consists of 160 real subjects. The classifier yielded the best performance when compared to: (i) One vs. One (OvO), One vs. Rest (OvR) and error correcting output codes (ECOC) as strategies for reducing the multiclass classification task to multiple binary classification problems, (ii) support vector machines, gradient boosting classifier and random forest as base binary classifiers, and (iii) bagging ensemble learning. A robust method has been proposed for the international challenge on MCI prediction based on MRI data. The system yielded the second best performance during the competition with an accuracy rate of 56.25% when evaluated on the real subjects of the test set. Copyright © 2017 Elsevier B.V. All rights reserved.

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...

A Hybrid Classification System for Heart Disease Diagnosis Based on the RFRS Method.

PubMed

Liu, Xiao; Wang, Xiaoli; Su, Qiang; Zhang, Mo; Zhu, Yanhong; Wang, Qiugen; Wang, Qian

2017-01-01

Heart disease is one of the most common diseases in the world. The objective of this study is to aid the diagnosis of heart disease using a hybrid classification system based on the ReliefF and Rough Set (RFRS) method. The proposed system contains two subsystems: the RFRS feature selection system and a classification system with an ensemble classifier. The first system includes three stages: (i) data discretization, (ii) feature extraction using the ReliefF algorithm, and (iii) feature reduction using the heuristic Rough Set reduction algorithm that we developed. In the second system, an ensemble classifier is proposed based on the C4.5 classifier. The Statlog (Heart) dataset, obtained from the UCI database, was used for experiments. A maximum classification accuracy of 92.59% was achieved according to a jackknife cross-validation scheme. The results demonstrate that the performance of the proposed system is superior to the performances of previously reported classification techniques.

Systemic Treatment Patterns With Advanced or Recurrent Non-small Cell Lung Cancer in Japan: A Retrospective Hospital Administrative Database Study.

PubMed

Wang, Feng; Mishina, Sari; Takai, Shinji; Le, T Kim; Ochi, Kenya; Funato, Kotaro; Matsuoka, Shozo; Ohe, Yuichiro

2017-06-01

Data on the treatment of non-small cell lung cancer (NSCLC) in real-world clinical practice in Japan are limited. This large-scale, retrospective cohort study examined data on patients' characteristics and systemic therapies for advanced or recurrent NSCLC in routine practice in Japan. This study used an electronic health records-based database of health claims and Diagnosis Procedure Combination data from 215 consenting hospitals in Japan. Records from April 2008 to September 2015 were analyzed. Regimens were examined by histology, age, sex, and therapeutic line. Logistic regression analysis was performed to predict which clinical and demographic factors affected patients' probability of receiving first- or second-line therapy or completing first-line platinum-based chemotherapy. Among 16,413 patients, 67.9%, 39.2%, and 22.3% received first-, second-, and third-line systemic treatment, respectively. Treatment was more common in patients aged <75 versus ≥75 years (76.0% vs 51.6%), in female versus male patients (71.6% vs 65.4%), and in patients with nonsquamous versus squamous disease (75.6% vs 61.9%). More than 30 systemic regimens were administered. The most common first-line therapy was platinum-based chemotherapy (nonsquamous, 53.6%; squamous, 73.7%). Non-platinum-based chemotherapy use increased in the second-line setting, but platinum-based chemotherapy use remained high (nonsquamous, 33.9%; squamous, 38.6%). Tyrosine kinase inhibitors were used in 32.0% and 29.4% of patients with nonsquamous NSCLC in the first- and second-line settings, respectively. Switches from first- to second-line platinum-based chemotherapy and from first- to second-line tyrosine kinase inhibitors occurred. Forty-two percent of the patients died during hospitalization. In the logistic regression analysis, factors associated with a decreased likelihood of receiving first-line therapy were male sex, squamous histology, age >75 years, treatment at a general (vs cancer-specific) hospital, worse scores on certain activities of daily living, presence of chronic pulmonary disease, worse Hugh-Jones classification, and positive smoking status. The likelihood of completing first-line platinum-based chemotherapy was increased with greater body mass index, better activities of daily living scores, absence of chronic pulmonary disease, and better Hugh-Jones classification. The likelihood of continuing with second-line therapy was decreased with older age and recurrence of NSCLC. Systemic treatment patterns for advanced or recurrent NSCLC in Japan were varied. Nearly 30% of all patients and approximately half of elderly patients did not receive systemic treatment. Treatment rates declined with subsequent therapeutic lines. Generally, guidelines were followed with first-line treatment administration, but not with second-line administration. These results underscore the need for better guideline adherence and more optimal treatment in and elderly patients and in those receiving later-line treatment in Japan. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Genetic burden associated with varying degrees of disease severity in endometriosis

PubMed Central

Sapkota, Yadav; Attia, John; Gordon, Scott D.; Henders, Anjali K.; Holliday, Elizabeth G.; Rahmioglu, Nilufer; MacGregor, Stuart; Martin, Nicholas G.; McEvoy, Mark; Morris, Andrew P.; Scott, Rodney J.; Zondervan, Krina T.; Montgomery, Grant W.; Nyholt, Dale R.

2015-01-01

Endometriosis is primarily characterized by the presence of tissue resembling endometrium outside the uterine cavity and is usually diagnosed by laparoscopy. The most commonly used classification of disease, the revised American Fertility Society (rAFS) system to grade endometriosis into different stages based on disease severity (I to IV), has been questioned as it does not correlate well with underlying symptoms, posing issues in diagnosis and choice of treatment. Using two independent European genome-wide association (GWA) datasets and top-level classification of the endometriosis cases based on rAFS [minimal or mild (Stage A) and moderate-to-severe (Stage B) disease], we previously showed that Stage B endometriosis has greater contribution of common genetic variation to its aetiology than Stage A disease. Herein, we extend our previous analysis to four endometriosis stages [minimal (Stage I), mild (Stage II), moderate (Stage III) and severe (Stage IV) disease] based on the rAFS classification system and compared the genetic burden across stages. Our results indicate that genetic burden increases from minimal to severe endometriosis. For the minimal disease, genetic factors may contribute to a lesser extent than other disease categories. Mild and moderate endometriosis appeared genetically similar, making it difficult to tease them apart. Consistent with our previous reports, moderate and severe endometriosis showed greater genetic burden than minimal or mild disease. Overall, our results provide new insights into the genetic architecture of endometriosis and further investigation in larger samples may help to understand better the aetiology of varying degrees of endometriosis, enabling improved diagnostic and treatment modalities. PMID:25882541

The ESHRE/ESGE consensus on the classification of female genital tract congenital anomalies†,‡

PubMed Central

Grimbizis, Grigoris F.; Gordts, Stephan; Di Spiezio Sardo, Attilio; Brucker, Sara; De Angelis, Carlo; Gergolet, Marco; Li, Tin-Chiu; Tanos, Vasilios; Brölmann, Hans; Gianaroli, Luca; Campo, Rudi

2013-01-01

STUDY QUESTION What classification system is more suitable for the accurate, clear, simple and related to the clinical management categorization of female genital anomalies? SUMMARY ANSWER The new ESHRE/ESGE classification system of female genital anomalies is presented. WHAT IS KNOWN ALREADY Congenital malformations of the female genital tract are common miscellaneous deviations from normal anatomy with health and reproductive consequences. Until now, three systems have been proposed for their categorization but all of them are associated with serious limitations. STUDY DESIGN, SIZE AND DURATION The European Society of Human Reproduction and Embryology (ESHRE) and the European Society for Gynaecological Endoscopy (ESGE) have established a common Working Group, under the name CONUTA (CONgenital UTerine Anomalies), with the goal of developing a new updated classification system. A scientific committee (SC) has been appointed to run the project, looking also for consensus within the scientists working in the field. PARTICIPANTS/MATERIALS, SETTING, METHODS The new system is designed and developed based on (i) scientific research through critical review of current proposals and preparation of an initial proposal for discussion between the experts, (ii) consensus measurement among the experts through the use of the DELPHI procedure and (iii) consensus development by the SC, taking into account the results of the DELPHI procedure and the comments of the experts. Almost 90 participants took part in the process of development of the ESHRE/ESGE classification system, contributing with their structured answers and comments. MAIN RESULTS AND THE ROLE OF CHANCE The ESHRE/ESGE classification system is based on anatomy. Anomalies are classified into the following main classes, expressing uterine anatomical deviations deriving from the same embryological origin: U0, normal uterus; U1, dysmorphic uterus; U2, septate uterus; U3, bicorporeal uterus; U4, hemi-uterus; U5, aplastic uterus; U6, for still unclassified cases. Main classes have been divided into sub-classes expressing anatomical varieties with clinical significance. Cervical and vaginal anomalies are classified independently into sub-classes having clinical significance. LIMITATIONS, REASONS FOR CAUTION The ESHRE/ESGE classification of female genital anomalies seems to fulfill the expectations and the needs of the experts in the field, but its clinical value needs to be proved in everyday practice. WIDER IMPLICATIONS OF THE FINDINGS The ESHRE/ESGE classification system of female genital anomalies could be used as a starting point for the development of guidelines for their diagnosis and treatment. STUDY FUNDING/COMPETING INTEREST(S) None. PMID:23771171

42 CFR 412.620 - Patient classification system.

Code of Federal Regulations, 2013 CFR

2013-10-01

... weighting factors to reflect changes in— (1) Treatment patterns; (2) Technology; (3) Number of discharges... 42 Public Health 2 2013-10-01 2013-10-01 false Patient classification system. 412.620 Section 412... rehabilitation facilities into mutually exclusive case-mix groups. (2) For purposes of this subpart, case-mix...

42 CFR 412.620 - Patient classification system.

Code of Federal Regulations, 2012 CFR

2012-10-01

... weighting factors to reflect changes in— (1) Treatment patterns; (2) Technology; (3) Number of discharges... 42 Public Health 2 2012-10-01 2012-10-01 false Patient classification system. 412.620 Section 412... rehabilitation facilities into mutually exclusive case-mix groups. (2) For purposes of this subpart, case-mix...

42 CFR 412.620 - Patient classification system.

Code of Federal Regulations, 2014 CFR

2014-10-01

... weighting factors to reflect changes in— (1) Treatment patterns; (2) Technology; (3) Number of discharges... 42 Public Health 2 2014-10-01 2014-10-01 false Patient classification system. 412.620 Section 412... rehabilitation facilities into mutually exclusive case-mix groups. (2) For purposes of this subpart, case-mix...

A model-based test for treatment effects with probabilistic classifications.

PubMed

Cavagnaro, Daniel R; Davis-Stober, Clintin P

2018-05-21

Within modern psychology, computational and statistical models play an important role in describing a wide variety of human behavior. Model selection analyses are typically used to classify individuals according to the model(s) that best describe their behavior. These classifications are inherently probabilistic, which presents challenges for performing group-level analyses, such as quantifying the effect of an experimental manipulation. We answer this challenge by presenting a method for quantifying treatment effects in terms of distributional changes in model-based (i.e., probabilistic) classifications across treatment conditions. The method uses hierarchical Bayesian mixture modeling to incorporate classification uncertainty at the individual level into the test for a treatment effect at the group level. We illustrate the method with several worked examples, including a reanalysis of the data from Kellen, Mata, and Davis-Stober (2017), and analyze its performance more generally through simulation studies. Our simulations show that the method is both more powerful and less prone to type-1 errors than Fisher's exact test when classifications are uncertain. In the special case where classifications are deterministic, we find a near-perfect power-law relationship between the Bayes factor, derived from our method, and the p value obtained from Fisher's exact test. We provide code in an online supplement that allows researchers to apply the method to their own data. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

A new set of wavelet- and fractals-based features for Gleason grading of prostate cancer histopathology images

NASA Astrophysics Data System (ADS)

Mosquera Lopez, Clara; Agaian, Sos

2013-02-01

Prostate cancer detection and staging is an important step towards patient treatment selection. Advancements in digital pathology allow the application of new quantitative image analysis algorithms for computer-assisted diagnosis (CAD) on digitized histopathology images. In this paper, we introduce a new set of features to automatically grade pathological images using the well-known Gleason grading system. The goal of this study is to classify biopsy images belonging to Gleason patterns 3, 4, and 5 by using a combination of wavelet and fractal features. For image classification we use pairwise coupling Support Vector Machine (SVM) classifiers. The accuracy of the system, which is close to 97%, is estimated through three different cross-validation schemes. The proposed system offers the potential for automating classification of histological images and supporting prostate cancer diagnosis.

Classifying diseases and remedies in ethnomedicine and ethnopharmacology.

PubMed

Staub, Peter O; Geck, Matthias S; Weckerle, Caroline S; Casu, Laura; Leonti, Marco

2015-11-04

Ethnopharmacology focuses on the understanding of local and indigenous use of medicines and therefore an emic approach is inevitable. Often, however, standard biomedical disease classifications are used to describe and analyse local diseases and remedies. Standard classifications might be a valid tool for cross-cultural comparisons and bioprospecting purposes but are not suitable to understand the local perception of disease and use of remedies. Different standard disease classification systems exist but their suitability for cross-cultural comparisons of ethnomedical data has never been assessed. Depending on the research focus, (I) ethnomedical, (II) cross-cultural, and (III) bioprospecting, we provide suggestions for the use of specific classification systems. We analyse three different standard biomedical classification systems (the International Classification of Diseases (ICD); the Economic Botany Data Collection Standard (EBDCS); and the International Classification of Primary Care (ICPC)), and discuss their value for categorizing diseases of ethnomedical systems and their suitability for cross-cultural research in ethnopharmacology. Moreover, based on the biomedical uses of all approved plant derived biomedical drugs, we propose a biomedical therapy-based classification system as a guide for the discovery of drugs from ethnopharmacological sources. Widely used standards, such as the International Classification of Diseases (ICD) by the WHO and the Economic Botany Data Collection Standard (EBDCS) are either technically challenging due to a categorisation system based on clinical examinations, which are usually not possible during field research (ICD) or lack clear biomedical criteria combining disorders and medical effects in an imprecise and confusing way (EBDCS). The International Classification of Primary Care (ICPC), also accepted by the WHO, has more in common with ethnomedical reality than the ICD or the EBDCS, as the categories are designed according to patient's perceptions and are less influenced by clinical medicine. Since diagnostic tools are not required, medical ethnobotanists and ethnopharmacologists can easily classify reported symptoms and complaints with the ICPC in one of the "chapters" based on 17 body systems, psychological and social problems. Also the biomedical uses of plant-derived drugs are classifiable into 17 broad organ- and therapy-based use-categories but can easily be divided into more specific subcategories. Depending on the research focus (I-III) we propose the following classification systems: I. Ethnomedicine: Ethnomedicine is culture-bound and local classifications have to be understood from an emic perspective. Consequently, the application of prefabricated, "one-size fits all" biomedical classification schemes is of limited value. II. Cross-cultural analysis: The ICPC is a suitable standard that can be applied but modified as required. III. Bioprospecting: We suggest a biomedical therapy-driven classification system with currently 17 use-categories based on biomedical uses of all approved plant derived natural product drugs. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Classification for congenital anomalies of the hand: the IFSSH classification and the JSSH modification.

PubMed

De Smet, L

2002-01-01

The purpose of a classification for clinical problems which, except for a few specialized centers, occur only sporadically is to provide a system where these cases can be stored. This should allow all involved investigators to speak the same language; so-doing syndromes can be delinated, frequencies of occurence established and results of--different--treatments compared. A classification system should be simple to use, reliable and uniformly accepted. It should allow space for adaptations and/or extensions. The IFSSH proposed a 7 categories classification based on the proposed classification of Swanson et al. in 1976. This classification, was based on, which was thought in the seventies, etiopathogenic pathways. These 7 groups are: I. Failure of formation; transverse (A), or longitudinal (B) II. Failure of differentiation III. Polydactyly IV. Overgrowth V. Undergrowth VI. Amniotic band syndrome VII. Generalized skeletal syndromes. The extended classification proposed by IFSSH was used to classify 1013 hand differences in 925 hands of 650 patients. We found associated anomalies in 26.7%. The classification was straightforward in 86%, difficult in 6.6% and not possible in 7.8%. Group II was the most numerous group including 513 anomalies. We propose to include in this group the Madelung deformity, the Kirner deformity and congenital trigger fingers and trigger thumbs. In group I the radial and ulnar deficiencies, limited to the hand without forearm deficlencies should be Included. Triphalangeal thumbs are a problem, we suggest it to be listed in group III and consider it as a duplication in length. It is not always possible to evaluate the (transverse) absence of the fingers or hand. Longitudinal deficiencies (group IIB), symbrachydactyly (group V), and amniotic bands (group IV) occasionally develop a phenotype similar to the genuine transverse deficiency (group IA). Recently, the Japanese Society for Surgery of the Hand (JSSH) (16) proposed an extension/modification of the IFSSH classification. Based on newer knowledge on teratology, symbrachydactyly in all stages were transfered to group I. Two new groups were introduced. A group "failure of finger ray induction" including typical cleft hand (IC), central polydactyly (III) and (bony) syndactyly (II)--was included. Also a group of "unclassifiable" cases was added. This Japanese proposed classification is a real improvement and most clinicians and surgeons tend to use it in the future.

Classification of parotidectomy: a proposed modification to the European Salivary Gland Society classification system.

PubMed

Wong, Wai Keat; Shetty, Subhaschandra

2017-08-01

Parotidectomy remains the mainstay of treatment for both benign and malignant lesions of the parotid gland. There exists a wide range of possible surgical options in parotidectomy in terms of extent of parotid tissue removed. There is increasing need for uniformity of terminology resulting from growing interest in modifications of the conventional parotidectomy. It is, therefore, of paramount importance for a standardized classification system in describing extent of parotidectomy. Recently, the European Salivary Gland Society (ESGS) proposed a novel classification system for parotidectomy. The aim of this study is to evaluate this system. A classification system proposed by the ESGS was critically re-evaluated and modified to increase its accuracy and its acceptability. Modifications mainly focused on subdividing Levels I and II into IA, IB, IIA, and IIB. From June 2006 to June 2016, 126 patients underwent 130 parotidectomies at our hospital. The classification system was tested in that cohort of patient. While the ESGS classification system is comprehensive, it does not cover all possibilities. The addition of Sublevels IA, IB, IIA, and IIB may help to address some of the clinical situations seen and is clinically relevant. We aim to test the modified classification system for partial parotidectomy to address some of the challenges mentioned.

Automated classification of articular cartilage surfaces based on surface texture.

PubMed

Stachowiak, G P; Stachowiak, G W; Podsiadlo, P

2006-11-01

In this study the automated classification system previously developed by the authors was used to classify articular cartilage surfaces with different degrees of wear. This automated system classifies surfaces based on their texture. Plug samples of sheep cartilage (pins) were run on stainless steel discs under various conditions using a pin-on-disc tribometer. Testing conditions were specifically designed to produce different severities of cartilage damage due to wear. Environmental scanning electron microscope (SEM) (ESEM) images of cartilage surfaces, that formed a database for pattern recognition analysis, were acquired. The ESEM images of cartilage were divided into five groups (classes), each class representing different wear conditions or wear severity. Each class was first examined and assessed visually. Next, the automated classification system (pattern recognition) was applied to all classes. The results of the automated surface texture classification were compared to those based on visual assessment of surface morphology. It was shown that the texture-based automated classification system was an efficient and accurate method of distinguishing between various cartilage surfaces generated under different wear conditions. It appears that the texture-based classification method has potential to become a useful tool in medical diagnostics.

How Should Children with Speech Sound Disorders be Classified? A Review and Critical Evaluation of Current Classification Systems

ERIC Educational Resources Information Center

Waring, R.; Knight, R.

2013-01-01

Background: Children with speech sound disorders (SSD) form a heterogeneous group who differ in terms of the severity of their condition, underlying cause, speech errors, involvement of other aspects of the linguistic system and treatment response. To date there is no universal and agreed-upon classification system. Instead, a number of…

Abnormal Uterine Bleeding: American College of Nurse-Midwives.

PubMed

2016-07-01

Variations in uterine bleeding, termed abnormal uterine bleeding, occur commonly among women and often are physiologic in nature with no significant consequences. However, abnormal uterine bleeding can cause significant distress to women or may signify an underlying pathologic condition. Most women experience variations in menstrual and perimenstrual bleeding in their lifetimes; therefore, the ability of the midwife to differentiate between normal and abnormal bleeding is a key diagnostic skill. A comprehensive history and use of the PALM-COEIN classification system will provide clear guidelines for clinical management, evidence-based treatment, and an individualized plan of care. The purpose of this Clinical Bulletin is to define and describe classifications of abnormal uterine bleeding, review updated terminology, and identify methods of assessment and treatment using a woman-centered approach. © 2016 by the American College of Nurse-Midwives.

15 CFR 921.3 - National Estuarine Research Reserve System biogeographic classification scheme and estuarine...

Code of Federal Regulations, 2012 CFR

2012-01-01

... System biogeographic classification scheme and estuarine typologies. 921.3 Section 921.3 Commerce and... biogeographic classification scheme and estuarine typologies. (a) National Estuarine Research Reserves are... classification scheme based on regional variations in the nation's coastal zone has been developed. The...

15 CFR 921.3 - National Estuarine Research Reserve System biogeographic classification scheme and estuarine...

Code of Federal Regulations, 2013 CFR

2013-01-01

... System biogeographic classification scheme and estuarine typologies. 921.3 Section 921.3 Commerce and... biogeographic classification scheme and estuarine typologies. (a) National Estuarine Research Reserves are... classification scheme based on regional variations in the nation's coastal zone has been developed. The...

15 CFR 921.3 - National Estuarine Research Reserve System biogeographic classification scheme and estuarine...

Code of Federal Regulations, 2010 CFR

2010-01-01

... System biogeographic classification scheme and estuarine typologies. 921.3 Section 921.3 Commerce and... biogeographic classification scheme and estuarine typologies. (a) National Estuarine Research Reserves are... classification scheme based on regional variations in the nation's coastal zone has been developed. The...

15 CFR 921.3 - National Estuarine Research Reserve System biogeographic classification scheme and estuarine...

Code of Federal Regulations, 2014 CFR

2014-01-01

... System biogeographic classification scheme and estuarine typologies. 921.3 Section 921.3 Commerce and... biogeographic classification scheme and estuarine typologies. (a) National Estuarine Research Reserves are... classification scheme based on regional variations in the nation's coastal zone has been developed. The...

15 CFR 921.3 - National Estuarine Research Reserve System biogeographic classification scheme and estuarine...

Code of Federal Regulations, 2011 CFR

2011-01-01

... System biogeographic classification scheme and estuarine typologies. 921.3 Section 921.3 Commerce and... biogeographic classification scheme and estuarine typologies. (a) National Estuarine Research Reserves are... classification scheme based on regional variations in the nation's coastal zone has been developed. The...

Automatic diagnosis of tuberculosis disease based on Plasmonic ELISA and color-based image classification.

PubMed

AbuHassan, Kamal J; Bakhori, Noremylia M; Kusnin, Norzila; Azmi, Umi Z M; Tania, Marzia H; Evans, Benjamin A; Yusof, Nor A; Hossain, M A

2017-07-01

Tuberculosis (TB) remains one of the most devastating infectious diseases and its treatment efficiency is majorly influenced by the stage at which infection with the TB bacterium is diagnosed. The available methods for TB diagnosis are either time consuming, costly or not efficient. This study employs a signal generation mechanism for biosensing, known as Plasmonic ELISA, and computational intelligence to facilitate automatic diagnosis of TB. Plasmonic ELISA enables the detection of a few molecules of analyte by the incorporation of smart nanomaterials for better sensitivity of the developed detection system. The computational system uses k-means clustering and thresholding for image segmentation. This paper presents the results of the classification performance of the Plasmonic ELISA imaging data by using various types of classifiers. The five-fold cross-validation results show high accuracy rate (>97%) in classifying TB images using the entire data set. Future work will focus on developing an intelligent mobile-enabled expert system to diagnose TB in real-time. The intelligent system will be clinically validated and tested in collaboration with healthcare providers in Malaysia.

Efficacy measures associated to a plantar pressure based classification system in diabetic foot medicine.

PubMed

Deschamps, Kevin; Matricali, Giovanni Arnoldo; Desmet, Dirk; Roosen, Philip; Keijsers, Noel; Nobels, Frank; Bruyninckx, Herman; Staes, Filip

2016-09-01

The concept of 'classification' has, similar to many other diseases, been found to be fundamental in the field of diabetic medicine. In the current study, we aimed at determining efficacy measures of a recently published plantar pressure based classification system. Technical efficacy of the classification system was investigated by applying a high resolution, pixel-level analysis on the normalized plantar pressure pedobarographic fields of the original experimental dataset consisting of 97 patients with diabetes and 33 persons without diabetes. Clinical efficacy was assessed by considering the occurence of foot ulcers at the plantar aspect of the forefoot in this dataset. Classification efficacy was assessed by determining the classification recognition rate as well as its sensitivity and specificity using cross-validation subsets of the experimental dataset together with a novel cohort of 12 patients with diabetes. Pixel-level comparison of the four groups associated to the classification system highlighted distinct regional differences. Retrospective analysis showed the occurence of eleven foot ulcers in the experimental dataset since their gait analysis. Eight out of the eleven ulcers developed in a region of the foot which had the highest forces. Overall classification recognition rate exceeded 90% for all cross-validation subsets. Sensitivity and specificity of the four groups associated to the classification system exceeded respectively the 0.7 and 0.8 level in all cross-validation subsets. The results of the current study support the use of the novel plantar pressure based classification system in diabetic foot medicine. It may particularly serve in communication, diagnosis and clinical decision making. Copyright © 2016 Elsevier B.V. All rights reserved.

Lenke and King classification systems for adolescent idiopathic scoliosis: interobserver agreement and postoperative results.

PubMed

Hosseinpour-Feizi, Hojjat; Soleimanpour, Jafar; Sales, Jafar Ganjpour; Arzroumchilar, Ali

2011-01-01

The aim of this study was to investigate the interobserver agreement of the Lenke and King classifications for adolescent idiopathic scoliosis, and to compare the results of surgery performed based on classification of the scoliosis according to each of these classification systems. The study was conducted in Shohada Hospital in Tabriz, Iran, between 2009 and 2010. First, a reliability assessment was undertaken to assess interobserver agreement of the Lenke and King classifications for adolescent idiopathic scoliosis. Second, postoperative efficacy and safety of surgery performed based on the Lenke and King classifications were compared. Kappa coefficients of agreement were calculated to assess the agreement. Outcomes were compared using bivariate tests and repeated measures analysis of variance. A low to moderate interobserver agreement was observed for the King classification; the Lenke classification yielded mostly high agreement coefficients. The outcome of surgery was not found to be substantially different between the two systems. Based on the results, the Lenke classification method seems advantageous. This takes into consideration the Lenke classification's priority in providing details of curvatures in different anatomical surfaces to explain precise intensity of scoliosis, that it has higher interobserver agreement scores, and also that it leads to noninferior postoperative results compared with the King classification method.

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.

Changing beliefs for changing movement and pain: Classification-based cognitive functional therapy (CB-CFT) for chronic non-specific low back pain.

PubMed

Meziat Filho, N

2016-02-01

This case report presents the effect of classification-based cognitive functional therapy in a patient with chronic disabling low back pain. The patient was assessed using a multidimensional biopsychosocial classification system and was classified as having flexion pattern of movement impairment disorder. Management of this patient was to change her belief that bending over and sitting would cause damage to her disc, combined with active exercises for graded exposure to lumbar flexion to restore normal movement. Three months after the first appointment, the treatment resulted in reduced pain, the mitigation of fear avoidance beliefs and the remediation of functional disability. The patient returned to work and was walking for one hour a day on a treadmill. The cognitive intervention to change the patient's negative beliefs related to the biomedical model was important to make the graded exercises and the lifestyle changes possible. Copyright © 2015 Elsevier Ltd. All rights reserved.

The Comprehensive AOCMF Classification: Skull Base and Cranial Vault Fractures – Level 2 and 3 Tutorial

PubMed Central

Ieva, Antonio Di; Audigé, Laurent; Kellman, Robert M.; Shumrick, Kevin A.; Ringl, Helmut; Prein, Joachim; Matula, Christian

2014-01-01

The AOCMF Classification Group developed a hierarchical three-level craniomaxillofacial classification system with increasing level of complexity and details. The highest level 1 system distinguish four major anatomical units, including the mandible (code 91), midface (code 92), skull base (code 93), and cranial vault (code 94). This tutorial presents the level 2 and more detailed level 3 systems for the skull base and cranial vault units. The level 2 system describes fracture location outlining the topographic boundaries of the anatomic regions, considering in particular the endocranial and exocranial skull base surfaces. The endocranial skull base is divided into nine regions; a central skull base adjoining a left and right side are divided into the anterior, middle, and posterior skull base. The exocranial skull base surface and cranial vault are divided in regions defined by the names of the bones involved: frontal, parietal, temporal, sphenoid, and occipital bones. The level 3 system allows assessing fracture morphology described by the presence of fracture fragmentation, displacement, and bone loss. A documentation of associated intracranial diagnostic features is proposed. This tutorial is organized in a sequence of sections dealing with the description of the classification system with illustrations of the topographical skull base and cranial vault regions along with rules for fracture location and coding, a series of case examples with clinical imaging and a general discussion on the design of this classification. PMID:25489394

Multi-material classification of dry recyclables from municipal solid waste based on thermal imaging.

PubMed

Gundupalli, Sathish Paulraj; Hait, Subrata; Thakur, Atul

2017-12-01

There has been a significant rise in municipal solid waste (MSW) generation in the last few decades due to rapid urbanization and industrialization. Due to the lack of source segregation practice, a need for automated segregation of recyclables from MSW exists in the developing countries. This paper reports a thermal imaging based system for classifying useful recyclables from simulated MSW sample. Experimental results have demonstrated the possibility to use thermal imaging technique for classification and a robotic system for sorting of recyclables in a single process step. The reported classification system yields an accuracy in the range of 85-96% and is comparable with the existing single-material recyclable classification techniques. We believe that the reported thermal imaging based system can emerge as a viable and inexpensive large-scale classification-cum-sorting technology in recycling plants for processing MSW in developing countries. Copyright © 2017 Elsevier Ltd. All rights reserved.

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.

A universal hybrid decision tree classifier design for human activity classification.

PubMed

Chien, Chieh; Pottie, Gregory J

2012-01-01

A system that reliably classifies daily life activities can contribute to more effective and economical treatments for patients with chronic conditions or undergoing rehabilitative therapy. We propose a universal hybrid decision tree classifier for this purpose. The tree classifier can flexibly implement different decision rules at its internal nodes, and can be adapted from a population-based model when supplemented by training data for individuals. The system was tested using seven subjects each monitored by 14 triaxial accelerometers. Each subject performed fourteen different activities typical of daily life. Using leave-one-out cross validation, our decision tree produced average classification accuracies of 89.9%. In contrast, the MATLAB personalized tree classifiers using Gini's diversity index as the split criterion followed by optimally tuning the thresholds for each subject yielded 69.2%.

DNA methylation-based classification and grading system for meningioma: a multicentre, retrospective analysis.

PubMed

Sahm, Felix; Schrimpf, Daniel; Stichel, Damian; Jones, David T W; Hielscher, Thomas; Schefzyk, Sebastian; Okonechnikov, Konstantin; Koelsche, Christian; Reuss, David E; Capper, David; Sturm, Dominik; Wirsching, Hans-Georg; Berghoff, Anna Sophie; Baumgarten, Peter; Kratz, Annekathrin; Huang, Kristin; Wefers, Annika K; Hovestadt, Volker; Sill, Martin; Ellis, Hayley P; Kurian, Kathreena M; Okuducu, Ali Fuat; Jungk, Christine; Drueschler, Katharina; Schick, Matthias; Bewerunge-Hudler, Melanie; Mawrin, Christian; Seiz-Rosenhagen, Marcel; Ketter, Ralf; Simon, Matthias; Westphal, Manfred; Lamszus, Katrin; Becker, Albert; Koch, Arend; Schittenhelm, Jens; Rushing, Elisabeth J; Collins, V Peter; Brehmer, Stefanie; Chavez, Lukas; Platten, Michael; Hänggi, Daniel; Unterberg, Andreas; Paulus, Werner; Wick, Wolfgang; Pfister, Stefan M; Mittelbronn, Michel; Preusser, Matthias; Herold-Mende, Christel; Weller, Michael; von Deimling, Andreas

2017-05-01

The WHO classification of brain tumours describes 15 subtypes of meningioma. Nine of these subtypes are allotted to WHO grade I, and three each to grade II and grade III. Grading is based solely on histology, with an absence of molecular markers. Although the existing classification and grading approach is of prognostic value, it harbours shortcomings such as ill-defined parameters for subtypes and grading criteria prone to arbitrary judgment. In this study, we aimed for a comprehensive characterisation of the entire molecular genetic landscape of meningioma to identify biologically and clinically relevant subgroups. In this multicentre, retrospective analysis, we investigated genome-wide DNA methylation patterns of meningiomas from ten European academic neuro-oncology centres to identify distinct methylation classes of meningiomas. The methylation classes were further characterised by DNA copy number analysis, mutational profiling, and RNA sequencing. Methylation classes were analysed for progression-free survival outcomes by the Kaplan-Meier method. The DNA methylation-based and WHO classification schema were compared using the Brier prediction score, analysed in an independent cohort with WHO grading, progression-free survival, and disease-specific survival data available, collected at the Medical University Vienna (Vienna, Austria), assessing methylation patterns with an alternative methylation chip. We retrospectively collected 497 meningiomas along with 309 samples of other extra-axial skull tumours that might histologically mimic meningioma variants. Unsupervised clustering of DNA methylation data clearly segregated all meningiomas from other skull tumours. We generated genome-wide DNA methylation profiles from all 497 meningioma samples. DNA methylation profiling distinguished six distinct clinically relevant methylation classes associated with typical mutational, cytogenetic, and gene expression patterns. Compared with WHO grading, classification by individual and combined methylation classes more accurately identifies patients at high risk of disease progression in tumours with WHO grade I histology, and patients at lower risk of recurrence among WHO grade II tumours (p=0·0096) from the Brier prediction test). We validated this finding in our independent cohort of 140 patients with meningioma. DNA methylation-based meningioma classification captures clinically more homogenous groups and has a higher power for predicting tumour recurrence and prognosis than the WHO classification. The approach presented here is potentially very useful for stratifying meningioma patients to observation-only or adjuvant treatment groups. We consider methylation-based tumour classification highly relevant for the future diagnosis and treatment of meningioma. German Cancer Aid, Else Kröner-Fresenius Foundation, and DKFZ/Heidelberg Institute of Personalized Oncology/Precision Oncology Program. Copyright © 2017 Elsevier Ltd. All rights reserved.

Prediction of lithium response in first-episode mania using the LITHium Intelligent Agent (LITHIA): Pilot data and proof-of-concept.

PubMed

Fleck, David E; Ernest, Nicholas; Adler, Caleb M; Cohen, Kelly; Eliassen, James C; Norris, Matthew; Komoroski, Richard A; Chu, Wen-Jang; Welge, Jeffrey A; Blom, Thomas J; DelBello, Melissa P; Strakowski, Stephen M

2017-06-01

Individualized treatment for bipolar disorder based on neuroimaging treatment targets remains elusive. To address this shortcoming, we developed a linguistic machine learning system based on a cascading genetic fuzzy tree (GFT) design called the LITHium Intelligent Agent (LITHIA). Using multiple objectively defined functional magnetic resonance imaging (fMRI) and proton magnetic resonance spectroscopy ( 1 H-MRS) inputs, we tested whether LITHIA could accurately predict the lithium response in participants with first-episode bipolar mania. We identified 20 subjects with first-episode bipolar mania who received an adequate trial of lithium over 8 weeks and both fMRI and 1 H-MRS scans at baseline pre-treatment. We trained LITHIA using 18 1 H-MRS and 90 fMRI inputs over four training runs to classify treatment response and predict symptom reductions. Each training run contained a randomly selected 80% of the total sample and was followed by a 20% validation run. Over a different randomly selected distribution of the sample, we then compared LITHIA to eight common classification methods. LITHIA demonstrated nearly perfect classification accuracy and was able to predict post-treatment symptom reductions at 8 weeks with at least 88% accuracy in training and 80% accuracy in validation. Moreover, LITHIA exceeded the predictive capacity of the eight comparator methods and showed little tendency towards overfitting. The results provided proof-of-concept that a novel GFT is capable of providing control to a multidimensional bioinformatics problem-namely, prediction of the lithium response-in a pilot data set. Future work on this, and similar machine learning systems, could help assign psychiatric treatments more efficiently, thereby optimizing outcomes and limiting unnecessary treatment. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

The International Neuroblastoma Risk Group (INRG) Staging System: An INRG Task Force Report

PubMed Central

Monclair, Tom; Brodeur, Garrett M.; Ambros, Peter F.; Brisse, Hervé J.; Cecchetto, Giovanni; Holmes, Keith; Kaneko, Michio; London, Wendy B.; Matthay, Katherine K.; Nuchtern, Jed G.; von Schweinitz, Dietrich; Simon, Thorsten; Cohn, Susan L.; Pearson, Andrew D.J.

2009-01-01

Purpose The International Neuroblastoma Risk Group (INRG) classification system was developed to establish a consensus approach for pretreatment risk stratification. Because the International Neuroblastoma Staging System (INSS) is a postsurgical staging system, a new clinical staging system was required for the INRG pretreatment risk classification system. Methods To stage patients before any treatment, the INRG Task Force, consisting of neuroblastoma experts from Australia/New Zealand, China, Europe, Japan, and North America, developed a new INRG staging system (INRGSS) based on clinical criteria and image-defined risk factors (IDRFs). To investigate the impact of IDRFs on outcome, survival analyses were performed on 661 European patients with INSS stages 1, 2, or 3 disease for whom IDRFs were known. Results In the INGRSS, locoregional tumors are staged L1 or L2 based on the absence or presence of one or more of 20 IDRFs, respectively. Metastatic tumors are defined as stage M, except for stage MS, in which metastases are confined to the skin, liver, and/or bone marrow in children younger than 18 months of age. Within the 661-patient cohort, IDRFs were present (ie, stage L2) in 21% of patients with stage 1, 45% of patients with stage 2, and 94% of patients with stage 3 disease. Patients with INRGSS stage L2 disease had significantly lower 5-year event-free survival than those with INRGSS stage L1 disease (78% ± 4% v 90% ± 3%; P = .0010). Conclusion Use of the new staging (INRGSS) and risk classification (INRG) of neuroblastoma will greatly facilitate the comparison of risk-based clinical trials conducted in different regions of the world. PMID:19047290

A study on the predictability of acute lymphoblastic leukaemia response to treatment using a hybrid oncosimulator.

PubMed

Ouzounoglou, Eleftherios; Kolokotroni, Eleni; Stanulla, Martin; Stamatakos, Georgios S

2018-02-06

Efficient use of Virtual Physiological Human (VPH)-type models for personalized treatment response prediction purposes requires a precise model parameterization. In the case where the available personalized data are not sufficient to fully determine the parameter values, an appropriate prediction task may be followed. This study, a hybrid combination of computational optimization and machine learning methods with an already developed mechanistic model called the acute lymphoblastic leukaemia (ALL) Oncosimulator which simulates ALL progression and treatment response is presented. These methods are used in order for the parameters of the model to be estimated for retrospective cases and to be predicted for prospective ones. The parameter value prediction is based on a regression model trained on retrospective cases. The proposed Hybrid ALL Oncosimulator system has been evaluated when predicting the pre-phase treatment outcome in ALL. This has been correctly achieved for a significant percentage of patient cases tested (approx. 70% of patients). Moreover, the system is capable of denying the classification of cases for which the results are not trustworthy enough. In that case, potentially misleading predictions for a number of patients are avoided, while the classification accuracy for the remaining patient cases further increases. The results obtained are particularly encouraging regarding the soundness of the proposed methodologies and their relevance to the process of achieving clinical applicability of the proposed Hybrid ALL Oncosimulator system and VPH models in general.

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.

Classification of full-thickness rotator cuff lesions: a review

PubMed Central

Lädermann, Alexandre; Burkhart, Stephen S.; Hoffmeyer, Pierre; Neyton, Lionel; Collin, Philippe; Yates, Evan; Denard, Patrick J.

2016-01-01

Rotator cuff lesions (RCL) have considerable variability in location, tear pattern, functional impairment, and repairability. Historical classifications for differentiating these lesions have been based upon factors such as the size and shape of the tear, and the degree of atrophy and fatty infiltration. Additional recent descriptions include bipolar rotator cuff insufficiency, ‘Fosbury flop tears’, and musculotendinous lesions. Recommended treatment is based on the location of the lesion, patient factors and associated pathology, and often includes personal experience and data from case series. Development of a more comprehensive classification which integrates historical and newer descriptions of RCLs may help to guide treatment further. Cite this article: Lädermann A, Burkhart SS, Hoffmeyer P, et al. Classification of full thickness rotator cuff lesions: a review. EFORT Open Rev 2016;1:420-430. DOI: 10.1302/2058-5241.1.160005. PMID:28461921

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.

Characteristics of patients with lower extremity symptoms treated with slump stretching: a case series.

PubMed

George, Steven Z

2002-08-01

Prospective case series. The purpose of this case series was to describe the criteria used to determine if patients were to receive slump stretch treatment within a treatment-based classification system and to describe selected symptom characteristics associated with these patients. Previous reports from the literature suggest that the slump test position may be a useful treatment and evaluation technique. However, little information has been presented regarding how to identify patients who are appropriate to treat with slump stretching and the symptom characteristics associated with these patients. Prior to recruitment, criteria were established to identify patients who would be considered appropriate to treat with slump stretching. Consecutive patients referred with low back diagnosis or low-back-related diagnoses were then evaluated using a treatment-based classification system. Selected symptom characteristics were collected from patients treated with slump stretching. Out of 88 consecutive patients with low back diagnoses or low-back-related diagnoses, 6 met the study's inclusion criteria and were treated with slump stretching. All pain diagrams were classified as "organic" or "possibly organic," and the most common symptom descriptor was "deep ache." At the discharge session of physical therapy, 5 of 6 patients had symptoms that were more proximally located and all patients reported a decrease in symptom intensity. Favorable changes in symptom intensity and location were observed for this case series, but definitive conclusions cannot be drawn from this study design. Additional research needs to be completed to determine if the slump test position is an effective evaluation and treatment technique.

A new tree classification system for southern hardwoods

Treesearch

James S. Meadows; Daniel A. Jr. Skojac

2008-01-01

A new tree classification system for southern hardwoods is described. The new system is based on the Putnam tree classification system, originally developed by Putnam et al., 1960, Management ond inventory of southern hardwoods, Agriculture Handbook 181, US For. Sew., Washington, DC, which consists of four tree classes: (1) preferred growing stock, (2) reserve growing...

Lenke and King classification systems for adolescent idiopathic scoliosis: interobserver agreement and postoperative results

PubMed Central

Hosseinpour-Feizi, Hojjat; Soleimanpour, Jafar; Sales, Jafar Ganjpour; Arzroumchilar, Ali

2011-01-01

Purpose The aim of this study was to investigate the interobserver agreement of the Lenke and King classifications for adolescent idiopathic scoliosis, and to compare the results of surgery performed based on classification of the scoliosis according to each of these classification systems. Methods The study was conducted in Shohada Hospital in Tabriz, Iran, between 2009 and 2010. First, a reliability assessment was undertaken to assess interobserver agreement of the Lenke and King classifications for adolescent idiopathic scoliosis. Second, postoperative efficacy and safety of surgery performed based on the Lenke and King classifications were compared. Kappa coefficients of agreement were calculated to assess the agreement. Outcomes were compared using bivariate tests and repeated measures analysis of variance. Results A low to moderate interobserver agreement was observed for the King classification; the Lenke classification yielded mostly high agreement coefficients. The outcome of surgery was not found to be substantially different between the two systems. Conclusion Based on the results, the Lenke classification method seems advantageous. This takes into consideration the Lenke classification’s priority in providing details of curvatures in different anatomical surfaces to explain precise intensity of scoliosis, that it has higher interobserver agreement scores, and also that it leads to noninferior postoperative results compared with the King classification method. PMID:22267934

[Structure of pain management facilities in Germany : Classification of medical and psychological pain treatment services-Consensus of the Joint Commission of the Professional Societies and Organizations for Quality in Pain Medicine].

PubMed

Müller-Schwefe, G H H; Nadstawek, J; Tölle, T; Nilges, P; Überall, M A; Laubenthal, H J; Bock, F; Arnold, B; Casser, H R; Cegla, T H; Emrich, O M D; Graf-Baumann, T; Henning, J; Horlemann, J; Kayser, H; Kletzko, H; Koppert, W; Längler, K H; Locher, H; Ludwig, J; Maurer, S; Pfingsten, M; Schäfer, M; Schenk, M; Willweber-Strumpf, A

2016-06-01

On behalf of the Medical/Psychological Pain Associations, Pain Patients Alliance and the Professional Association of Pain Physicians and Psychologists, the Joint Commission of Professional Societies and Organizations for Quality in Pain Medicine, working in close collaboration with the respective presidents, has developed verifiable structural and process-related criteria for the classification of medical and psychological pain treatment facilities in Germany. Based on the established system of graded care in Germany and on existing qualifications, these criteria also argue for the introduction of a basic qualification in pain medicine. In addition to the first-ever comprehensive description of psychological pain facilities, the criteria presented can be used to classify five different levels of pain facilities, from basic pain management facilities, to specialized institutions, to the Centre for Interdisciplinary Pain Medicine. The recommendations offer binding and verifiable criteria for quality assurance in pain medicine and improved pain treatment.

Japanese Society for Cancer of the Colon and Rectum (JSCCR) guidelines 2016 for the treatment of colorectal cancer.

PubMed

Watanabe, Toshiaki; Muro, Kei; Ajioka, Yoichi; Hashiguchi, Yojiro; Ito, Yoshinori; Saito, Yutaka; Hamaguchi, Tetsuya; Ishida, Hideyuki; Ishiguro, Megumi; Ishihara, Soichiro; Kanemitsu, Yukihide; Kawano, Hiroshi; Kinugasa, Yusuke; Kokudo, Norihiro; Murofushi, Keiko; Nakajima, Takako; Oka, Shiro; Sakai, Yoshiharu; Tsuji, Akihito; Uehara, Keisuke; Ueno, Hideki; Yamazaki, Kentaro; Yoshida, Masahiro; Yoshino, Takayuki; Boku, Narikazu; Fujimori, Takahiro; Itabashi, Michio; Koinuma, Nobuo; Morita, Takayuki; Nishimura, Genichi; Sakata, Yuh; Shimada, Yasuhiro; Takahashi, Keiichi; Tanaka, Shinji; Tsuruta, Osamu; Yamaguchi, Toshiharu; Yamaguchi, Naohiko; Tanaka, Toshiaki; Kotake, Kenjiro; Sugihara, Kenichi

2018-02-01

Japanese mortality due to colorectal cancer is on the rise, surpassing 49,000 in 2015. Many new treatment methods have been developed during recent decades. The Japanese Society for Cancer of the Colon and Rectum Guidelines 2016 for the treatment of colorectal cancer (JSCCR Guidelines 2016) were prepared to show standard treatment strategies for colorectal cancer, to eliminate disparities among institutions in terms of treatment, to eliminate unnecessary treatment and insufficient treatment, and to deepen mutual understanding between health-care professionals and patients by making these Guidelines available to the general public. These Guidelines were prepared by consensus reached by the JSCCR Guideline Committee, based on a careful review of the evidence retrieved by literature searches, and in view of the medical health insurance system and actual clinical practice settings in Japan. Therefore, these Guidelines can be used as a tool for treating colorectal cancer in actual clinical practice settings. More specifically, they can be used as a guide to obtaining informed consent from patients and choosing the method of treatment for each patient. As a result of the discussions held by the Guideline Committee, controversial issues were selected as Clinical Questions, and recommendations were made. Each recommendation is accompanied by a classification of the evidence and a classification of recommendation categories based on the consensus reached by the Guideline Committee members. Here we present the English version of the JSCCR Guidelines 2016.

Subject-Adaptive Real-Time Sleep Stage Classification Based on Conditional Random Field

PubMed Central

Luo, Gang; Min, Wanli

2007-01-01

Sleep staging is the pattern recognition task of classifying sleep recordings into sleep stages. This task is one of the most important steps in sleep analysis. It is crucial for the diagnosis and treatment of various sleep disorders, and also relates closely to brain-machine interfaces. We report an automatic, online sleep stager using electroencephalogram (EEG) signal based on a recently-developed statistical pattern recognition method, conditional random field, and novel potential functions that have explicit physical meanings. Using sleep recordings from human subjects, we show that the average classification accuracy of our sleep stager almost approaches the theoretical limit and is about 8% higher than that of existing systems. Moreover, for a new subject snew with limited training data Dnew, we perform subject adaptation to improve classification accuracy. Our idea is to use the knowledge learned from old subjects to obtain from Dnew a regulated estimate of CRF’s parameters. Using sleep recordings from human subjects, we show that even without any Dnew, our sleep stager can achieve an average classification accuracy of 70% on snew. This accuracy increases with the size of Dnew and eventually becomes close to the theoretical limit. PMID:18693884

Advances in the molecular genetics of gliomas - implications for classification and therapy.

PubMed

Reifenberger, Guido; Wirsching, Hans-Georg; Knobbe-Thomsen, Christiane B; Weller, Michael

2017-07-01

Genome-wide molecular-profiling studies have revealed the characteristic genetic alterations and epigenetic profiles associated with different types of gliomas. These molecular characteristics can be used to refine glioma classification, to improve prediction of patient outcomes, and to guide individualized treatment. Thus, the WHO Classification of Tumours of the Central Nervous System was revised in 2016 to incorporate molecular biomarkers - together with classic histological features - in an integrated diagnosis, in order to define distinct glioma entities as precisely as possible. This paradigm shift is markedly changing how glioma is diagnosed, and has important implications for future clinical trials and patient management in daily practice. Herein, we highlight the developments in our understanding of the molecular genetics of gliomas, and review the current landscape of clinically relevant molecular biomarkers for use in classification of the disease subtypes. Novel approaches to the genetic characterization of gliomas based on large-scale DNA-methylation profiling and next-generation sequencing are also discussed. In addition, we illustrate how advances in the molecular genetics of gliomas can promote the development and clinical translation of novel pathogenesis-based therapeutic approaches, thereby paving the way towards precision medicine in neuro-oncology.

On-board multispectral classification study

NASA Technical Reports Server (NTRS)

Ewalt, D.

1979-01-01

The factors relating to onboard multispectral classification were investigated. The functions implemented in ground-based processing systems for current Earth observation sensors were reviewed. The Multispectral Scanner, Thematic Mapper, Return Beam Vidicon, and Heat Capacity Mapper were studied. The concept of classification was reviewed and extended from the ground-based image processing functions to an onboard system capable of multispectral classification. Eight different onboard configurations, each with varying amounts of ground-spacecraft interaction, were evaluated. Each configuration was evaluated in terms of turnaround time, onboard processing and storage requirements, geometric and classification accuracy, onboard complexity, and ancillary data required from the ground.

World Reference Base | FAO SOILS PORTAL | Food and Agriculture

Science.gov Websites

> Soil classification > World Reference Base FAO SOILS PORTAL Survey Assessment Biodiversity Management Degradation/Restoration Policies/Governance Publications Soil properties Soil classification World Reference Base FAO legend USDA soil taxonomy Universal soil classification National Systems Numerical

Second Language Writing Classification System Based on Word-Alignment Distribution

ERIC Educational Resources Information Center

Kotani, Katsunori; Yoshimi, Takehiko

2010-01-01

The present paper introduces an automatic classification system for assisting second language (L2) writing evaluation. This system, which classifies sentences written by L2 learners as either native speaker-like or learner-like sentences, is constructed by machine learning algorithms using word-alignment distributions as classification features…

2008 International Conference on Ectodermal Dysplasias Classification Conference Report

PubMed Central

Salinas, Carlos F.; Jorgenson, Ronald J.; Wright, J. Timothy; DiGiovanna, John J.; Fete, Mary D.

2009-01-01

There are many ways to classify ectodermal dysplasia syndromes. Clinicians in practice use a list of syndromes from which to choose a potential diagnosis, paging through a volume, such as Freire-Maia and Pinheiro's corpus, matching their patient's findings to listed syndromes. Medical researchers may want a list of syndromes that share one (monothetic system) or several (polythetic system) traits in order to focus research on a narrowly defined group. Special interest groups may want a list from which they can choose constituencies, and insurance companies and government agencies may want a list to determine for whom to provide (or deny) health care coverage. Furthermore, various molecular biologists are now promoting classification systems based on gene mutation (e.g. TP63 associated syndromes) or common molecular pathways. The challenge will be to balance comprehensiveness within the classification with usability and accessibility so that the benefits truly serve the needs of researchers, health care providers and ultimately the individuals and families directly affected by ectodermal dysplasias. It is also recognized that a new classification approach is an ongoing process and will require periodical reviews or updates. Whatever scheme is developed, however, will have far-reaching application for other groups of disorders for which classification is complicated by the number of interested parties and advances in diagnostic acumen. Consensus among interested parties is necessary for optimizing communication among the diverse groups whether it be for equitable distribution of funds, correctness of diagnosis and treatment, or focusing research efforts. PMID:19681152

Classification of upper limb disability levels of children with spastic unilateral cerebral palsy using K-means algorithm.

PubMed

Raouafi, Sana; Achiche, Sofiane; Begon, Mickael; Sarcher, Aurélie; Raison, Maxime

2018-01-01

Treatment for cerebral palsy depends upon the severity of the child's condition and requires knowledge about upper limb disability. The aim of this study was to develop a systematic quantitative classification method of the upper limb disability levels for children with spastic unilateral cerebral palsy based on upper limb movements and muscle activation. Thirteen children with spastic unilateral cerebral palsy and six typically developing children participated in this study. Patients were matched on age and manual ability classification system levels I to III. Twenty-three kinematic and electromyographic variables were collected from two tasks. Discriminative analysis and K-means clustering algorithm were applied using 23 kinematic and EMG variables of each participant. Among the 23 kinematic and electromyographic variables, only two variables containing the most relevant information for the prediction of the four levels of severity of spastic unilateral cerebral palsy, which are fixed by manual ability classification system, were identified by discriminant analysis: (1) the Falconer index (CAI E ) which represents the ratio of biceps to triceps brachii activity during extension and (2) the maximal angle extension (θ Extension,max ). A good correlation (Kendall Rank correlation coefficient = -0.53, p = 0.01) was found between levels fixed by manual ability classification system and the obtained classes. These findings suggest that the cost and effort needed to assess and characterize the disability level of a child can be further reduced.

Comparing the MRI-based Goutallier Classification to an experimental quantitative MR spectroscopic fat measurement of the supraspinatus muscle.

PubMed

Gilbert, Fabian; Böhm, Dirk; Eden, Lars; Schmalzl, Jonas; Meffert, Rainer H; Köstler, Herbert; Weng, Andreas M; Ziegler, Dirk

2016-08-22

The Goutallier Classification is a semi quantitative classification system to determine the amount of fatty degeneration in rotator cuff muscles. Although initially proposed for axial computer tomography scans it is currently applied to magnet-resonance-imaging-scans. The role for its clinical use is controversial, as the reliability of the classification has been shown to be inconsistent. The purpose of this study was to compare the semi quantitative MRI-based Goutallier Classification applied by 5 different raters to experimental MR spectroscopic quantitative fat measurement in order to determine the correlation between this classification system and the true extent of fatty degeneration shown by spectroscopy. MRI-scans of 42 patients with rotator cuff tears were examined by 5 shoulder surgeons and were graduated according to the MRI-based Goutallier Classification proposed by Fuchs et al. Additionally the fat/water ratio was measured with MR spectroscopy using the experimental SPLASH technique. The semi quantitative grading according to the Goutallier Classification was statistically correlated with the quantitative measured fat/water ratio using Spearman's rank correlation. Statistical analysis of the data revealed only fair correlation of the Goutallier Classification system and the quantitative fat/water ratio with R = 0.35 (p < 0.05). By dichotomizing the scale the correlation was 0.72. The interobserver and intraobserver reliabilities were substantial with R = 0.62 and R = 0.74 (p < 0.01). The correlation between the semi quantitative MRI based Goutallier Classification system and MR spectroscopic fat measurement is weak. As an adequate estimation of fatty degeneration based on standard MRI may not be possible, quantitative methods need to be considered in order to increase diagnostic safety and thus provide patients with ideal care in regard to the amount of fatty degeneration. Spectroscopic MR measurement may increase the accuracy of the Goutallier classification and thus improve the prediction of clinical results after rotator cuff repair. However, these techniques are currently only available in an experimental setting.

Italian consensus conference on guidelines for conservative treatment on lower limb muscle injuries in athlete

PubMed Central

Bisciotti, Gian Nicola; Volpi, Piero; Amato, Maurizio; Alberti, Giampietro; Allegra, Francesco; Aprato, Alessandro; Artina, Matteo; Auci, Alessio; Bait, Corrado; Bastieri, Gian Matteo; Balzarini, Luca; Belli, Andrea; Bellini, Gianandrea; Bettinsoli, Pierfrancesco; Bisciotti, Alessandro; Bisciotti, Andrea; Bona, Stefano; Brambilla, Lorenzo; Bresciani, Marco; Buffoli, Michele; Calanna, Filippo; Canata, Gian Luigi; Cardinali, Davide; Carimati, Giulia; Cassaghi, Gabriella; Cautero, Enrico; Cena, Emanuele; Corradini, Barbara; D'Agostino, Cristina; De Donato, Massimo; Delle Rose, Giacomo; Di Marzo, Francesco; Di Pietto, Francesco; Enrica, Drapchind; Eirale, Cristiano; Febbrari, Luigi; Ferrua, Paolo; Foglia, Andrea; Galbiati, Alberto; Gheza, Alberto; Giammattei, Carlo; Masia, Francesco; Melegati, Gianluca; Moretti, Biagio; Moretti, Lorenzo; Niccolai, Roberto; Orgiani, Antonio; Orizio, Claudio; Pantalone, Andrea; Parra, Federica; Patroni, Paolo; Pereira Ruiz, Maria Teresa; Perri, Marzio; Petrillo, Stefano; Pulici, Luca; Quaglia, Alessandro; Ricciotti, Luca; Rosa, Francesco; Sasso, Nicola; Sprenger, Claudio; Tarantola, Chiara; Tenconi, Fabio Gianpaolo; Tosi, Fabio; Trainini, Michele; Tucciarone, Agostino; Yekdah, Ali; Vuckovic, Zarko; Zini, Raul; Chamari, Karim

2018-01-01

Provide the state of the art concerning (1) biology and aetiology, (2) classification, (3) clinical assessment and (4) conservative treatment of lower limb muscle injuries (MI) in athletes. Seventy international experts with different medical backgrounds participated in the consensus conference. They discussed and approved a consensus composed of four sections which are presented in these documents. This paper represents a synthesis of the consensus conference, the following four sections are discussed: (i) The biology and aetiology of MIs. A definition of MI was formulated and some key points concerning physiology and pathogenesis of MIs were discussed. (ii) The MI classification. A classification of MIs was proposed. (iii) The MI clinical assessment, in which were discussed anamnesis, inspection and clinical examination and are provided the relative guidelines. (iv) The MI conservative treatment, in which are provided the guidelines for conservative treatment based on the severity of the lesion. Furthermore, instrumental therapy and pharmacological treatment were discussed. Knowledge of the aetiology and biology of MIs is an essential prerequisite in order to plan and conduct a rehabilitation plan. Another important aspect is the use of a rational MI classification on prognostic values. We propose a classification based on radiological investigations performed by ultrasonography and MRI strongly linked to prognostic factors. Furthermore, the consensus conference results will able to provide fundamental guidelines for diagnostic and rehabilitation practice, also considering instrumental therapy and pharmacological treatment of MI. Expert opinion, level IV. PMID:29862040

Arrhythmia Classification Based on Multi-Domain Feature Extraction for an ECG Recognition System.

PubMed

Li, Hongqiang; Yuan, Danyang; Wang, Youxi; Cui, Dianyin; Cao, Lu

2016-10-20

Automatic recognition of arrhythmias is particularly important in the diagnosis of heart diseases. This study presents an electrocardiogram (ECG) recognition system based on multi-domain feature extraction to classify ECG beats. An improved wavelet threshold method for ECG signal pre-processing is applied to remove noise interference. A novel multi-domain feature extraction method is proposed; this method employs kernel-independent component analysis in nonlinear feature extraction and uses discrete wavelet transform to extract frequency domain features. The proposed system utilises a support vector machine classifier optimized with a genetic algorithm to recognize different types of heartbeats. An ECG acquisition experimental platform, in which ECG beats are collected as ECG data for classification, is constructed to demonstrate the effectiveness of the system in ECG beat classification. The presented system, when applied to the MIT-BIH arrhythmia database, achieves a high classification accuracy of 98.8%. Experimental results based on the ECG acquisition experimental platform show that the system obtains a satisfactory classification accuracy of 97.3% and is able to classify ECG beats efficiently for the automatic identification of cardiac arrhythmias.

Arrhythmia Classification Based on Multi-Domain Feature Extraction for an ECG Recognition System

PubMed Central

Li, Hongqiang; Yuan, Danyang; Wang, Youxi; Cui, Dianyin; Cao, Lu

2016-01-01

Automatic recognition of arrhythmias is particularly important in the diagnosis of heart diseases. This study presents an electrocardiogram (ECG) recognition system based on multi-domain feature extraction to classify ECG beats. An improved wavelet threshold method for ECG signal pre-processing is applied to remove noise interference. A novel multi-domain feature extraction method is proposed; this method employs kernel-independent component analysis in nonlinear feature extraction and uses discrete wavelet transform to extract frequency domain features. The proposed system utilises a support vector machine classifier optimized with a genetic algorithm to recognize different types of heartbeats. An ECG acquisition experimental platform, in which ECG beats are collected as ECG data for classification, is constructed to demonstrate the effectiveness of the system in ECG beat classification. The presented system, when applied to the MIT-BIH arrhythmia database, achieves a high classification accuracy of 98.8%. Experimental results based on the ECG acquisition experimental platform show that the system obtains a satisfactory classification accuracy of 97.3% and is able to classify ECG beats efficiently for the automatic identification of cardiac arrhythmias. PMID:27775596

Symptom classification in irritable bowel syndrome as a guide to treatment.

PubMed

Wiesner, Maureen; Naylor, Sally J; Copping, Ann; Furlong, Anita; Lynch, Andrew G; Parkes, Miles; Hunter, John O

2009-01-01

The treatment of irritable bowel syndrome (IBS) remains unsatisfactory. There are no objective markers for diagnosis, and classification (currently based on symptoms) provides little insight into potential causes or optimal therapy. The aim of this study was to determine whether a Swedish classification of IBS based on cluster analysis of patients' symptoms might provide a guide to successful treatment. Patients in a research clinic for IBS were classified according to criteria published by Ragnarsson & Bodemar (R&B) and also assessed independently by a clinician. Patients fulfilling the R&B criteria for subgroups 1 and 2 received specific treatments, either bulk laxatives or dietary treatment to reduce colonic fermentation, respectively. Patients who did not fit into these categories were given "best treatment" targeted at their predominant symptoms, but not limited in any way. Results before and after follow-up were assessed using a validated symptom-scoring scale. Seventy-one successive patients were recruited, and the numbers falling into R&B subgroups 1 and 2 were 15 (21%), and 28 (39%), respectively, leaving 28 (39%) unclassified. Receiver operating characteristic plots showed that the criteria for separation into subgroups 1 and 2 correlated well with the clinician's assessment. After treatment, symptom scores for the whole group showed a significant improvement (p<0.0001), but results were significantly better in subgroups 1 and 2 than in those unclassified, even when allowance was made for a potential therapeutic placebo effect of 40%. The R&B classification provides a helpful guide to treatment in many cases of IBS.

Canadian Network for Mood and Anxiety Treatments (CANMAT) clinical guidelines for the management of major depressive disorder in adults. I. Classification, burden and principles of management.

PubMed

Patten, Scott B; Kennedy, Sidney H; Lam, Raymond W; O'Donovan, Claire; Filteau, Marie J; Parikh, Sagar V; Ravindran, Arun V

2009-10-01

Major depressive disorder (MDD) is one of the most burdensome illnesses in Canada. The purpose of this introductory section of the 2009 revised CANMAT guidelines is to provide definitions of the depressive disorders (with an emphasis on MDD), summarize Canadian data concerning their epidemiology and describe overarching principles of managing these conditions. This section on "Classification, Burden and Principles of Management" is one of 5 guideline articles in the 2009 CANMAT guidelines. The CANMAT guidelines are based on a question-answer format to enhance accessibility to clinicians. An evidence-based format was used with updated systematic reviews of the literature and recommendations were graded according to the Level of Evidence using pre-defined criteria. Lines of Treatment were identified based on criteria that included evidence and expert clinical support. Epidemiologic data indicate that MDD afflicts 11% of Canadians at some time in their lives, and approximately 4% during any given year. MDD has a detrimental impact on overall health, role functioning and quality of life. Detection of MDD, accurate diagnosis and provision of evidence-based treatment are challenging tasks for both clinicians and for the health systems in which they work. Epidemiologic and clinical data cannot be seamlessly linked due to heterogeneity of syndromes within the population. In the eight years since the last CANMAT Guidelines for Treatment of Depressive Disorders were published, progress has been made in understanding the epidemiology and treatment of these disorders. Evidence supporting specific therapeutic interventions is summarized and evaluated in subsequent sections.

Clinical decision support of radiotherapy treatment planning: A data-driven machine learning strategy for patient-specific dosimetric decision making.

PubMed

Valdes, Gilmer; Simone, Charles B; Chen, Josephine; Lin, Alexander; Yom, Sue S; Pattison, Adam J; Carpenter, Colin M; Solberg, Timothy D

2017-12-01

Clinical decision support systems are a growing class of tools with the potential to impact healthcare. This study investigates the construction of a decision support system through which clinicians can efficiently identify which previously approved historical treatment plans are achievable for a new patient to aid in selection of therapy. Treatment data were collected for early-stage lung and postoperative oropharyngeal cancers treated using photon (lung and head and neck) and proton (head and neck) radiotherapy. Machine-learning classifiers were constructed using patient-specific feature-sets and a library of historical plans. Model accuracy was analyzed using learning curves, and historical treatment plan matching was investigated. Learning curves demonstrate that for these datasets, approximately 45, 60, and 30 patients are needed for a sufficiently accurate classification model for radiotherapy for early-stage lung, postoperative oropharyngeal photon, and postoperative oropharyngeal proton, respectively. The resulting classification model provides a database of previously approved treatment plans that are achievable for a new patient. An exemplary case, highlighting tradeoffs between the heart and chest wall dose while holding target dose constant in two historical plans is provided. We report on the first artificial-intelligence based clinical decision support system that connects patients to past discrete treatment plans in radiation oncology and demonstrate for the first time how this tool can enable clinicians to use past decisions to help inform current assessments. Clinicians can be informed of dose tradeoffs between critical structures early in the treatment process, enabling more time spent on finding the optimal course of treatment for individual patients. Copyright © 2017. Published by Elsevier B.V.

How do we understand the disagreement in the frequency of surgical site infection between the CDC and Clavien-Dindo classifications?

PubMed

Yamamoto, Takanobu; Takahashi, Satoshi; Ichihara, Koji; Hiyama, Yoshiki; Uehara, Teruhisa; Hashimoto, Jiro; Hirobe, Megumi; Masumori, Naoya

2015-02-01

To clarify the discrepancy in the incidence and severity of surgical site infections (SSI) for radical cystectomy between reports based on the CDC guideline and those using the Clavien-Dindo classification we evaluated 449 consecutive patients who underwent radical cystectomy for bladder cancer between 1990 and 2012. Of the 115 (25.6%) patients with SSI defined by the CDC guideline, 89 could be analyzed. We compared the SSI rates and severity defined by the CDC guideline and Clavien-Dindo classifications. There were 58 patients with superficial SSI, 16 with deep SSI, and 15 with organ/space SSI according to the CDC guideline. All patients with organ/space SSI were judged as "not having SSI" by the Clavien-Dindo classification. They were classified as having "intestinal prolapse", "intestinal fistula", "abdominal abscess" and "pelvic abscess." There was a significant association between the treatment duration and depth of SSI based on the CDC guideline by Spearman's rank-correlation coefficient (p < 0.001, r = 0.614) and with the grade of complications (p < 0.001, r = 0.632) in the Clavien-Dindo classification. Multivariate analysis showed that patients with grade III SSI in the Clavien-Dindo classification needed a significantly longer treatment duration. It is necessary to be aware that a discrepancy can occur automatically due to the different natures of the definitions. Using the CDC guideline, we can effectively estimate the future treatment period when SSI occurs. With the Clavien-Dindo classification, grade III SSI requires a longer treatment duration. Copyright © 2014 Japanese Society of Chemotherapy and The Japanese Association for Infectious Diseases. Published by Elsevier Ltd. All rights reserved.

A novel method to guide classification of para swimmers with limb deficiency.

PubMed

Hogarth, Luke; Payton, Carl; Van de Vliet, Peter; Connick, Mark; Burkett, Brendan

2018-05-30

The International Paralympic Committee has directed International Federations that govern Para sports to develop evidence-based classification systems. This study defined the impact of limb deficiency impairment on 100 m freestyle performance to guide an evidence-based classification system in Para Swimming, which will be implemented following the 2020 Tokyo Paralympic games. Impairment data and competitive race performances of 90 international swimmers with limb deficiency were collected. Ensemble partial least squares regression established the relationship between relative limb length measures and competitive 100 m freestyle performance. The model explained 80% of the variance in 100 m freestyle performance, and found hand length and forearm length to be the most important predictors of performance. Based on the results of this model, Para swimmers were clustered into four-, five-, six- and seven-class structures using nonparametric kernel density estimations. The validity of these classification structures, and effectiveness against the current classification system, were examined by establishing within-class variations in 100 m freestyle performance and differences between adjacent classes. The derived classification structures were found to be more effective than current classification based on these criteria. This study provides a novel method that can be used to improve the objectivity and transparency of decision-making in Para sport classification. Expert consensus from experienced coaches, Para swimmers, classifiers and sport science and medicine personnel will benefit the translation of these findings into a revised classification system that is accepted by the Para swimming community. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

DORS: DDC Online Retrieval System.

ERIC Educational Resources Information Center

Liu, Songqiao; Svenonius, Elaine

1991-01-01

Describes the Dewey Online Retrieval System (DORS), which was developed at the University of California, Los Angeles (UCLA), to experiment with classification-based search strategies in online catalogs. Classification structures in automated information retrieval are discussed; and specifications for a classification retrieval interface are…

A new hierarchical method for inter-patient heartbeat classification using random projections and RR intervals

PubMed Central

2014-01-01

Background The inter-patient classification schema and the Association for the Advancement of Medical Instrumentation (AAMI) standards are important to the construction and evaluation of automated heartbeat classification systems. The majority of previously proposed methods that take the above two aspects into consideration use the same features and classification method to classify different classes of heartbeats. The performance of the classification system is often unsatisfactory with respect to the ventricular ectopic beat (VEB) and supraventricular ectopic beat (SVEB). Methods Based on the different characteristics of VEB and SVEB, a novel hierarchical heartbeat classification system was constructed. This was done in order to improve the classification performance of these two classes of heartbeats by using different features and classification methods. First, random projection and support vector machine (SVM) ensemble were used to detect VEB. Then, the ratio of the RR interval was compared to a predetermined threshold to detect SVEB. The optimal parameters for the classification models were selected on the training set and used in the independent testing set to assess the final performance of the classification system. Meanwhile, the effect of different lead configurations on the classification results was evaluated. Results Results showed that the performance of this classification system was notably superior to that of other methods. The VEB detection sensitivity was 93.9% with a positive predictive value of 90.9%, and the SVEB detection sensitivity was 91.1% with a positive predictive value of 42.2%. In addition, this classification process was relatively fast. Conclusions A hierarchical heartbeat classification system was proposed based on the inter-patient data division to detect VEB and SVEB. It demonstrated better classification performance than existing methods. It can be regarded as a promising system for detecting VEB and SVEB of unknown patients in clinical practice. PMID:24981916

Categorization of intraoperative ureteroscopy complications using modified Satava classification system.

PubMed

Tepeler, Abdulkadir; Resorlu, Berkan; Sahin, Tolga; Sarikaya, Selcuk; Bayindir, Mirze; Oguz, Ural; Armagan, Abdullah; Unsal, Ali

2014-02-01

To review our experience with ureteroscopy (URS) in the treatment of ureteral calculi and stratify intraoperative complications of URS according to the modified Satava classification system. We performed a retrospective analysis of 1,208 patients (672 males and 536 females), with a mean age of 43.1 years (range 1-78), who underwent ureteroscopic procedures for removal of ureteral stones. Intraoperative complications were recorded according to modified Satava classification system. Grade 1 complications included incidents without consequences for the patient; grade 2 complications, which are treated intraoperatively with endoscopic surgery (grade 2a) or required endoscopic re-treatment (grade 2b); and grade 3 complications included incidents requiring open or laparoscopic surgery. The stones were completely removed in 1,067 (88.3%) patients after primary procedure by either simple extraction or after fragmentation. The overall incidence of intraoperative complications was 12.6%. The most common complications were proximal stone migration (3.9%), mucosal injury (2.8%), bleeding (1.9%), inability to reach stone (1.8%), malfunctioning or breakage of instruments (0.8%), ureteral perforation (0.8%) and ureteral avulsion (0.16%). According to modified Satava classification system, there were 4.5% grade 1; 4.4% grade 2a; 3.2% grade 2b; and 0.57% grade 3 complications. We think that modified Satava classification is a quick and simple system for describing the severity of intraoperative URS complications and this grading system will facilitate a better comparison for the surgical outcomes obtained from different centers.

Automated Classification of Radiology Reports for Acute Lung Injury: Comparison of Keyword and Machine Learning Based Natural Language Processing Approaches.

PubMed

Solti, Imre; Cooke, Colin R; Xia, Fei; Wurfel, Mark M

2009-11-01

This paper compares the performance of keyword and machine learning-based chest x-ray report classification for Acute Lung Injury (ALI). ALI mortality is approximately 30 percent. High mortality is, in part, a consequence of delayed manual chest x-ray classification. An automated system could reduce the time to recognize ALI and lead to reductions in mortality. For our study, 96 and 857 chest x-ray reports in two corpora were labeled by domain experts for ALI. We developed a keyword and a Maximum Entropy-based classification system. Word unigram and character n-grams provided the features for the machine learning system. The Maximum Entropy algorithm with character 6-gram achieved the highest performance (Recall=0.91, Precision=0.90 and F-measure=0.91) on the 857-report corpus. This study has shown that for the classification of ALI chest x-ray reports, the machine learning approach is superior to the keyword based system and achieves comparable results to highest performing physician annotators.

Automated Classification of Radiology Reports for Acute Lung Injury: Comparison of Keyword and Machine Learning Based Natural Language Processing Approaches

PubMed Central

Solti, Imre; Cooke, Colin R.; Xia, Fei; Wurfel, Mark M.

2010-01-01

This paper compares the performance of keyword and machine learning-based chest x-ray report classification for Acute Lung Injury (ALI). ALI mortality is approximately 30 percent. High mortality is, in part, a consequence of delayed manual chest x-ray classification. An automated system could reduce the time to recognize ALI and lead to reductions in mortality. For our study, 96 and 857 chest x-ray reports in two corpora were labeled by domain experts for ALI. We developed a keyword and a Maximum Entropy-based classification system. Word unigram and character n-grams provided the features for the machine learning system. The Maximum Entropy algorithm with character 6-gram achieved the highest performance (Recall=0.91, Precision=0.90 and F-measure=0.91) on the 857-report corpus. This study has shown that for the classification of ALI chest x-ray reports, the machine learning approach is superior to the keyword based system and achieves comparable results to highest performing physician annotators. PMID:21152268

A Novel Fiber Optic Based Surveillance System for Prevention of Pipeline Integrity Threats.

PubMed

Tejedor, Javier; Macias-Guarasa, Javier; Martins, Hugo F; Piote, Daniel; Pastor-Graells, Juan; Martin-Lopez, Sonia; Corredera, Pedro; Gonzalez-Herraez, Miguel

2017-02-12

This paper presents a novel surveillance system aimed at the detection and classification of threats in the vicinity of a long gas pipeline. The sensing system is based on phase-sensitive optical time domain reflectometry ( ϕ -OTDR) technology for signal acquisition and pattern recognition strategies for threat identification. The proposal incorporates contextual information at the feature level and applies a system combination strategy for pattern classification. The contextual information at the feature level is based on the tandem approach (using feature representations produced by discriminatively-trained multi-layer perceptrons) by employing feature vectors that spread different temporal contexts. The system combination strategy is based on a posterior combination of likelihoods computed from different pattern classification processes. The system operates in two different modes: (1) machine + activity identification, which recognizes the activity being carried out by a certain machine, and (2) threat detection, aimed at detecting threats no matter what the real activity being conducted is. In comparison with a previous system based on the same rigorous experimental setup, the results show that the system combination from the contextual feature information improves the results for each individual class in both operational modes, as well as the overall classification accuracy, with statistically-significant improvements.

Surgical management of morbidity due to lymphatic filariasis: the usefulness of a standardized international clinical classification of hydroceles.

PubMed

Capuano, G P; Capuano, C

2012-03-01

The objective of this work is to evaluate the usefulness of a standardized clinical classification of hydroceles in lymphatic filariasis endemic countries to guide their surgical management. 64 patients with hydroceles were operated in 2009-2010, in Level II hospitals (WHO classification), during two visits to Fiji, by the same mobile surgical team. The number of hydroceles treated was 83. We developed and evaluated a much needed clinical classification of hydroceles based on four criteria: Type (uni/bilateral); Side (left/right); Stage of enlargement of the scrotum rated from I to VI; Grade of burial of the penis rated from 0 to 4. It lead to the conclusion that 1) A Stage I or II hydrocele, associated with Grade 0 or 1 penis burial could be considered a "Simple Hydrocele". The surgical treatment is simple with no anticipated early complication. WHO Level II of health care structure seems adapted. 2) A Stage III or IV hydrocele associated with Grade 2, 3 or 4 penis burial could be considered a "Complicated Hydrocele". The operation is longer, more complicated and the possibility of occurrence of complications seems greater. A level III health care facility would be more adapted under the normal functioning of the health system. We conclude that a standardized clinical classification of hydroceles based on the Stage of enlargement of the scrotum and the Grade of burial of the penis appears to be a useful tool to guide the decision about the level of care and the surgical technique required. We use the same classification for penoscrotal lymphoedema. A decision tree is presented for the management of hydroceles in lymphatic filariasis endemic countries which could usefully complement the "Algorithm for management of scrotal swelling" proposed by WHO in 2002. An international classification system of hydroceles would also allow standardization and facilitate study design and comparisons of their results.

MO-DE-207B-03: Improved Cancer Classification Using Patient-Specific Biological Pathway Information Via Gene Expression Data

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

Young, M; Craft, D

Purpose: To develop an efficient, pathway-based classification system using network biology statistics to assist in patient-specific response predictions to radiation and drug therapies across multiple cancer types. Methods: We developed PICS (Pathway Informed Classification System), a novel two-step cancer classification algorithm. In PICS, a matrix m of mRNA expression values for a patient cohort is collapsed into a matrix p of biological pathways. The entries of p, which we term pathway scores, are obtained from either principal component analysis (PCA), normal tissue centroid (NTC), or gene expression deviation (GED). The pathway score matrix is clustered using both k-means and hierarchicalmore » clustering, and a clustering is judged by how well it groups patients into distinct survival classes. The most effective pathway scoring/clustering combination, per clustering p-value, thus generates various ‘signatures’ for conventional and functional cancer classification. Results: PICS successfully regularized large dimension gene data, separated normal and cancerous tissues, and clustered a large patient cohort spanning six cancer types. Furthermore, PICS clustered patient cohorts into distinct, statistically-significant survival groups. For a suboptimally-debulked ovarian cancer set, the pathway-classified Kaplan-Meier survival curve (p = .00127) showed significant improvement over that of a prior gene expression-classified study (p = .0179). For a pancreatic cancer set, the pathway-classified Kaplan-Meier survival curve (p = .00141) showed significant improvement over that of a prior gene expression-classified study (p = .04). Pathway-based classification confirmed biomarkers for the pyrimidine, WNT-signaling, glycerophosphoglycerol, beta-alanine, and panthothenic acid pathways for ovarian cancer. Despite its robust nature, PICS requires significantly less run time than current pathway scoring methods. Conclusion: This work validates the PICS method to improve cancer classification using biological pathways. Patients are classified with greater specificity and physiological relevance as compared to current gene-specific approaches. Focus now moves to utilizing PICS for pan-cancer patient-specific treatment response prediction.« less

Designing a Classification System for Internet Offenders: Doing Cognitive Distortions

ERIC Educational Resources Information Center

Hundersmarck, Steven F.; Durkin, Keith F.; Delong, Ronald L.

2007-01-01

Televised features such as NBC's "To Catch a Predator" have highlighted the growing problem posed by Internet sexual predators. This paper reports on the authors' attempts in designing a classification system for Internet offenders. The classification system was designed based on existing theory, understanding the nature of Internet offenders and…

78 FR 64925 - Request for Comments on Proposed Elimination of Patents Search Templates

Federal Register 2010, 2011, 2012, 2013, 2014

2013-10-30

... is a detailed, collaborative, and dynamic system that will enable patent examiners and the public to... launched in January 2013. CPC is a detailed, dynamic classification system that is based on the IPC and... updating. Further, the USPTO launched a new classification system, the Cooperative Patent Classification...

Total motile sperm count: a better indicator for the severity of male factor infertility than the WHO sperm classification system.

PubMed

Hamilton, J A M; Cissen, M; Brandes, M; Smeenk, J M J; de Bruin, J P; Kremer, J A M; Nelen, W L D M; Hamilton, C J C M

2015-05-01

Does the prewash total motile sperm count (TMSC) have a better predictive value for spontaneous ongoing pregnancy (SOP) than the World Health Organization (WHO) classification system? The prewash TMSC shows a better correlation with the spontaneous ongoing pregnancy rate (SOPR) than the WHO 2010 classification system. According to the WHO classification system, an abnormal semen analysis can be diagnosed as oligozoospermia, astenozoospermia, teratozoospermia or combinations of these and azoospermia. This classification is based on the fifth percentile cut-off values of a cohort of 1953 men with proven fertility. Although this classification suggests accuracy, the relevance for the prognosis of an infertile couple and the choice of treatment is questionable. The TMSC is obtained by multiplying the sample volume by the density and the percentage of A and B motility spermatozoa. We analyzed data from a longitudinal cohort study among unselected infertile couples who were referred to three Dutch hospitals between January 2002 and December 2006. Of the total cohort of 2476 infertile couples, only the couples with either male infertility as a single diagnosis or unexplained infertility were included (n = 1177) with a follow-up period of 3 years. In all couples a semen analysis was performed. Based on the best semen analysis if more tests were performed, couples were grouped according to the WHO classification system and the TMSC range, as described in the Dutch national guidelines for male infertility. The primary outcome measure was the SOPR, which occurred before, during or after treatments, including expectant management, intrauterine insemination, in vitro fertilization or intracytoplasmic sperm injection. After adjustment for the confounding factors (female and male age, duration and type of infertility and result of the postcoital test) the odd ratios (ORs) for risk of SOP for each WHO and TMSC group were calculated. The couples with unexplained infertility were used as reference. A total of 514 couples did and 663 couples did not achieve a SOP. All WHO groups have a lower SOPR compared with the unexplained group (ORs varying from 0.136 to 0.397). Comparing the couples within the abnormal WHO groups, there are no significant differences in SOPR, except when oligoasthenoteratozoospermia is compared with asthenozoospermia [OR 0.501 (95% CI 0.311-0.809)] and teratozoospermia [OR 0.499 (95% CI: 0.252-0.988)], and oligoasthenozoospermia is compared with asthenozoospermia [OR 0.572 (95% CI: 0.373-0.877)]. All TMSC groups have a significantly lower SOPR compared with the unexplained group (ORs varying from 0.171 to 0.461). Couples with a TMSC of <1 × 10(6) and 1-5 × 10(6) have significantly lower SOPR compared with couples with a TMSC of 5-10 × 10(6) [respectively, OR 0.371 (95% CI: 0.215-0.64) and OR 0.505 (95% CI: 0.307-0.832)]. To include all SOPs during the follow-up period of 3 years, couples were not censured at the start of treatment. Roughly, three prognostic groups can be discerned: couples with a TMSC <5, couples with a TMSC between 5 and 20 and couples with a TMSC of more than 20 × 10(6) spermatozoa. We suggest using TMSC as the method of choice to express severity of male infertility. None. © The Author 2015. Published by Oxford University Press on behalf of the European Society of Human Reproduction and Embryology. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Adverse events following cervical manipulative therapy: consensus on classification among Dutch medical specialists, manual therapists, and patients.

PubMed

Kranenburg, Hendrikus A; Lakke, Sandra E; Schmitt, Maarten A; Van der Schans, Cees P

2017-12-01

To obtain consensus-based agreement on a classification system of adverse events (AE) following cervical spinal manipulation. The classification system should be comprised of clear definitions, include patients' and clinicians' perspectives, and have an acceptable number of categories. Design : A three-round Delphi study. Participants : Thirty Dutch participants (medical specialists, manual therapists, and patients) participated in an online survey. Procedure : Participants inventoried AE and were asked about their preferences for either a three- or a four-category classification system. The identified AE were classified by two analysts following the International Classification of Functioning, Disability and Health (ICF), and the International Classification of Diseases and Related Health Problems (ICD-10). Participants were asked to classify the severity for all AE in relation to the time duration. Consensus occurred in a three-category classification system. There was strong consensus for 16 AE in all severities (no, minor, and major AE) and all three time durations [hours, days, weeks]. The 16 AE included anxiety, flushing, skin rash, fainting, dizziness, coma, altered sensation, muscle tenderness, pain, increased pain during movement, radiating pain, dislocation, fracture, transient ischemic attack, stroke, and death. Mild to strong consensus was reached for 13 AE. A consensus-based classification system of AE is established which includes patients' and clinicians' perspectives and has three categories. The classification comprises a precise description of potential AE in accordance with internationally accepted classifications. After international validation, clinicians and researchers may use this AE classification system to report AE in clinical practice and research.

The new intra-articular calcaneal fracture classification system in term of sustentacular fragment configurations and incorporation of posterior calcaneal facet fractures with fracture components of the calcaneal body.

PubMed

Harnroongroj, Thossart; Harnroongroj, Thos; Suntharapa, Thongchai; Arunakul, Marut

2016-10-01

The aim of this study was to develop a new calcaneal fracture classification system which will consider sustentacular fragment configuration and relation of posterior calcaneal facet to calcaneal body. The new classification system used sustentacular fragment configuration and relation of posterior calcaneal facet fracture with fracture components of calcaneal body as key aspects of main types and subtypes. Between 2000 and 2014, 126 intraarticular calcaneal fractures were classified according to the new classification system by using computed tomography images. The new classification system was studied in term of reliability, correlation to choices of treatment, implant fixation and quality of fracture reduction. Types of sustentacular fragment comprised type A, B and C. Type A sustentacular fragment included sustentacular tali containing middle calcaneal facet. In Type B and C fractures sustentacular fragment included medial aspect and entire posterior calcaneal facet as a single unit, respectively. The fractures with type A, B and C sustentacular fragments were classified as main type A, B and C intra-articular calcaneal fractures. The main type A and B comprised 4 subtypes. Subtypes A1, A3, B1, and B3 associated with avulsion and bending fragments of calcaneal body. Subtype A2, B2, and B4 associated with burst calcaneal body. Subtype B4 was not found in the study. Main type C had no subtype and associated with burst calcaneal body. The data showed good reliability. The study showed that our new intra-articular calcaneal fracture classification system correlates to choices of treatment, implant fixation and quality of fracture reduction. Level IV, Study of Diagnostic Test. Copyright © 2016 Turkish Association of Orthopaedics and Traumatology. Production and hosting by Elsevier B.V. All rights reserved.

Evaluation of the Melanocytic Pathology Assessment Tool and Hierarchy for Diagnosis (MPATH-Dx) classification scheme for diagnosis of cutaneous melanocytic neoplasms: Results from the International Melanoma Pathology Study Group.

PubMed

Lott, Jason P; Elmore, Joann G; Zhao, Ge A; Knezevich, Stevan R; Frederick, Paul D; Reisch, Lisa M; Chu, Emily Y; Cook, Martin G; Duncan, Lyn M; Elenitsas, Rosalie; Gerami, Pedram; Landman, Gilles; Lowe, Lori; Messina, Jane L; Mihm, Martin C; van den Oord, Joost J; Rabkin, Michael S; Schmidt, Birgitta; Shea, Christopher R; Yun, Sook Jung; Xu, George X; Piepkorn, Michael W; Elder, David E; Barnhill, Raymond L

2016-08-01

Pathologists use diverse terminology when interpreting melanocytic neoplasms, potentially compromising quality of care. We sought to evaluate the Melanocytic Pathology Assessment Tool and Hierarchy for Diagnosis (MPATH-Dx) scheme, a 5-category classification system for melanocytic lesions. Participants (n = 16) of the 2013 International Melanoma Pathology Study Group Workshop provided independent case-level diagnoses and treatment suggestions for 48 melanocytic lesions. Individual diagnoses (including, when necessary, least and most severe diagnoses) were mapped to corresponding MPATH-Dx classes. Interrater agreement and correlation between MPATH-Dx categorization and treatment suggestions were evaluated. Most participants were board-certified dermatopathologists (n = 15), age 50 years or older (n = 12), male (n = 9), based in the United States (n = 11), and primary academic faculty (n = 14). Overall, participants generated 634 case-level diagnoses with treatment suggestions. Mean weighted kappa coefficients for diagnostic agreement after MPATH-Dx mapping (assuming least and most severe diagnoses, when necessary) were 0.70 (95% confidence interval 0.68-0.71) and 0.72 (95% confidence interval 0.71-0.73), respectively, whereas correlation between MPATH-Dx categorization and treatment suggestions was 0.91. This was a small sample size of experienced pathologists in a testing situation. Varying diagnostic nomenclature can be classified into a concise hierarchy using the MPATH-Dx scheme. Further research is needed to determine whether this classification system can facilitate diagnostic concordance in general pathology practice and improve patient care. Copyright © 2016 American Academy of Dermatology, Inc. Published by Elsevier Inc. All rights reserved.

Invasive endocervical adenocarcinoma: proposal for a new pattern-based classification system with significant clinical implications: a multi-institutional study.

PubMed

Diaz De Vivar, Andrea; Roma, Andres A; Park, Kay J; Alvarado-Cabrero, Isabel; Rasty, Golnar; Chanona-Vilchis, Jose G; Mikami, Yoshiki; Hong, Sung R; Arville, Brent; Teramoto, Norihiro; Ali-Fehmi, Rouba; Rutgers, Joanne K L; Tabassum, Farah; Barbuto, Denise; Aguilera-Barrantes, Irene; Shaye-Brown, Alexandra; Daya, Dean; Silva, Elvio G

2013-11-01

The management of endocervical adenocarcinoma is largely based on tumor size and depth of invasion (DOI); however, DOI is difficult to measure accurately. The surgical treatment includes resection of regional lymph nodes, even though most lymph nodes are negative and lymphadenectomies can cause significant morbidity. We have investigated alternative parameters to better identify patients at risk of node metastases. Cases of invasive endocervical adenocarcinoma from 12 institutions were reviewed, and clinical/pathologic features assessed: patients' age, tumor size, DOI, differentiation, lymph-vascular invasion, lymph node metastases, recurrences, and stage. Cases were classified according to a new pattern-based system into Pattern A (well-demarcated glands), B (early destructive stromal invasion arising from well-demarcated glands), and C (diffuse destructive invasion). In total, 352 cases (FIGO Stages I-IV) were identified. Patients' age ranged from 20 to 83 years (mean 45), DOI ranged from 0.2 to 27 mm (mean 6.73), and lymph-vascular invasion was present in 141 cases. Forty-nine (13.9%) demonstrated lymph node metastases. Using this new system, 73 patients (20.7%) with Pattern A tumors (all Stage I) were identified. None had lymph node metastases and/or recurrences. Ninety patients (25.6%) had Pattern B tumors, of which 4 (4.4%) had positive nodes; whereas 189 (53.7%) had Pattern C tumors, of which 45 (23.8%) had metastatic nodes. The proposed classification system can spare 20.7% of patients (Pattern A) of unnecessary lymphadenectomy. Patients with Pattern B rarely present with positive nodes. An aggressive approach is justified in patients with Pattern C. This classification system is simple, easy to apply, and clinically significant.

German guidelines for the diagnosis and therapy of localized scleroderma.

PubMed

Kreuter, Alexander; Krieg, Thomas; Worm, Margitta; Wenzel, Jörg; Moinzadeh, Pia; Kuhn, Annegret; Aberer, Elisabeth; Scharffetter-Kochanek, Karin; Horneff, Gerd; Reil, Emma; Weberschock, Tobias; Hunzelmann, Nicolas

2016-02-01

Localized scleroderma designates a heterogeneous group of sclerotic skin disorders. Depending on the subtype, severity, and site affected, adjacent structures such as adipose tissue, muscles, joints, and bones may be involved. This is an update of the existing German AWMF (Association of the Scientific Medical Societies in Germany) guidelines (classification: S2k). These guidelines provide an overview of the definition, epidemiology, classification, pathogenesis, laboratory workup, histopathology, clinical scoring systems, as well as imaging and device-based workup of localized scleroderma. Moreover, consensus-based recommendations are given on the management of localized scleroderma depending on its clinical subtype. Treatment recommendations are presented in a therapeutic algorithm. No financial support was given by any pharmaceutical company. The guidelines are valid until July 2019. © 2016 The Authors | Journal compilation © Blackwell Verlag GmbH, Berlin.

A multilayered approach for the analysis of perinatal mortality using different classification systems.

PubMed

Gordijn, Sanne J; Korteweg, Fleurisca J; Erwich, Jan Jaap H M; Holm, Jozien P; van Diem, Mariet Th; Bergman, Klasien A; Timmer, Albertus

2009-06-01

Many classification systems for perinatal mortality are available, all with their own strengths and weaknesses: none of them has been universally accepted. We present a systematic multilayered approach for the analysis of perinatal mortality based on information related to the moment of death, the conditions associated with death and the underlying cause of death, using a combination of representatives of existing classification systems. We compared the existing classification systems regarding their definition of the perinatal period, level of complexity, inclusion of maternal, foetal and/or placental factors and whether they focus at a clinical or pathological viewpoint. Furthermore, we allocated the classification systems to one of three categories: 'when', 'what' or 'why', dependent on whether the allocation of the individual cases of perinatal mortality is based on the moment of death ('when'), the clinical conditions associated with death ('what'), or the underlying cause of death ('why'). A multilayered approach for the analysis and classification of perinatal mortality is possible by using combinations of existing systems; for example the Wigglesworth or Nordic Baltic ('when'), ReCoDe ('what') and Tulip ('why') classification systems. This approach is useful not only for in depth analysis of perinatal mortality in the developed world but also for analysis of perinatal mortality in the developing countries, where resources to investigate death are often limited.

Recognizing systemic sclerosis: comparative analysis of various sets of classification criteria

PubMed Central

Romanowska-Próchnicka, Katarzyna; Olesińska, Marzena

2016-01-01

Systemic sclerosis is a complex disease characterized by autoimmunity, vasculopathy and tissue fibrosis. Although most patients present with some degree of skin sclerosis, which is a distinguishing hallmark, the clinical presentation vary greatly complicating the diagnosis. In this regard, new classification criteria were jointly published in 2013 by American College of Rheumatology (ACR) and European League Against Rheumatism (EULAR). A recent major development in the classification criteria is improved sensitivity, particularly for detecting early disease. The new criteria allow more cases to be classified as having systemic sclerosis (SSc), which leads to earlier treatment. Moreover it is clinically beneficial in preventing the disease progression with its irreversible fibrosis and organ damage. The aim of this review is to give insight into new classification criteria and current trends in the diagnosis of systemic sclerosis. PMID:28115780

Industrial robots: Handbook

NASA Astrophysics Data System (ADS)

Kozyrev, Iu. G.

Topics covered include terms, definitions, and classification; operator-directed manipulators; autooperators as used in automated pressure casting; construction and application of industrial robots; and the operating bases of automated systems. Attention is given to adaptive and interactive robots; gripping mechanisms; applications to foundary production, press-forging plants, heat treatment, welding, and assembly operations. A review of design recommendations includes a determination of fundamental structural and technological indicators for industrial robots and a consideration of drive mechanisms.

A Proposal for a Dimensional Classification System Based on the Shared Features of the "DSM-IV" Anxiety and Mood Disorders: Implications for Assessment and Treatment

ERIC Educational Resources Information Center

Brown, Timothy A.; Barlow, David H.

2009-01-01

A wealth of evidence attests to the extensive current and lifetime diagnostic comorbidity of the "Diagnostic and Statistical Manual of Mental Disorders" (4th ed., "DSM-IV") anxiety and mood disorders. Research has shown that the considerable cross-sectional covariation of "DSM-IV" emotional disorders is accounted for by common higher order…

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.

Conceptual-driven classification for coding advise in health insurance reimbursement.

PubMed

Li, Sheng-Tun; Chen, Chih-Chuan; Huang, Fernando

2011-01-01

With the non-stop increases in medical treatment fees, the economic survival of a hospital in Taiwan relies on the reimbursements received from the Bureau of National Health Insurance, which in turn depend on the accuracy and completeness of the content of the discharge summaries as well as the correctness of their International Classification of Diseases (ICD) codes. The purpose of this research is to enforce the entire disease classification framework by supporting disease classification specialists in the coding process. This study developed an ICD code advisory system (ICD-AS) that performed knowledge discovery from discharge summaries and suggested ICD codes. Natural language processing and information retrieval techniques based on Zipf's Law were applied to process the content of discharge summaries, and fuzzy formal concept analysis was used to analyze and represent the relationships between the medical terms identified by MeSH. In addition, a certainty factor used as reference during the coding process was calculated to account for uncertainty and strengthen the credibility of the outcome. Two sets of 360 and 2579 textual discharge summaries of patients suffering from cerebrovascular disease was processed to build up ICD-AS and to evaluate the prediction performance. A number of experiments were conducted to investigate the impact of system parameters on accuracy and compare the proposed model to traditional classification techniques including linear-kernel support vector machines. The comparison results showed that the proposed system achieves the better overall performance in terms of several measures. In addition, some useful implication rules were obtained, which improve comprehension of the field of cerebrovascular disease and give insights to the relationships between relevant medical terms. Our system contributes valuable guidance to disease classification specialists in the process of coding discharge summaries, which consequently brings benefits in aspects of patient, hospital, and healthcare system. Copyright © 2010 Elsevier B.V. All rights reserved.

Simultaneous detection and classification of breast masses in digital mammograms via a deep learning YOLO-based CAD system.

PubMed

Al-Masni, Mohammed A; Al-Antari, Mugahed A; Park, Jeong-Min; Gi, Geon; Kim, Tae-Yeon; Rivera, Patricio; Valarezo, Edwin; Choi, Mun-Taek; Han, Seung-Moo; Kim, Tae-Seong

2018-04-01

Automatic detection and classification of the masses in mammograms are still a big challenge and play a crucial role to assist radiologists for accurate diagnosis. In this paper, we propose a novel Computer-Aided Diagnosis (CAD) system based on one of the regional deep learning techniques, a ROI-based Convolutional Neural Network (CNN) which is called You Only Look Once (YOLO). Although most previous studies only deal with classification of masses, our proposed YOLO-based CAD system can handle detection and classification simultaneously in one framework. The proposed CAD system contains four main stages: preprocessing of mammograms, feature extraction utilizing deep convolutional networks, mass detection with confidence, and finally mass classification using Fully Connected Neural Networks (FC-NNs). In this study, we utilized original 600 mammograms from Digital Database for Screening Mammography (DDSM) and their augmented mammograms of 2,400 with the information of the masses and their types in training and testing our CAD. The trained YOLO-based CAD system detects the masses and then classifies their types into benign or malignant. Our results with five-fold cross validation tests show that the proposed CAD system detects the mass location with an overall accuracy of 99.7%. The system also distinguishes between benign and malignant lesions with an overall accuracy of 97%. Our proposed system even works on some challenging breast cancer cases where the masses exist over the pectoral muscles or dense regions. Copyright © 2018 Elsevier B.V. All rights reserved.

Classification of current anticancer immunotherapies

PubMed Central

Vacchelli, Erika; Pedro, José-Manuel Bravo-San; Buqué, Aitziber; Senovilla, Laura; Baracco, Elisa Elena; Bloy, Norma; Castoldi, Francesca; Abastado, Jean-Pierre; Agostinis, Patrizia; Apte, Ron N.; Aranda, Fernando; Ayyoub, Maha; Beckhove, Philipp; Blay, Jean-Yves; Bracci, Laura; Caignard, Anne; Castelli, Chiara; Cavallo, Federica; Celis, Estaban; Cerundolo, Vincenzo; Clayton, Aled; Colombo, Mario P.; Coussens, Lisa; Dhodapkar, Madhav V.; Eggermont, Alexander M.; Fearon, Douglas T.; Fridman, Wolf H.; Fučíková, Jitka; Gabrilovich, Dmitry I.; Galon, Jérôme; Garg, Abhishek; Ghiringhelli, François; Giaccone, Giuseppe; Gilboa, Eli; Gnjatic, Sacha; Hoos, Axel; Hosmalin, Anne; Jäger, Dirk; Kalinski, Pawel; Kärre, Klas; Kepp, Oliver; Kiessling, Rolf; Kirkwood, John M.; Klein, Eva; Knuth, Alexander; Lewis, Claire E.; Liblau, Roland; Lotze, Michael T.; Lugli, Enrico; Mach, Jean-Pierre; Mattei, Fabrizio; Mavilio, Domenico; Melero, Ignacio; Melief, Cornelis J.; Mittendorf, Elizabeth A.; Moretta, Lorenzo; Odunsi, Adekunke; Okada, Hideho; Palucka, Anna Karolina; Peter, Marcus E.; Pienta, Kenneth J.; Porgador, Angel; Prendergast, George C.; Rabinovich, Gabriel A.; Restifo, Nicholas P.; Rizvi, Naiyer; Sautès-Fridman, Catherine; Schreiber, Hans; Seliger, Barbara; Shiku, Hiroshi; Silva-Santos, Bruno; Smyth, Mark J.; Speiser, Daniel E.; Spisek, Radek; Srivastava, Pramod K.; Talmadge, James E.; Tartour, Eric; Van Der Burg, Sjoerd H.; Van Den Eynde, Benoît J.; Vile, Richard; Wagner, Hermann; Weber, Jeffrey S.; Whiteside, Theresa L.; Wolchok, Jedd D.; Zitvogel, Laurence; Zou, Weiping

2014-01-01

During the past decades, anticancer immunotherapy has evolved from a promising therapeutic option to a robust clinical reality. Many immunotherapeutic regimens are now approved by the US Food and Drug Administration and the European Medicines Agency for use in cancer patients, and many others are being investigated as standalone therapeutic interventions or combined with conventional treatments in clinical studies. Immunotherapies may be subdivided into “passive” and “active” based on their ability to engage the host immune system against cancer. Since the anticancer activity of most passive immunotherapeutics (including tumor-targeting monoclonal antibodies) also relies on the host immune system, this classification does not properly reflect the complexity of the drug-host-tumor interaction. Alternatively, anticancer immunotherapeutics can be classified according to their antigen specificity. While some immunotherapies specifically target one (or a few) defined tumor-associated antigen(s), others operate in a relatively non-specific manner and boost natural or therapy-elicited anticancer immune responses of unknown and often broad specificity. Here, we propose a critical, integrated classification of anticancer immunotherapies and discuss the clinical relevance of these approaches. PMID:25537519

MODEL-BASED CLUSTERING FOR CLASSIFICATION OF AQUATIC SYSTEMS AND DIAGNOSIS OF ECOLOGICAL STRESS

EPA Science Inventory

Clustering approaches were developed using the classification likelihood, the mixture likelihood, and also using a randomization approach with a model index. Using a clustering approach based on the mixture and classification likelihoods, we have developed an algorithm that...

HYDROLOGIC REGIME CLASSIFICATION OF LAKE MICHIGAN COASTAL RIVERINE WETLANDS BASED ON WATERSHED CHARACTERISTICS

EPA Science Inventory

Classification of wetlands systems is needed not only to establish reference condition, but also to predict the relative sensitivity of different wetland classes. In the current study, we examined the potential for ecoregion- versus flow-based classification strategies to explain...

Promoting new concepts of skincare via skinomics and systems biology-From traditional skincare and efficacy-based skincare to precision skincare.

PubMed

Jiang, Biao; Jia, Yan; He, Congfen

2018-05-11

Traditional skincare involves the subjective classification of skin into 4 categories (oily, dry, mixed, and neutral) prior to skin treatment. Following the development of noninvasive methods in skin and skin imaging technology, scientists have developed efficacy-based skincare products based on the physiological characteristics of skin under different conditions. Currently, the emergence of skinomics and systems biology has facilitated the development of precision skincare. In this article, the evolution of skincare based on the physiological states of the skin (from traditional skincare and efficacy-based skincare to precision skincare) is described. In doing so, we highlight skinomics and systems biology, with particular emphasis on the importance of skin lipidomics and microbiomes in precision skincare. The emerging trends of precision skincare are anticipated. © 2018 Wiley Periodicals, Inc.

Standardizing Foot-Type Classification Using Arch Index Values

PubMed Central

Weil, Rich; de Boer, Emily

2012-01-01

ABSTRACT Purpose: The lack of a reliable classification standard for foot type makes drawing conclusions from existing research and clinical decisions difficult, since different foot types may move and respond to treatment differently. The purpose of this study was to determine interrater agreement for foot-type classification based on photo-box-derived arch index values. Method: For this correlational study with two raters, a sample of 11 healthy volunteers with normal to obese body mass indices was recruited from both a community weight-loss programme and a programme in physical therapy. Arch index was calculated using AutoCAD software from footprint photographs obtained via mirrored photo-box. Classification as high-arched, normal, or low-arched foot type was based on arch index values. Reliability of the arch index was determined with intra-class correlations; agreement on foot-type classification was determined using quadratic weighted kappa (κw). Results: Average arch index was 0.215 for one tester and 0.219 for the second tester, with an overall range of 0.017 to 0.370. Both testers classified 6 feet as low-arched, 9 feet as normal, and 7 feet as high-arched. Interrater reliability for the arch index was ICC=0.90; interrater agreement for foot-type classification was κw=0.923. Conclusions: Classification of foot type based on arch index values derived from plantar footprint photographs obtained via mirrored photo-box showed excellent reliability in people with varying BMI. Foot-type classification may help clinicians and researchers subdivide sample populations to better differentiate mobility, gait, or treatment effects among foot types. PMID:23729964

It is time to bring borderline intellectual functioning back into the main fold of classification systems

PubMed Central

Wieland, Jannelien; Zitman, Frans G.

2016-01-01

Borderline intellectual functioning is an important and frequently unrecognised comorbid condition relevant to the diagnosis and treatment of any and all psychiatric disorders. In the DSM-IV-TR, it is defined by IQ in the 71–84 range. In DSM-5, IQ boundaries are no longer part of the classification, leaving the concept without a clear definition. This modification is one of the least highlighted changes in DSM-5. In this article we describe the history of the classification of borderline intellectual functioning. We provide information about it and on the importance of placing it in the right context and in the right place in future DSM editions and other classification systems such as the International Classification of Diseases. PMID:27512590

Osteochondroma of the mandibular condyle: a classification system based on computed tomographic appearances.

PubMed

Chen, Min-jie; Yang, Chi; Qiu, Ya-ting; Zhou, Qin; Huang, Dong; Shi, Hui-min

2014-09-01

The objectives of this study were to introduce the classification of osteochondroma of the mandibular condyle based on computed tomographic images and to present our treatment experiences. From January 2002 and December 2012, a total of 61 patients with condylar osteochondroma were treated in our division. Both clinical and radiologic aspects were reviewed. The average follow-up period was 24.3 months with a range of 6 to 120 months. Two types of condylar osteochondroma were presented: type 1 (protruding expansion) in 50 patients (82.0%) and type 2 (globular expansion) in 11 patients (18.0%). Type 1 condylar osteochondroma presented 5 forms: anterior/anteromedial (58%), posterior/posteromedial (6%), medial (16%), lateral (6%), and gigantic (14%). Local resection was performed on patients with type 1 condylar osteochondroma. Subtotal condylectomy/total condylectomy using costochondral graft reconstruction with/without orthognathic surgeries was performed on patients with type 2 condylar osteochondroma. During the follow-up period, tumor reformation, condyle absorption, and new deformity were not detected. The patients almost reattained facial symmetry. Preoperative classification based on computed tomographic images will help surgeons to choose the suitable surgical procedure to treat the condylar osteochondroma.

The research on medical image classification algorithm based on PLSA-BOW model.

PubMed

Cao, C H; Cao, H L

2016-04-29

With the rapid development of modern medical imaging technology, medical image classification has become more important for medical diagnosis and treatment. To solve the existence of polysemous words and synonyms problem, this study combines the word bag model with PLSA (Probabilistic Latent Semantic Analysis) and proposes the PLSA-BOW (Probabilistic Latent Semantic Analysis-Bag of Words) model. In this paper we introduce the bag of words model in text field to image field, and build the model of visual bag of words model. The method enables the word bag model-based classification method to be further improved in accuracy. The experimental results show that the PLSA-BOW model for medical image classification can lead to a more accurate classification.

Assessment of fatty degeneration of the gluteal muscles in patients with THA using MRI: reliability and accuracy of the Goutallier and quartile classification systems.

PubMed

Engelken, Florian; Wassilew, Georgi I; Köhlitz, Torsten; Brockhaus, Sebastian; Hamm, Bernd; Perka, Carsten; Diederichs, und Gerd

2014-01-01

The purpose of this study was to quantify the performance of the Goutallier classification for assessing fatty degeneration of the gluteus muscles from magnetic resonance (MR) images and to compare its performance to a newly proposed system. Eighty-four hips with clinical signs of gluteal insufficiency and 50 hips from asymptomatic controls were analyzed using a standard classification system (Goutallier) and a new scoring system (Quartile). Interobserver reliability and intraobserver repeatability were determined, and accuracy was assessed by comparing readers' scores with quantitative estimates of the proportion of intramuscular fat based on MR signal intensities (gold standard). The existing Goutallier classification system and the new Quartile system performed equally well in assessing fatty degeneration of the gluteus muscles, both showing excellent levels of interrater and intrarater agreement. While the Goutallier classification system has the advantage of being widely known, the benefit of the Quartile system is that it is based on more clearly defined grades of fatty degeneration. Copyright © 2014 Elsevier Inc. All rights reserved.

Fast clustering algorithm for large ECG data sets based on CS theory in combination with PCA and K-NN methods.

PubMed

Balouchestani, Mohammadreza; Krishnan, Sridhar

2014-01-01

Long-term recording of Electrocardiogram (ECG) signals plays an important role in health care systems for diagnostic and treatment purposes of heart diseases. Clustering and classification of collecting data are essential parts for detecting concealed information of P-QRS-T waves in the long-term ECG recording. Currently used algorithms do have their share of drawbacks: 1) clustering and classification cannot be done in real time; 2) they suffer from huge energy consumption and load of sampling. These drawbacks motivated us in developing novel optimized clustering algorithm which could easily scan large ECG datasets for establishing low power long-term ECG recording. In this paper, we present an advanced K-means clustering algorithm based on Compressed Sensing (CS) theory as a random sampling procedure. Then, two dimensionality reduction methods: Principal Component Analysis (PCA) and Linear Correlation Coefficient (LCC) followed by sorting the data using the K-Nearest Neighbours (K-NN) and Probabilistic Neural Network (PNN) classifiers are applied to the proposed algorithm. We show our algorithm based on PCA features in combination with K-NN classifier shows better performance than other methods. The proposed algorithm outperforms existing algorithms by increasing 11% classification accuracy. In addition, the proposed algorithm illustrates classification accuracy for K-NN and PNN classifiers, and a Receiver Operating Characteristics (ROC) area of 99.98%, 99.83%, and 99.75% respectively.

Lauren classification and individualized chemotherapy in gastric cancer.

PubMed

Ma, Junli; Shen, Hong; Kapesa, Linda; Zeng, Shan

2016-05-01

Gastric cancer is one of the most common malignancies worldwide. During the last 50 years, the histological classification of gastric carcinoma has been largely based on Lauren's criteria, in which gastric cancer is classified into two major histological subtypes, namely intestinal type and diffuse type adenocarcinoma. This classification was introduced in 1965, and remains currently widely accepted and employed, since it constitutes a simple and robust classification approach. The two histological subtypes of gastric cancer proposed by the Lauren classification exhibit a number of distinct clinical and molecular characteristics, including histogenesis, cell differentiation, epidemiology, etiology, carcinogenesis, biological behaviors and prognosis. Gastric cancer exhibits varied sensitivity to chemotherapy drugs and significant heterogeneity; therefore, the disease may be a target for individualized therapy. The Lauren classification may provide the basis for individualized treatment for advanced gastric cancer, which is increasingly gaining attention in the scientific field. However, few studies have investigated individualized treatment that is guided by pathological classification. The aim of the current review is to analyze the two major histological subtypes of gastric cancer, as proposed by the Lauren classification, and to discuss the implications of this for personalized chemotherapy.

A review of classification algorithms for EEG-based brain-computer interfaces.

PubMed

Lotte, F; Congedo, M; Lécuyer, A; Lamarche, F; Arnaldi, B

2007-06-01

In this paper we review classification algorithms used to design brain-computer interface (BCI) systems based on electroencephalography (EEG). We briefly present the commonly employed algorithms and describe their critical properties. Based on the literature, we compare them in terms of performance and provide guidelines to choose the suitable classification algorithm(s) for a specific BCI.

Psychological Features and Their Relationship to Movement-Based Subgroups in People Living With Low Back Pain.

PubMed

Karayannis, Nicholas V; Jull, Gwendolen A; Nicholas, Michael K; Hodges, Paul W

2018-01-01

To determine the distribution of higher psychological risk features within movement-based subgroups for people with low back pain (LBP). Cross-sectional observational study. Participants were recruited from physiotherapy clinics and community advertisements. Measures were collected at a university outpatient-based physiotherapy clinic. People (N=102) seeking treatment for LBP. Participants were subgrouped according to 3 classification schemes: Mechanical Diagnosis and Treatment (MDT), Treatment-Based Classification (TBC), and O'Sullivan Classification (OSC). Questionnaires were used to categorize low-, medium-, and high-risk features based on depression, anxiety, and stress (Depression, Anxiety, and Stress Scale-21 Items); fear avoidance (Fear-Avoidance Beliefs Questionnaire); catastrophizing and coping (Pain-Related Self-Symptoms Scale); and self-efficacy (Pain Self-Efficacy Questionnaire). Psychological risk profiles were compared between movement-based subgroups within each scheme. Scores across all questionnaires revealed that most patients had low psychological risk profiles, but there were instances of higher (range, 1%-25%) risk profiles within questionnaire components. The small proportion of individuals with higher psychological risk scores were distributed between subgroups across TBC, MDT, and OSC schemes. Movement-based subgrouping alone cannot inform on individuals with higher psychological risk features. Copyright © 2017 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

The classification based on intrahepatic portal system for congenital portosystemic shunts.

PubMed

Kanazawa, Hiroyuki; Nosaka, Shunsuke; Miyazaki, Osamu; Sakamoto, Seisuke; Fukuda, Akinari; Shigeta, Takanobu; Nakazawa, Atsuko; Kasahara, Mureo

2015-04-01

Liver transplantation was previously indicated as a curative operation for congenital absence of portal vein. Recent advances in radiological interventional techniques can precisely visualize the architecture of the intrahepatic portal system (IHPS). Therefore, the therapeutic approach for congenital portosystemic shunt (CPS) needs to be reevaluated from a viewpoint of radiological appearances. The aim of this study was to propose the IHPS classification which could explain the pathophysiological characteristics and play a complementary role of a therapeutic approach and management for CPS. Nineteen patients with CPS were retrospectively reviewed. The median age at diagnosis was 6.8 years old. Eighteen of these patients underwent angiography with a shunt occlusion test and were classified based of the severity of the hypoplasia of IHPS. The eighteen cases who could undergo the shunt occlusion test were classified into mild (n=7), moderate (n=6) and severe types (n=5) according to the IHPS classification. The IHPS classification correlated with the portal venous pressure under shunt occlusion, the histopathological findings, postoperative portal venous flow and liver regeneration. Shunt closure resulted in dramatic improvement in the laboratory data and subclinical encephalopathy. Two patients with the severe type suffered from sepsis associated with portal hypertension after treatment, and from the portal flow steal phenomenon because of the development of unexpected collateral vessels. The patients with the severe type had a high risk of postoperative complications after shunt closure in one step, even if the PVP was relatively low during the shunt occlusion test. The IHPS could be visualized by the shunt occlusion test. The IHPS classification reflected the clinicopathological features of CPS, and was useful to determine the therapeutic approach and management for CPS. Copyright © 2015 Elsevier Inc. All rights reserved.

Chinese wine classification system based on micrograph using combination of shape and structure features

NASA Astrophysics Data System (ADS)

Wan, Yi

2011-06-01

Chinese wines can be classification or graded by the micrographs. Micrographs of Chinese wines show floccules, stick and granule of variant shape and size. Different wines have variant microstructure and micrographs, we study the classification of Chinese wines based on the micrographs. Shape and structure of wines' particles in microstructure is the most important feature for recognition and classification of wines. So we introduce a feature extraction method which can describe the structure and region shape of micrograph efficiently. First, the micrographs are enhanced using total variation denoising, and segmented using a modified Otsu's method based on the Rayleigh Distribution. Then features are extracted using proposed method in the paper based on area, perimeter and traditional shape feature. Eight kinds total 26 features are selected. Finally, Chinese wine classification system based on micrograph using combination of shape and structure features and BP neural network have been presented. We compare the recognition results for different choices of features (traditional shape features or proposed features). The experimental results show that the better classification rate have been achieved using the combinational features proposed in this paper.

Periodontitis: Consensus report of workgroup 2 of the 2017 World Workshop on the Classification of Periodontal and Peri-Implant Diseases and Conditions.

PubMed

Papapanou, Panos N; Sanz, Mariano; Buduneli, Nurcan; Dietrich, Thomas; Feres, Magda; Fine, Daniel H; Flemmig, Thomas F; Garcia, Raul; Giannobile, William V; Graziani, Filippo; Greenwell, Henry; Herrera, David; Kao, Richard T; Kebschull, Moritz; Kinane, Denis F; Kirkwood, Keith L; Kocher, Thomas; Kornman, Kenneth S; Kumar, Purnima S; Loos, Bruno G; Machtei, Eli; Meng, Huanxin; Mombelli, Andrea; Needleman, Ian; Offenbacher, Steven; Seymour, Gregory J; Teles, Ricardo; Tonetti, Maurizio S

2018-06-01

A new periodontitis classification scheme has been adopted, in which forms of the disease previously recognized as "chronic" or "aggressive" are now grouped under a single category ("periodontitis") and are further characterized based on a multi-dimensional staging and grading system. Staging is largely dependent upon the severity of disease at presentation as well as on the complexity of disease management, while grading provides supplemental information about biological features of the disease including a history-based analysis of the rate of periodontitis progression; assessment of the risk for further progression; analysis of possible poor outcomes of treatment; and assessment of the risk that the disease or its treatment may negatively affect the general health of the patient. Necrotizing periodontal diseases, whose characteristic clinical phenotype includes typical features (papilla necrosis, bleeding, and pain) and are associated with host immune response impairments, remain a distinct periodontitis category. Endodontic-periodontal lesions, defined by a pathological communication between the pulpal and periodontal tissues at a given tooth, occur in either an acute or a chronic form, and are classified according to signs and symptoms that have direct impact on their prognosis and treatment. Periodontal abscesses are defined as acute lesions characterized by localized accumulation of pus within the gingival wall of the periodontal pocket/sulcus, rapid tissue destruction and are associated with risk for systemic dissemination. © 2018 American Academy of Periodontology and European Federation of Periodontology.

The Alaska vegetation classification.

Treesearch

L.A. Viereck; C.T. Dyrness; A.R. Batten; K.J. Wenzlick

1992-01-01

The Alaska vegetation classification presented here is a comprehensive, statewide system that has been under development since 1976. The classification is based, as much as possible, on the characteristics of the vegetation itself and is designed to categorize existing vegetation, not potential vegetation. A hierarchical system with five levels of resolution is used...

Diagnosis-related groups for stroke in Europe: patient classification and hospital reimbursement in 11 countries.

PubMed

Peltola, Mikko; Quentin, Wilm

2013-01-01

Diagnosis-related groups (DRGs) are increasingly being used for various purposes in many countries. However, there are no studies comparing different DRG systems in the care of stroke. As part of the EuroDRG project, researchers from 11 countries (i.e. Austria, England, Estonia, Finland, France, Germany, Ireland, the Netherlands, Poland, Sweden and Spain) compared how their DRG systems deal with stroke patients. The study aims to assist clinicians and national authorities to optimize their DRG systems. National or regional databases were used to identify hospital cases with a diagnosis of stroke. DRG classification algorithms and indicators of resource consumption were compared for those DRGs that individually represent at least 1% of stroke cases. In addition, standardized case vignettes were defined, and quasi prices according to national DRG-based hospital payment systems were ascertained. European DRG systems vary widely: they classify stroke patients according to different sets of variables (between 1 and 7 classification variables) into diverging numbers of DRGs (between 1 and 10 DRGs). In 6 of the countries more than half of the patients are concentrated within a single DRG. The countries' systems also vary with respect to the evaluation of different kinds of stroke patients. The most complex DRG is considered 3.8 times more resource intensive than an index case in Finland. By contrast, in England, the DRG system does not account for complex cases. Comparisons of quasi prices for the case vignettes show that hypothetical payments for the index case amount to only EUR 907 in Poland but to EUR 7,881 in Ireland. Large variations in the classification of stroke patients raise concerns whether all systems rely on the most appropriate classification variables and whether the DRGs adequately reflect differences in the complexity of treating different groups of patients. Learning from other DRG systems may help in improving the national systems. Clinicians and national DRG authorities should consider how other countries' DRG systems classify stroke patients in order to optimize their DRG system and to ensure fair and appropriate reimbursement. In future, quantitative research is needed to verify whether the most important determinants of cost are considered in different patient classification systems, and whether differences between systems reflect country-specific differences in treatment patterns and, most importantly, what influence they have on patient outcomes. Copyright © 2013 S. Karger AG, Basel.

Cutaneous Lupus Erythematosus: Diagnosis and treatment

PubMed Central

Okon, Lauren G.; Werth, Victoria P.

2013-01-01

Cutaneous lupus erythematosus encompasses a wide range of dermatologic manifestations, which may or may not be associated with the development of systemic disease. Cutaneous lupus is divided into several subtypes, including acute cutaneous lupus erythematosus, subacute cutaneous lupus erythematosus, and chronic cutaneous lupus erythematosus. Chronic cutaneous lupus erythematosus includes discoid lupus erythematosus, lupus erythematosus profundus, chilblain cutaneous lupus, and lupus tumidus. Diagnosis of these diseases requires proper classification of the subtype, through a combination of physical exam, laboratory studies, histology, antibody serology, and occasionally direct immunofluorescence, while ensuring to exclude systemic disease. Treatment of cutaneous lupus consists of patient education on proper sun protection along with appropriate topical and systemic agents. Systemic agents are indicated in cases of widespread, scarring, or treatment-refractory disease. In this review, we discuss issues in classification and diagnosis of the various subtypes of CLE, as well as provide an update on therapeutic management. PMID:24238695

Kyoto global consensus report on Helicobacter pylori gastritis

PubMed Central

Sugano, Kentaro; Tack, Jan; Kuipers, Ernst J; Graham, David Y; El-Omar, Emad M; Miura, Soichiro; Haruma, Ken; Asaka, Masahiro; Uemura, Naomi; Malfertheiner, Peter

2015-01-01

Objective To present results of the Kyoto Global Consensus Meeting, which was convened to develop global consensus on (1) classification of chronic gastritis and duodenitis, (2) clinical distinction of dyspepsia caused by Helicobacter pylori from functional dyspepsia, (3) appropriate diagnostic assessment of gastritis and (4) when, whom and how to treat H. pylori gastritis. Design Twenty-three clinical questions addressing the above-mentioned four domains were drafted for which expert panels were asked to formulate relevant statements. A Delphi method using an anonymous electronic system was adopted to develop the consensus, the level of which was predefined as ≥80%. Final modifications of clinical questions and consensus were achieved at the face-to-face meeting in Kyoto. Results All 24 statements for 22 clinical questions after extensive modifications and omission of one clinical question were achieved with a consensus level of >80%. To better organise classification of gastritis and duodenitis based on aetiology, a new classification of gastritis and duodenitis is recommended for the 11th international classification. A new category of H. pylori-associated dyspepsia together with a diagnostic algorithm was proposed. The adoption of grading systems for gastric cancer risk stratification, and modern image-enhancing endoscopy for the diagnosis of gastritis, were recommended. Treatment to eradicate H. pylori infection before preneoplastic changes develop, if feasible, was recommended to minimise the risk of more serious complications of the infection. Conclusions A global consensus for gastritis was developed for the first time, which will be the basis for an international classification system and for further research on the subject. PMID:26187502

A support vector machine approach for classification of welding defects from ultrasonic signals

NASA Astrophysics Data System (ADS)

Chen, Yuan; Ma, Hong-Wei; Zhang, Guang-Ming

2014-07-01

Defect classification is an important issue in ultrasonic non-destructive evaluation. A layered multi-class support vector machine (LMSVM) classification system, which combines multiple SVM classifiers through a layered architecture, is proposed in this paper. The proposed LMSVM classification system is applied to the classification of welding defects from ultrasonic test signals. The measured ultrasonic defect echo signals are first decomposed into wavelet coefficients by the wavelet packet transform. The energy of the wavelet coefficients at different frequency channels are used to construct the feature vectors. The bees algorithm (BA) is then used for feature selection and SVM parameter optimisation for the LMSVM classification system. The BA-based feature selection optimises the energy feature vectors. The optimised feature vectors are input to the LMSVM classification system for training and testing. Experimental results of classifying welding defects demonstrate that the proposed technique is highly robust, precise and reliable for ultrasonic defect classification.

Web-based newborn screening system for metabolic diseases: machine learning versus clinicians.

PubMed

Chen, Wei-Hsin; Hsieh, Sheau-Ling; Hsu, Kai-Ping; Chen, Han-Ping; Su, Xing-Yu; Tseng, Yi-Ju; Chien, Yin-Hsiu; Hwu, Wuh-Liang; Lai, Feipei

2013-05-23

A hospital information system (HIS) that integrates screening data and interpretation of the data is routinely requested by hospitals and parents. However, the accuracy of disease classification may be low because of the disease characteristics and the analytes used for classification. The objective of this study is to describe a system that enhanced the neonatal screening system of the Newborn Screening Center at the National Taiwan University Hospital. The system was designed and deployed according to a service-oriented architecture (SOA) framework under the Web services .NET environment. The system consists of sample collection, testing, diagnosis, evaluation, treatment, and follow-up services among collaborating hospitals. To improve the accuracy of newborn screening, machine learning and optimal feature selection mechanisms were investigated for screening newborns for inborn errors of metabolism. The framework of the Newborn Screening Hospital Information System (NSHIS) used the embedded Health Level Seven (HL7) standards for data exchanges among heterogeneous platforms integrated by Web services in the C# language. In this study, machine learning classification was used to predict phenylketonuria (PKU), hypermethioninemia, and 3-methylcrotonyl-CoA-carboxylase (3-MCC) deficiency. The classification methods used 347,312 newborn dried blood samples collected at the Center between 2006 and 2011. Of these, 220 newborns had values over the diagnostic cutoffs (positive cases) and 1557 had values that were over the screening cutoffs but did not meet the diagnostic cutoffs (suspected cases). The original 35 analytes and the manifested features were ranked based on F score, then combinations of the top 20 ranked features were selected as input features to support vector machine (SVM) classifiers to obtain optimal feature sets. These feature sets were tested using 5-fold cross-validation and optimal models were generated. The datasets collected in year 2011 were used as predicting cases. The feature selection strategies were implemented and the optimal markers for PKU, hypermethioninemia, and 3-MCC deficiency were obtained. The results of the machine learning approach were compared with the cutoff scheme. The number of the false positive cases were reduced from 21 to 2 for PKU, from 30 to 10 for hypermethioninemia, and 209 to 46 for 3-MCC deficiency. This SOA Web service-based newborn screening system can accelerate screening procedures effectively and efficiently. An SVM learning methodology for PKU, hypermethioninemia, and 3-MCC deficiency metabolic diseases classification, including optimal feature selection strategies, is presented. By adopting the results of this study, the number of suspected cases could be reduced dramatically.

Web-Based Newborn Screening System for Metabolic Diseases: Machine Learning Versus Clinicians

PubMed Central

Chen, Wei-Hsin; Hsu, Kai-Ping; Chen, Han-Ping; Su, Xing-Yu; Tseng, Yi-Ju; Chien, Yin-Hsiu; Hwu, Wuh-Liang; Lai, Feipei

2013-01-01

Background A hospital information system (HIS) that integrates screening data and interpretation of the data is routinely requested by hospitals and parents. However, the accuracy of disease classification may be low because of the disease characteristics and the analytes used for classification. Objective The objective of this study is to describe a system that enhanced the neonatal screening system of the Newborn Screening Center at the National Taiwan University Hospital. The system was designed and deployed according to a service-oriented architecture (SOA) framework under the Web services .NET environment. The system consists of sample collection, testing, diagnosis, evaluation, treatment, and follow-up services among collaborating hospitals. To improve the accuracy of newborn screening, machine learning and optimal feature selection mechanisms were investigated for screening newborns for inborn errors of metabolism. Methods The framework of the Newborn Screening Hospital Information System (NSHIS) used the embedded Health Level Seven (HL7) standards for data exchanges among heterogeneous platforms integrated by Web services in the C# language. In this study, machine learning classification was used to predict phenylketonuria (PKU), hypermethioninemia, and 3-methylcrotonyl-CoA-carboxylase (3-MCC) deficiency. The classification methods used 347,312 newborn dried blood samples collected at the Center between 2006 and 2011. Of these, 220 newborns had values over the diagnostic cutoffs (positive cases) and 1557 had values that were over the screening cutoffs but did not meet the diagnostic cutoffs (suspected cases). The original 35 analytes and the manifested features were ranked based on F score, then combinations of the top 20 ranked features were selected as input features to support vector machine (SVM) classifiers to obtain optimal feature sets. These feature sets were tested using 5-fold cross-validation and optimal models were generated. The datasets collected in year 2011 were used as predicting cases. Results The feature selection strategies were implemented and the optimal markers for PKU, hypermethioninemia, and 3-MCC deficiency were obtained. The results of the machine learning approach were compared with the cutoff scheme. The number of the false positive cases were reduced from 21 to 2 for PKU, from 30 to 10 for hypermethioninemia, and 209 to 46 for 3-MCC deficiency. Conclusions This SOA Web service–based newborn screening system can accelerate screening procedures effectively and efficiently. An SVM learning methodology for PKU, hypermethioninemia, and 3-MCC deficiency metabolic diseases classification, including optimal feature selection strategies, is presented. By adopting the results of this study, the number of suspected cases could be reduced dramatically. PMID:23702487

GPU based cloud system for high-performance arrhythmia detection with parallel k-NN algorithm.

PubMed

Tae Joon Jun; Hyun Ji Park; Hyuk Yoo; Young-Hak Kim; Daeyoung Kim

2016-08-01

In this paper, we propose an GPU based Cloud system for high-performance arrhythmia detection. Pan-Tompkins algorithm is used for QRS detection and we optimized beat classification algorithm with K-Nearest Neighbor (K-NN). To support high performance beat classification on the system, we parallelized beat classification algorithm with CUDA to execute the algorithm on virtualized GPU devices on the Cloud system. MIT-BIH Arrhythmia database is used for validation of the algorithm. The system achieved about 93.5% of detection rate which is comparable to previous researches while our algorithm shows 2.5 times faster execution time compared to CPU only detection algorithm.

Evaluation and integration of disparate classification systems for clefts of the lip

PubMed Central

Wang, Kathie H.; Heike, Carrie L.; Clarkson, Melissa D.; Mejino, Jose L. V.; Brinkley, James F.; Tse, Raymond W.; Birgfeld, Craig B.; Fitzsimons, David A.; Cox, Timothy C.

2014-01-01

Orofacial clefting is a common birth defect with wide phenotypic variability. Many systems have been developed to classify cleft patterns to facilitate diagnosis, management, surgical treatment, and research. In this review, we examine the rationale for different existing classification schemes and determine their inter-relationships, as well as strengths and deficiencies for subclassification of clefts of the lip. The various systems differ in how they describe and define attributes of cleft lip (CL) phenotypes. Application and analysis of the CL classifications reveal discrepancies that may result in errors when comparing studies that use different systems. These inconsistencies in terminology, variable levels of subclassification, and ambiguity in some descriptions may confound analyses and impede further research aimed at understanding the genetics and etiology of clefts, development of effective treatment options for patients, as well as cross-institutional comparisons of outcome measures. Identification and reconciliation of discrepancies among existing systems is the first step toward creating a common standard to allow for a more explicit interpretation that will ultimately lead to a better understanding of the causes and manifestations of phenotypic variations in clefting. PMID:24860508

Systems Operation Studies for Automated Guideway Transit Systems - Classification and Definition of AGT Systems

DOT National Transportation Integrated Search

1980-02-01

The report describes the development of an AGT classification structure. Five classes are defined based on three system characteristics: service type, minimum travelling unit capacity, and maximum operating velocity. The five classes defined are: Per...

Mapping fuels at multiple scales: landscape application of the fuel characteristic classification system.

Treesearch

D. McKenzie; C.L. Raymond; L.-K.B. Kellogg; R.A. Norheim; A.G. Andreu; A.C. Bayard; K.E. Kopper; E. Elman

2007-01-01

Fuel mapping is a complex and often multidisciplinary process, involving remote sensing, ground-based validation, statistical modeling, and knowledge-based systems. The scale and resolution of fuel mapping depend both on objectives and availability of spatial data layers. We demonstrate use of the Fuel Characteristic Classification System (FCCS) for fuel mapping at two...

Identification of Putative Cardiovascular System Developmental Toxicants using a Classification Model based on Signaling Pathway-Adverse Outcome Pathways

EPA Science Inventory

An important challenge for an integrative approach to developmental systems toxicology is associating putative molecular initiating events (MIEs), cell signaling pathways, cell function and modeled fetal exposure kinetics. We have developed a chemical classification model based o...

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.

Power System Transient Stability Based on Data Mining Theory

NASA Astrophysics Data System (ADS)

Cui, Zhen; Shi, Jia; Wu, Runsheng; Lu, Dan; Cui, Mingde

2018-01-01

In order to study the stability of power system, a power system transient stability based on data mining theory is designed. By introducing association rules analysis in data mining theory, an association classification method for transient stability assessment is presented. A mathematical model of transient stability assessment based on data mining technology is established. Meanwhile, combining rule reasoning with classification prediction, the method of association classification is proposed to perform transient stability assessment. The transient stability index is used to identify the samples that cannot be correctly classified in association classification. Then, according to the critical stability of each sample, the time domain simulation method is used to determine the state, so as to ensure the accuracy of the final results. The results show that this stability assessment system can improve the speed of operation under the premise that the analysis result is completely correct, and the improved algorithm can find out the inherent relation between the change of power system operation mode and the change of transient stability degree.

Effects of a Peer Assessment System Based on a Grid-Based Knowledge Classification Approach on Computer Skills Training

ERIC Educational Resources Information Center

Hsu, Ting-Chia

2016-01-01

In this study, a peer assessment system using the grid-based knowledge classification approach was developed to improve students' performance during computer skills training. To evaluate the effectiveness of the proposed approach, an experiment was conducted in a computer skills certification course. The participants were divided into three…

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.

Approach for a Clinically Useful Comprehensive Classification of Vascular and Neural Aspects of Diabetic Retinal Disease

PubMed Central

Abramoff, Michael D.; Fort, Patrice E.; Han, Ian C.; Jayasundera, K. Thiran; Sohn, Elliott H.; Gardner, Thomas W.

2018-01-01

The Early Treatment Diabetic Retinopathy Study (ETDRS) and other standardized classification schemes have laid a foundation for tremendous advances in the understanding and management of diabetic retinopathy (DR). However, technological advances in optics and image analysis, especially optical coherence tomography (OCT), OCT angiography (OCTa), and ultra-widefield imaging, as well as new discoveries in diabetic retinal neuropathy (DRN), are exposing the limitations of ETDRS and other classification systems to completely characterize retinal changes in diabetes, which we term diabetic retinal disease (DRD). While it may be most straightforward to add axes to existing classification schemes, as diabetic macular edema (DME) was added as an axis to earlier DR classifications, doing so may make these classifications increasingly complicated and thus clinically intractable. Therefore, we propose future research efforts to develop a new, comprehensive, and clinically useful classification system that will identify multimodal biomarkers to reflect the complex pathophysiology of DRD and accelerate the development of therapies to prevent vision-threatening DRD. PMID:29372250

Approach for a Clinically Useful Comprehensive Classification of Vascular and Neural Aspects of Diabetic Retinal Disease.

PubMed

Abramoff, Michael D; Fort, Patrice E; Han, Ian C; Jayasundera, K Thiran; Sohn, Elliott H; Gardner, Thomas W

2018-01-01

The Early Treatment Diabetic Retinopathy Study (ETDRS) and other standardized classification schemes have laid a foundation for tremendous advances in the understanding and management of diabetic retinopathy (DR). However, technological advances in optics and image analysis, especially optical coherence tomography (OCT), OCT angiography (OCTa), and ultra-widefield imaging, as well as new discoveries in diabetic retinal neuropathy (DRN), are exposing the limitations of ETDRS and other classification systems to completely characterize retinal changes in diabetes, which we term diabetic retinal disease (DRD). While it may be most straightforward to add axes to existing classification schemes, as diabetic macular edema (DME) was added as an axis to earlier DR classifications, doing so may make these classifications increasingly complicated and thus clinically intractable. Therefore, we propose future research efforts to develop a new, comprehensive, and clinically useful classification system that will identify multimodal biomarkers to reflect the complex pathophysiology of DRD and accelerate the development of therapies to prevent vision-threatening DRD.

Understanding Treatment of Mild Traumatic Brain Injury in the Military Health System

DTIC Science & Technology

2016-04-18

OEF Veterans: Polytrauma Clinical Triad,” Journal of Rehabilitation Research and Development, Vol. 46, No. 6, July 2009, pp. 697–702. Lew, Henry L...pubs/permissions.html. The RAND Corporation is a research organization that develops solutions to public policy challenges to help make communities...case definition for mTBI based on codes in the International Classification of Dis- eases, Ninth Revision (ICD-9), Clinical Modification. The team then

Phenomenology and classification of dystonia: a consensus update

PubMed Central

Albanese, Alberto; Bhatia, Kailash; Bressman, Susan B.; DeLong, Mahlon R.; Fahn, Stanley; Fung, Victor S.C.; Hallett, Mark; Jankovic, Joseph; Jinnah, H.A.; Klein, Christine; Lang, Anthony E.; Mink, Jonathan W.; Teller, Jan K.

2013-01-01

This report describes the consensus outcome of an international panel consisting of investigators with years of experience in this field that reviewed the definition and classification of dystonia. Agreement was obtained based on a consensus development methodology during three in-person meetings and manuscript review by mail. Dystonia is defined as a movement disorder characterized by sustained or intermittent muscle contractions causing abnormal, often repetitive, movements, postures, or both. Dystonic movements are typically patterned and twisting, and may be tremulous. Dystonia is often initiated or worsened by voluntary action and associated with overflow muscle activation. Dystonia is classified along two axes: clinical characteristics, including age at onset, body distribution, temporal pattern and associated features (additional movement disorders or neurological features), and etiology, which includes nervous system pathology and inheritance. The clinical characteristics fall into several specific dystonia syndromes that help to guide diagnosis and treatment. We provide here a new general definition of dystonia and propose a new classification. We encourage clinicians and researchers to use these innovative definition and classification and test them in the clinical setting on a variety of patients with dystonia. PMID:23649720

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

An auxiliary classification diagnosis software development of cervical cancer medical data based on various artificial neural networks

NASA Astrophysics Data System (ADS)

Qi, Yong; Lei, Kai; Zhang, Lizeqing; Xing, Ximing; Gou, Wenyue

2018-06-01

This paper introduced the development of a self-serving medical data assisted diagnosis software of cervical cancer on the basis of artificial neural network (SVN, FNN, KNN). The system is developed based on the idea of self-service platform, supported by the application and innovation of neural network algorithm in medical data identification. Furthermore, it combined the advanced methods in various fields to effectively solve the complicated and inaccurate problem of cervical canceration data in the traditional manual treatment.

The ICI classification for calcaneal injuries: a validation study.

PubMed

Frima, Herman; Eshuis, Rienk; Mulder, Paul; Leenen, Luke

2012-06-01

The integral classification of injuries (ICI), by Zwipp et al. has been developed as a classification system for injuries of the bones, joints, cartilage and ligaments of the foot. It follows the principles of the comprehensive classification of fractures by Müller et al. The ICI was developed for 'everyday use' and scientific purposes. Our aim was to perform a validation study for this classification system applied to the calcaneal injuries. A panel of five experienced trauma and orthopaedic surgeons evaluated the ICI score in 20 calcaneal injuries. After 2 months, a second classification was performed in a different order. Inter- and intra-observer variability were evaluated by kappa statistics. Panel members were not able to evaluate capsule and ligamental injuries based on X-ray and computed tomography (CT) films. Two injuries were excluded for logistical reasons. The inter-observer agreement based on 18 injuries of bone and joints was slight; kappa 0.14 (90% confidence interval (CI): 0.05-0.22). The intra-observer agreement was fair; kappa 0.31 (90% CI: 0.22-0.41). Overall, the panel rated the system as very complicated and not practical. The ICI is a complicated classification system with slight to fair inter- and intra-observer variabilities. It might not be a practical classification system for calcaneal injuries in 'everyday use' or scientific purposes. Copyright © 2011 Elsevier Ltd. All rights reserved.

Classification System and Information Services in the Library of SAO RAS

NASA Astrophysics Data System (ADS)

Shvedova, G. S.

The classification system used at SAO RAS is described. It includes both special determinants from UDC (Universal Decimal Classification) and newer tables with astronomical terms from the Library-Bibliographical Classification (LBC). The classification tables are continually modified, and new astronomical terms are introduced. At the present time the information services of the scientists is fulfilled with the help of the Abstract Journal Astronomy, Astronomy and Astrophysics Abstracts, catalogues and card indexes of the library. Based on our classification system and The Astronomy Thesaurus completed by R.M. Shobbrook and R.R. Shobbrook the development of a database for the library has been started, which allows prompt service of the observatory's staff members.

The Eighth Edition AJCC Cancer Staging Manual: Continuing to build a bridge from a population-based to a more "personalized" approach to cancer staging.

PubMed

Amin, Mahul B; Greene, Frederick L; Edge, Stephen B; Compton, Carolyn C; Gershenwald, Jeffrey E; Brookland, Robert K; Meyer, Laura; Gress, Donna M; Byrd, David R; Winchester, David P

2017-03-01

The American Joint Committee on Cancer (AJCC) staging manual has become the benchmark for classifying patients with cancer, defining prognosis, and determining the best treatment approaches. Many view the primary role of the tumor, lymph node, metastasis (TNM) system as that of a standardized classification system for evaluating cancer at a population level in terms of the extent of disease, both at initial presentation and after surgical treatment, and the overall impact of improvements in cancer treatment. The rapid evolution of knowledge in cancer biology and the discovery and validation of biologic factors that predict cancer outcome and response to treatment with better accuracy have led some cancer experts to question the utility of a TNM-based approach in clinical care at an individualized patient level. In the Eighth Edition of the AJCC Cancer Staging Manual, the goal of including relevant, nonanatomic (including molecular) factors has been foremost, although changes are made only when there is strong evidence for inclusion. The editorial board viewed this iteration as a proactive effort to continue to build the important bridge from a "population-based" to a more "personalized" approach to patient classification, one that forms the conceptual framework and foundation of cancer staging in the era of precision molecular oncology. The AJCC promulgates best staging practices through each new edition in an effort to provide cancer care providers with a powerful, knowledge-based resource for the battle against cancer. In this commentary, the authors highlight the overall organizational and structural changes as well as "what's new" in the Eighth Edition. It is hoped that this information will provide the reader with a better understanding of the rationale behind the aggregate proposed changes and the exciting developments in the upcoming edition. CA Cancer J Clin 2017;67:93-99. © 2017 American Cancer Society. © 2017 American Cancer Society.

[Rehabilitee-management-categories (RMK)--results of the development phase and of the first clinical implementation in alcohol rehabilitation centres].

PubMed

Spyra, K; Köhn, S; Ammelburg, N; Schmidt, C; Missel, P; Lindenmeyer, J

2011-10-01

Due to the introduction of lump sum reimbursement systems for acute-care settings (DRGs), patient classification systems have been developed in Germany during the last 15 years to adapt a case-based lump sum system to the field of medical rehabilitation. The concept of Rehabilitee-Management-Categories (RMK), developed by the Charité - Universitätsmedizin Berlin, classifies rehabilitees primarily by their relevant impairments of activity and participation, as these factors mainly determine treatment needs and resources required in rehabilitation. It can, inter alia, be used to optimize the demand-related allocation of treatment services in the rehabilitation centres as well as lead to more transparency in the allocation process. RMK results are reported on the example of inpatient rehabilitation of alcohol dependence. Utilizing internationally established assessments, an RMK-assessment was developed that allows the assessment of rehab treatment needs of patients undergoing alcohol dependence rehabilitation. The RMK-assessment was completed by n=731 rehabilitees. Latent class analysis was applied to find groups of cases. To facilitate the RMK-patient classification a software-based algorithm was developed and implemented in 12 rehabilitation centres (implementation study). To validate the results of the first study phase, the data collected during implementation (n=1,533) was again analyzed using latent class analysis. Combined standardized and qualitative user surveys were conducted at the end of the implementation study. On the basis of 15 needs-related patient characteristics, 4 comparable case groups (AL-1 to AL-4) each were identified in 2 independent samples, groups that differed significantly in their degree of dependence-related, psychological and social impairment. The user survey confirmed the basic clinical plausibility of the 4 different case groups as well as the feasibility of the instruments applied in a rehabilitation setting. The RMK-concept offers a new approach for a demand-related patient classification in medical rehabilitation. The RMK-instruments allow a standardized initial assessment of impairment and treatment needs in alcohol rehabilitation and can hence be used for objective comparisons between rehabilitation centres. The results of the RMK-assessment provide relevant information about demand-related treatment requirements, which is a matter of great interest in the context of limited resources. Appropriate treatment requirements for the 4 RMK-case groups will be defined and verified in the next step of the RMK-concept. A financial evaluation of the RMK is possible in principal, will however require more extensive development, not least in order to model and evaluate the health-economic implications involved. © Georg Thieme Verlag KG Stuttgart · New York.

Structural MRI-based detection of Alzheimer's disease using feature ranking and classification error.

PubMed

Beheshti, Iman; Demirel, Hasan; Farokhian, Farnaz; Yang, Chunlan; Matsuda, Hiroshi

2016-12-01

This paper presents an automatic computer-aided diagnosis (CAD) system based on feature ranking for detection of Alzheimer's disease (AD) using structural magnetic resonance imaging (sMRI) data. The proposed CAD system is composed of four systematic stages. First, global and local differences in the gray matter (GM) of AD patients compared to the GM of healthy controls (HCs) are analyzed using a voxel-based morphometry technique. The aim is to identify significant local differences in the volume of GM as volumes of interests (VOIs). Second, the voxel intensity values of the VOIs are extracted as raw features. Third, the raw features are ranked using a seven-feature ranking method, namely, statistical dependency (SD), mutual information (MI), information gain (IG), Pearson's correlation coefficient (PCC), t-test score (TS), Fisher's criterion (FC), and the Gini index (GI). The features with higher scores are more discriminative. To determine the number of top features, the estimated classification error based on training set made up of the AD and HC groups is calculated, with the vector size that minimized this error selected as the top discriminative feature. Fourth, the classification is performed using a support vector machine (SVM). In addition, a data fusion approach among feature ranking methods is introduced to improve the classification performance. The proposed method is evaluated using a data-set from ADNI (130 AD and 130 HC) with 10-fold cross-validation. The classification accuracy of the proposed automatic system for the diagnosis of AD is up to 92.48% using the sMRI data. An automatic CAD system for the classification of AD based on feature-ranking method and classification errors is proposed. In this regard, seven-feature ranking methods (i.e., SD, MI, IG, PCC, TS, FC, and GI) are evaluated. The optimal size of top discriminative features is determined by the classification error estimation in the training phase. The experimental results indicate that the performance of the proposed system is comparative to that of state-of-the-art classification models. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Quantitative classification of a historic northern Wisconsin (U.S.A.) landscape: mapping forests at regional scales

Treesearch

Lisa A. Schulte; David J. Mladenoff; Erik V. Nordheim

2002-01-01

We developed a quantitative and replicable classification system to improve understanding of historical composition and structure within northern Wisconsin's forests. The classification system was based on statistical cluster analysis and two forest metrics, relative dominance (% basal area) and relative importance (mean of relative dominance and relative density...

Alzheimer disease detection from structural MR images using FCM based weighted probabilistic neural network.

PubMed

Duraisamy, Baskar; Shanmugam, Jayanthi Venkatraman; Annamalai, Jayanthi

2018-02-19

An early intervention of Alzheimer's disease (AD) is highly essential due to the fact that this neuro degenerative disease generates major life-threatening issues, especially memory loss among patients in society. Moreover, categorizing NC (Normal Control), MCI (Mild Cognitive Impairment) and AD early in course allows the patients to experience benefits from new treatments. Therefore, it is important to construct a reliable classification technique to discriminate the patients with or without AD from the bio medical imaging modality. Hence, we developed a novel FCM based Weighted Probabilistic Neural Network (FWPNN) classification algorithm and analyzed the brain images related to structural MRI modality for better discrimination of class labels. Initially our proposed framework begins with brain image normalization stage. In this stage, ROI regions related to Hippo-Campus (HC) and Posterior Cingulate Cortex (PCC) from the brain images are extracted using Automated Anatomical Labeling (AAL) method. Subsequently, nineteen highly relevant AD related features are selected through Multiple-criterion feature selection method. At last, our novel FWPNN classification algorithm is imposed to remove suspicious samples from the training data with an end goal to enhance the classification performance. This newly developed classification algorithm combines both the goodness of supervised and unsupervised learning techniques. The experimental validation is carried out with the ADNI subset and then to the Bordex-3 city dataset. Our proposed classification approach achieves an accuracy of about 98.63%, 95.4%, 96.4% in terms of classification with AD vs NC, MCI vs NC and AD vs MCI. The experimental results suggest that the removal of noisy samples from the training data can enhance the decision generation process of the expert systems.

Perspectives on Next Steps in Classification of Orofacial Pain – Part 2: Role of psychosocial factors

PubMed Central

Durham, Justin; Raphael, Karen G.; Benoliel, Rafael; Ceusters, Werner; Michelotti, Ambra; Ohrbach, Richard

2015-01-01

This paper was initiated by a symposium, in which the present authors contributed, organised by the International RDC/TMD Consortium Network in March 2013. The purpose of the paper is to review the status of biobehavioural research – both quantitative and qualitative – related to orofacial pain with respect to the etiology, pathophysiology, diagnosis and management of orofacial pain conditions, and how this information can optimally be used for developing a structured orofacial pain classification system for research. In particular, we address: representation of psychosocial entities in classification systems, use of qualitative research to identify and understand the full scope of psychosocial entities and their interaction, and the usage of classification system for guiding treatment. We then provide recommendations for addressing these problems, including how ontological principles can inform this process. PMID:26257252

A statistical approach to root system classification

PubMed Central

Bodner, Gernot; Leitner, Daniel; Nakhforoosh, Alireza; Sobotik, Monika; Moder, Karl; Kaul, Hans-Peter

2013-01-01

Plant root systems have a key role in ecology and agronomy. In spite of fast increase in root studies, still there is no classification that allows distinguishing among distinctive characteristics within the diversity of rooting strategies. Our hypothesis is that a multivariate approach for “plant functional type” identification in ecology can be applied to the classification of root systems. The classification method presented is based on a data-defined statistical procedure without a priori decision on the classifiers. The study demonstrates that principal component based rooting types provide efficient and meaningful multi-trait classifiers. The classification method is exemplified with simulated root architectures and morphological field data. Simulated root architectures showed that morphological attributes with spatial distribution parameters capture most distinctive features within root system diversity. While developmental type (tap vs. shoot-borne systems) is a strong, but coarse classifier, topological traits provide the most detailed differentiation among distinctive groups. Adequacy of commonly available morphologic traits for classification is supported by field data. Rooting types emerging from measured data, mainly distinguished by diameter/weight and density dominated types. Similarity of root systems within distinctive groups was the joint result of phylogenetic relation and environmental as well as human selection pressure. We concluded that the data-define classification is appropriate for integration of knowledge obtained with different root measurement methods and at various scales. Currently root morphology is the most promising basis for classification due to widely used common measurement protocols. To capture details of root diversity efforts in architectural measurement techniques are essential. PMID:23914200

A statistical approach to root system classification.

PubMed

Bodner, Gernot; Leitner, Daniel; Nakhforoosh, Alireza; Sobotik, Monika; Moder, Karl; Kaul, Hans-Peter

2013-01-01

Plant root systems have a key role in ecology and agronomy. In spite of fast increase in root studies, still there is no classification that allows distinguishing among distinctive characteristics within the diversity of rooting strategies. Our hypothesis is that a multivariate approach for "plant functional type" identification in ecology can be applied to the classification of root systems. The classification method presented is based on a data-defined statistical procedure without a priori decision on the classifiers. The study demonstrates that principal component based rooting types provide efficient and meaningful multi-trait classifiers. The classification method is exemplified with simulated root architectures and morphological field data. Simulated root architectures showed that morphological attributes with spatial distribution parameters capture most distinctive features within root system diversity. While developmental type (tap vs. shoot-borne systems) is a strong, but coarse classifier, topological traits provide the most detailed differentiation among distinctive groups. Adequacy of commonly available morphologic traits for classification is supported by field data. Rooting types emerging from measured data, mainly distinguished by diameter/weight and density dominated types. Similarity of root systems within distinctive groups was the joint result of phylogenetic relation and environmental as well as human selection pressure. We concluded that the data-define classification is appropriate for integration of knowledge obtained with different root measurement methods and at various scales. Currently root morphology is the most promising basis for classification due to widely used common measurement protocols. To capture details of root diversity efforts in architectural measurement techniques are essential.

Recursive heuristic classification

NASA Technical Reports Server (NTRS)

Wilkins, David C.

1994-01-01

The author will describe a new problem-solving approach called recursive heuristic classification, whereby a subproblem of heuristic classification is itself formulated and solved by heuristic classification. This allows the construction of more knowledge-intensive classification programs in a way that yields a clean organization. Further, standard knowledge acquisition and learning techniques for heuristic classification can be used to create, refine, and maintain the knowledge base associated with the recursively called classification expert system. The method of recursive heuristic classification was used in the Minerva blackboard shell for heuristic classification. Minerva recursively calls itself every problem-solving cycle to solve the important blackboard scheduler task, which involves assigning a desirability rating to alternative problem-solving actions. Knowing these ratings is critical to the use of an expert system as a component of a critiquing or apprenticeship tutoring system. One innovation of this research is a method called dynamic heuristic classification, which allows selection among dynamically generated classification categories instead of requiring them to be prenumerated.

Classification of large-scale fundus image data sets: a cloud-computing framework.

PubMed

Roychowdhury, Sohini

2016-08-01

Large medical image data sets with high dimensionality require substantial amount of computation time for data creation and data processing. This paper presents a novel generalized method that finds optimal image-based feature sets that reduce computational time complexity while maximizing overall classification accuracy for detection of diabetic retinopathy (DR). First, region-based and pixel-based features are extracted from fundus images for classification of DR lesions and vessel-like structures. Next, feature ranking strategies are used to distinguish the optimal classification feature sets. DR lesion and vessel classification accuracies are computed using the boosted decision tree and decision forest classifiers in the Microsoft Azure Machine Learning Studio platform, respectively. For images from the DIARETDB1 data set, 40 of its highest-ranked features are used to classify four DR lesion types with an average classification accuracy of 90.1% in 792 seconds. Also, for classification of red lesion regions and hemorrhages from microaneurysms, accuracies of 85% and 72% are observed, respectively. For images from STARE data set, 40 high-ranked features can classify minor blood vessels with an accuracy of 83.5% in 326 seconds. Such cloud-based fundus image analysis systems can significantly enhance the borderline classification performances in automated screening systems.

The ACTTION-American Pain Society Pain Taxonomy (AAPT): an evidence-based and multidimensional approach to classifying chronic pain conditions.

PubMed

Fillingim, Roger B; Bruehl, Stephen; Dworkin, Robert H; Dworkin, Samuel F; Loeser, John D; Turk, Dennis C; Widerstrom-Noga, Eva; Arnold, Lesley; Bennett, Robert; Edwards, Robert R; Freeman, Roy; Gewandter, Jennifer; Hertz, Sharon; Hochberg, Marc; Krane, Elliot; Mantyh, Patrick W; Markman, John; Neogi, Tuhina; Ohrbach, Richard; Paice, Judith A; Porreca, Frank; Rappaport, Bob A; Smith, Shannon M; Smith, Thomas J; Sullivan, Mark D; Verne, G Nicholas; Wasan, Ajay D; Wesselmann, Ursula

2014-03-01

Current approaches to classification of chronic pain conditions suffer from the absence of a systematically implemented and evidence-based taxonomy. Moreover, existing diagnostic approaches typically fail to incorporate available knowledge regarding the biopsychosocial mechanisms contributing to pain conditions. To address these gaps, the Analgesic, Anesthetic, and Addiction Clinical Trial Translations Innovations Opportunities and Networks (ACTTION) public-private partnership with the U.S. Food and Drug Administration and the American Pain Society (APS) have joined together to develop an evidence-based chronic pain classification system called the ACTTION-APS Pain Taxonomy. This paper describes the outcome of an ACTTION-APS consensus meeting, at which experts agreed on a structure for this new taxonomy of chronic pain conditions. Several major issues around which discussion revolved are presented and summarized, and the structure of the taxonomy is presented. ACTTION-APS Pain Taxonomy will include the following dimensions: 1) core diagnostic criteria; 2) common features; 3) common medical comorbidities; 4) neurobiological, psychosocial, and functional consequences; and 5) putative neurobiological and psychosocial mechanisms, risk factors, and protective factors. In coming months, expert working groups will apply this taxonomy to clusters of chronic pain conditions, thereby developing a set of diagnostic criteria that have been consistently and systematically implemented across nearly all common chronic pain conditions. It is anticipated that the availability of this evidence-based and mechanistic approach to pain classification will be of substantial benefit to chronic pain research and treatment. The ACTTION-APS Pain Taxonomy is an evidence-based chronic pain classification system designed to classify chronic pain along the following dimensions: 1) core diagnostic criteria; 2) common features; 3) common medical comorbidities; 4) neurobiological, psychosocial, and functional consequences; and 5) putative neurobiological and psychosocial mechanisms, risk factors, and protective factors. Copyright © 2014 American Pain Society. Published by Elsevier Inc. All rights reserved.

21 CFR 862.1575 - Phospholipid test system.

Code of Federal Regulations, 2010 CFR

2010-04-01

...) MEDICAL DEVICES CLINICAL CHEMISTRY AND CLINICAL TOXICOLOGY DEVICES Clinical Chemistry Test Systems § 862... treatment of disorders involving lipid (fat) metabolism. (b) Classification. Class I (general controls). The...

21 CFR 862.1542 - Oxalate test system.

Code of Federal Regulations, 2010 CFR

2010-04-01

...) MEDICAL DEVICES CLINICAL CHEMISTRY AND CLINICAL TOXICOLOGY DEVICES Clinical Chemistry Test Systems § 862... treatment of urinary stones or certain other metabolic disorders. (b) Classification. Class I (general...

Automated radial basis function neural network based image classification system for diabetic retinopathy detection in retinal images

NASA Astrophysics Data System (ADS)

Anitha, J.; Vijila, C. Kezi Selva; Hemanth, D. Jude

2010-02-01

Diabetic retinopathy (DR) is a chronic eye disease for which early detection is highly essential to avoid any fatal results. Image processing of retinal images emerge as a feasible tool for this early diagnosis. Digital image processing techniques involve image classification which is a significant technique to detect the abnormality in the eye. Various automated classification systems have been developed in the recent years but most of them lack high classification accuracy. Artificial neural networks are the widely preferred artificial intelligence technique since it yields superior results in terms of classification accuracy. In this work, Radial Basis function (RBF) neural network based bi-level classification system is proposed to differentiate abnormal DR Images and normal retinal images. The results are analyzed in terms of classification accuracy, sensitivity and specificity. A comparative analysis is performed with the results of the probabilistic classifier namely Bayesian classifier to show the superior nature of neural classifier. Experimental results show promising results for the neural classifier in terms of the performance measures.

Assessment of the Hong Kong Liver Cancer Staging System in Europe.

PubMed

Kolly, Philippe; Reeves, Helen; Sangro, Bruno; Knöpfli, Marina; Candinas, Daniel; Dufour, Jean-François

2016-06-01

European and American guidelines have endorsed the Barcelona Clinic Liver Cancer (BCLC) staging system. The aim of this study was to assess the performance of the recently developed Hong Kong Liver Cancer (HKLC) classification as a staging system for hepatocellular carcinoma (HCC) in Europe. We used a pooled set of 1693 HCC patients combining three prospective European cohorts. Discrimination ability between the nine substages and five stages of the HKLC classification system was assessed. To evaluate the predictive power of the HKLC and BCLC staging systems on overall survival, Nagelkerke pseudo R2, Bayesian Information Criterion and Harrell's concordance index were calculated. The number of patients who would benefit from a curative therapy was assessed for both staging systems. The HKLC classification in nine substages shows suboptimal discrimination between the staging groups. The classification in five stages shows better discrimination between groups. However, the BCLC classification performs better than the HKLC classification in the ability to predict overall survival (OS). The HKLC treatment algorithm tags significantly more patients to curative therapy than the BCLC. The BCLC staging system performs better for European patients than the HKLC staging system in predicting OS. Twice more patients are eligible for a curative therapy with the HKLC algorithm; whether this translates in survival benefit remains to be investigated. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

48 CFR 47.305-9 - Commodity description and freight classification.

Code of Federal Regulations, 2010 CFR

2010-10-01

... freight classification. 47.305-9 Section 47.305-9 Federal Acquisition Regulations System FEDERAL... Commodity description and freight classification. (a) Generally, the freight rate for supplies is based on the rating applicable to the freight classification description published in the National Motor...

48 CFR 47.305-9 - Commodity description and freight classification.

Code of Federal Regulations, 2014 CFR

2014-10-01

... of previously shipped items, and different freight classifications may apply, the contracting officer... freight classification. 47.305-9 Section 47.305-9 Federal Acquisition Regulations System FEDERAL... Commodity description and freight classification. (a) Generally, the freight rate for supplies is based on...

48 CFR 47.305-9 - Commodity description and freight classification.

Code of Federal Regulations, 2013 CFR

2013-10-01

... of previously shipped items, and different freight classifications may apply, the contracting officer... freight classification. 47.305-9 Section 47.305-9 Federal Acquisition Regulations System FEDERAL... Commodity description and freight classification. (a) Generally, the freight rate for supplies is based on...

48 CFR 47.305-9 - Commodity description and freight classification.

Code of Federal Regulations, 2012 CFR

2012-10-01

... of previously shipped items, and different freight classifications may apply, the contracting officer... freight classification. 47.305-9 Section 47.305-9 Federal Acquisition Regulations System FEDERAL... Commodity description and freight classification. (a) Generally, the freight rate for supplies is based on...

48 CFR 47.305-9 - Commodity description and freight classification.

Code of Federal Regulations, 2011 CFR

2011-10-01

... of previously shipped items, and different freight classifications may apply, the contracting officer... freight classification. 47.305-9 Section 47.305-9 Federal Acquisition Regulations System FEDERAL... Commodity description and freight classification. (a) Generally, the freight rate for supplies is based on...

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.

Advanced microprocessor based power protection system using artificial neural network techniques

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

Chen, Z.; Kalam, A.; Zayegh, A.

This paper describes an intelligent embedded microprocessor based system for fault classification in power system protection system using advanced 32-bit microprocessor technology. The paper demonstrates the development of protective relay to provide overcurrent protection schemes for fault detection. It also describes a method for power fault classification in three-phase system based on the use of neural network technology. The proposed design is implemented and tested on a single line three phase power system in power laboratory. Both the hardware and software development are described in detail.

[Diagnosis-related groups as an instrument to develop suitable case-based lump sums in hematology and oncology].

PubMed

Thalheimer, Markus

2011-01-01

In 2003 a new reimbursement system was established for German hospitals. The approximately 17 million inpatient cases per year are now reimbursed based on a per-case payment regarding diagnoses and procedures, which was developed from an internationally approved system. The aim was a better conformity of costs and efforts in in-patient cases. In the first 2 years after implementation, the German diagnosis-related group (DRG) system was not able to adequately represent the complex structures of treatment in hematological and oncological in-patients. By creating new diagnoses and procedures (International Classification of Diseases 10 (ICD-10) and Surgical Operations and Procedures Classification System (OPS) catalogues), generating new DRGs and better splitting of existing ones, the hematology and oncology field could be much better described in the following years. The implementation of about 70 'co-payment structures' for new and expensive drugs and procedures in oncology was also crucial. To reimburse innovations, an additional system of co-payments for innovations was established to bridge the time until innovations are represented within the DRG system itself. In summary, hematological and oncological in-patients, including cases with extraordinary costs, are meanwhile well mapped in the German reimbursement system. Any tendencies to rationing could thereby be avoided, as most of the established procedures and costly drugs are adequately represented in the DRG system. Copyright © 2011 S. Karger AG, Basel.

Automatic classification of sleep stages based on the time-frequency image of EEG signals.

PubMed

Bajaj, Varun; Pachori, Ram Bilas

2013-12-01

In this paper, a new method for automatic sleep stage classification based on time-frequency image (TFI) of electroencephalogram (EEG) signals is proposed. Automatic classification of sleep stages is an important part for diagnosis and treatment of sleep disorders. The smoothed pseudo Wigner-Ville distribution (SPWVD) based time-frequency representation (TFR) of EEG signal has been used to obtain the time-frequency image (TFI). The segmentation of TFI has been performed based on the frequency-bands of the rhythms of EEG signals. The features derived from the histogram of segmented TFI have been used as an input feature set to multiclass least squares support vector machines (MC-LS-SVM) together with the radial basis function (RBF), Mexican hat wavelet, and Morlet wavelet kernel functions for automatic classification of sleep stages from EEG signals. The experimental results are presented to show the effectiveness of the proposed method for classification of sleep stages from EEG signals. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Gynecomastia Classification for Surgical Management: A Systematic Review and Novel Classification System.

PubMed

Waltho, Daniel; Hatchell, Alexandra; Thoma, Achilleas

2017-03-01

Gynecomastia is a common deformity of the male breast, where certain cases warrant surgical management. There are several surgical options, which vary depending on the breast characteristics. To guide surgical management, several classification systems for gynecomastia have been proposed. A systematic review was performed to (1) identify all classification systems for the surgical management of gynecomastia, and (2) determine the adequacy of these classification systems to appropriately categorize the condition for surgical decision-making. The search yielded 1012 articles, and 11 articles were included in the review. Eleven classification systems in total were ascertained, and a total of 10 unique features were identified: (1) breast size, (2) skin redundancy, (3) breast ptosis, (4) tissue predominance, (5) upper abdominal laxity, (6) breast tuberosity, (7) nipple malposition, (8) chest shape, (9) absence of sternal notch, and (10) breast skin elasticity. On average, classification systems included two or three of these features. Breast size and ptosis were the most commonly included features. Based on their review of the current classification systems, the authors believe the ideal classification system should be universal and cater to all causes of gynecomastia; be surgically useful and easy to use; and should include a comprehensive set of clinically appropriate patient-related features, such as breast size, breast ptosis, tissue predominance, and skin redundancy. None of the current classification systems appears to fulfill these criteria.

Attachment-based classifications of children's family drawings: psychometric properties and relations with children's adjustment in kindergarten.

PubMed

Pianta, R C; Longmaid, K; Ferguson, J E

1999-06-01

Investigated an attachment-based theoretical framework and classification system, introduced by Kaplan and Main (1986), for interpreting children's family drawings. This study concentrated on the psychometric properties of the system and the relation between drawings classified using this system and teacher ratings of classroom social-emotional and behavioral functioning, controlling for child age, ethnic status, intelligence, and fine motor skills. This nonclinical sample consisted of 200 kindergarten children of diverse racial and socioeconomic status (SES). Limited support for reliability of this classification system was obtained. Kappas for overall classifications of drawings (e.g., secure) exceeded .80 and mean kappa for discrete drawing features (e.g., figures with smiles) was .82. Coders' endorsement of the presence of certain discrete drawing features predicted their overall classification at 82.5% accuracy. Drawing classification was related to teacher ratings of classroom functioning independent of child age, sex, race, SES, intelligence, and fine motor skills (with p values for the multivariate effects ranging from .043-.001). Results are discussed in terms of the psychometric properties of this system for classifying children's representations of family and the limitations of family drawing techniques for young children.

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.

Patterns of Use of an Agent-Based Model and a System Dynamics Model: The Application of Patterns of Use and the Impacts on Learning Outcomes

ERIC Educational Resources Information Center

Thompson, Kate; Reimann, Peter

2010-01-01

A classification system that was developed for the use of agent-based models was applied to strategies used by school-aged students to interrogate an agent-based model and a system dynamics model. These were compared, and relationships between learning outcomes and the strategies used were also analysed. It was found that the classification system…

A Classification Model and an Open E-Learning System Based on Intuitionistic Fuzzy Sets for Instructional Design Concepts

ERIC Educational Resources Information Center

Güyer, Tolga; Aydogdu, Seyhmus

2016-01-01

This study suggests a classification model and an e-learning system based on this model for all instructional theories, approaches, models, strategies, methods, and technics being used in the process of instructional design that constitutes a direct or indirect resource for educational technology based on the theory of intuitionistic fuzzy sets…

Molecular cancer classification using a meta-sample-based regularized robust coding method.

PubMed

Wang, Shu-Lin; Sun, Liuchao; Fang, Jianwen

2014-01-01

Previous studies have demonstrated that machine learning based molecular cancer classification using gene expression profiling (GEP) data is promising for the clinic diagnosis and treatment of cancer. Novel classification methods with high efficiency and prediction accuracy are still needed to deal with high dimensionality and small sample size of typical GEP data. Recently the sparse representation (SR) method has been successfully applied to the cancer classification. Nevertheless, its efficiency needs to be improved when analyzing large-scale GEP data. In this paper we present the meta-sample-based regularized robust coding classification (MRRCC), a novel effective cancer classification technique that combines the idea of meta-sample-based cluster method with regularized robust coding (RRC) method. It assumes that the coding residual and the coding coefficient are respectively independent and identically distributed. Similar to meta-sample-based SR classification (MSRC), MRRCC extracts a set of meta-samples from the training samples, and then encodes a testing sample as the sparse linear combination of these meta-samples. The representation fidelity is measured by the l2-norm or l1-norm of the coding residual. Extensive experiments on publicly available GEP datasets demonstrate that the proposed method is more efficient while its prediction accuracy is equivalent to existing MSRC-based methods and better than other state-of-the-art dimension reduction based methods.

Evaluation of the WHO criteria for the classification of patients with mastocytosis.

PubMed

Sánchez-Muñoz, Laura; Alvarez-Twose, Ivan; García-Montero, Andrés C; Teodosio, Cristina; Jara-Acevedo, María; Pedreira, Carlos E; Matito, Almudena; Morgado, Jose Mario T; Sánchez, Maria Luz; Mollejo, Manuela; Gonzalez-de-Olano, David; Orfao, Alberto; Escribano, Luis

2011-09-01

Diagnosis and classification of mastocytosis is currently based on the World Health Organization (WHO) criteria. Here, we evaluate the utility of the WHO criteria for the diagnosis and classification of a large series of mastocytosis patients (n=133), and propose a new algorithm that could be routinely applied for refined diagnosis and classification of the disease. Our results confirm the utility of the WHO criteria and provide evidence for the need of additional information for (1) a more precise diagnosis of mastocytosis, (2) specific identification of new forms of the disease, (3) the differential diagnosis between cutaneous mastocytosis vs systemic mastocytosis, and (4) improved distinction between indolent systemic mastocytosis and aggressive systemic mastocytosis. Based on our results, a new algorithm is proposed for a better diagnostic definition and prognostic classification of mastocytosis, as confirmed prospectively in an independent validation series of 117 mastocytosis patients.

Starmind: A Fuzzy Logic Knowledge-Based System for the Automated Classification of Stars in the MK System

NASA Astrophysics Data System (ADS)

Manteiga, M.; Carricajo, I.; Rodríguez, A.; Dafonte, C.; Arcay, B.

2009-02-01

Astrophysics is evolving toward a more rational use of costly observational data by intelligently exploiting the large terrestrial and spatial astronomical databases. In this paper, we present a study showing the suitability of an expert system to perform the classification of stellar spectra in the Morgan and Keenan (MK) system. Using the formalism of artificial intelligence for the development of such a system, we propose a rules' base that contains classification criteria and confidence grades, all integrated in an inference engine that emulates human reasoning by means of a hierarchical decision rules tree that also considers the uncertainty factors associated with rules. Our main objective is to illustrate the formulation and development of such a system for an astrophysical classification problem. An extensive spectral database of MK standard spectra has been collected and used as a reference to determine the spectral indexes that are suitable for classification in the MK system. It is shown that by considering 30 spectral indexes and associating them with uncertainty factors, we can find an accurate diagnose in MK types of a particular spectrum. The system was evaluated against the NOAO-INDO-US spectral catalog.

Diagnosis and Treatment Strategy of Achalasia Subtypes and Esophagogastric Junction Outflow Obstruction Based on High-Resolution Manometry.

PubMed

Ihara, Eikichi; Muta, Kazumasa; Fukaura, Keita; Nakamura, Kazuhiko

2017-01-01

Based on Chicago Classification version 3.0, the disorders of esophagogastric junction outflow obstruction (EGJOO) include achalasia (types I, II and III) and EGJOO. Although no curative treatments are currently available for the treatment of the disorders of EGJOO, medical treatments, endoscopic pneumatic dilation (PD), laparoscopic Heller myotomy (LHM), and per-oral endoscopic myotomy (POEM) are usually the sought-after modes of treatment. Since the etiology and pathogenesis might vary depending on the types of EGJOO disorders, treatment strategies should be considered based on those subtypes. Based on the accumulated evidences, the treatment strategies of our institution are as follows: effects of medical treatments on achalasia are limited. Either PD or LHM/POEM can be considered a first-line in achalasia type I, according to the patient's wish. PD and POEM can be considered first-line in achalasia types II and III, respectively. Conversely, In EGJOO, medical treatments including drugs like acotiamide and/or diltiazem can be tested as a first-line, and PD and POEM will be considered second and third-line treatments, respectively. Key Messages: The classification of subtypes based on high-resolution manometry will help us consider which treatment option can be selected as a first-line treatment depending upon the subtypes of disorders of EGJOO. Acotiamide has the potential to cure patients with EGJOO. © 2016 S. Karger AG, Basel.

The software application and classification algorithms for welds radiograms analysis

NASA Astrophysics Data System (ADS)

Sikora, R.; Chady, T.; Baniukiewicz, P.; Grzywacz, B.; Lopato, P.; Misztal, L.; Napierała, L.; Piekarczyk, B.; Pietrusewicz, T.; Psuj, G.

2013-01-01

The paper presents a software implementation of an Intelligent System for Radiogram Analysis (ISAR). The system has to support radiologists in welds quality inspection. The image processing part of software with a graphical user interface and a welds classification part are described with selected classification results. Classification was based on a few algorithms: an artificial neural network, a k-means clustering, a simplified k-means and a rough sets theory.

[Research progress in molecular classification of gastric cancer].

PubMed

Zhou, Menglong; Li, Guichao; Zhang, Zhen

2016-09-25

Gastric cancer(GC) is a highly heterogeneous malignancy. The present widely used histopathological classifications have gradually failed to meet the needs of individualized diagnosis and treatment. Development of technologies such as microarray and next-generation sequencing (NGS) has allowed GC to be studied at the molecular level. Mechanisms about tumorigenesis and progression of GC can be elucidated in the aspects of gene mutations, chromosomal alterations, transcriptional and epigenetic changes, on the basis of which GC can be divided into several subtypes. The classifications of Tan's, Lei's, TCGA and ACRG are relatively comprehensive. Especially the TCGA and ACRG classifications have large sample size and abundant molecular profiling data, thus, the genomic characteristics of GC can be depicted more accurately. However, significant differences between both classifications still exist so that they cannot be substituted for each other. So far there is no widely accepted molecular classification of GC. Compared with TCGA classification, ACRG system may have more clinical significance in Chinese GC patients since the samples are mostly from Asian population and show better association with prognosis. The molecular classification of GC may provide the theoretical and experimental basis for early diagnosis, therapeutic efficacy prediction and treatment stratification while their clinical application is still limited. Future work should involve the application of molecular classifications in the clinical settings for improving the medical management of GC.

Extracting genetic alteration information for personalized cancer therapy from ClinicalTrials.gov

PubMed Central

Xu, Jun; Lee, Hee-Jin; Zeng, Jia; Wu, Yonghui; Zhang, Yaoyun; Huang, Liang-Chin; Johnson, Amber; Holla, Vijaykumar; Bailey, Ann M; Cohen, Trevor; Meric-Bernstam, Funda; Bernstam, Elmer V

2016-01-01

Objective: Clinical trials investigating drugs that target specific genetic alterations in tumors are important for promoting personalized cancer therapy. The goal of this project is to create a knowledge base of cancer treatment trials with annotations about genetic alterations from ClinicalTrials.gov. Methods: We developed a semi-automatic framework that combines advanced text-processing techniques with manual review to curate genetic alteration information in cancer trials. The framework consists of a document classification system to identify cancer treatment trials from ClinicalTrials.gov and an information extraction system to extract gene and alteration pairs from the Title and Eligibility Criteria sections of clinical trials. By applying the framework to trials at ClinicalTrials.gov, we created a knowledge base of cancer treatment trials with genetic alteration annotations. We then evaluated each component of the framework against manually reviewed sets of clinical trials and generated descriptive statistics of the knowledge base. Results and Discussion: The automated cancer treatment trial identification system achieved a high precision of 0.9944. Together with the manual review process, it identified 20 193 cancer treatment trials from ClinicalTrials.gov. The automated gene-alteration extraction system achieved a precision of 0.8300 and a recall of 0.6803. After validation by manual review, we generated a knowledge base of 2024 cancer trials that are labeled with specific genetic alteration information. Analysis of the knowledge base revealed the trend of increased use of targeted therapy for cancer, as well as top frequent gene-alteration pairs of interest. We expect this knowledge base to be a valuable resource for physicians and patients who are seeking information about personalized cancer therapy. PMID:27013523

Extracting genetic alteration information for personalized cancer therapy from ClinicalTrials.gov.

PubMed

Xu, Jun; Lee, Hee-Jin; Zeng, Jia; Wu, Yonghui; Zhang, Yaoyun; Huang, Liang-Chin; Johnson, Amber; Holla, Vijaykumar; Bailey, Ann M; Cohen, Trevor; Meric-Bernstam, Funda; Bernstam, Elmer V; Xu, Hua

2016-07-01

Clinical trials investigating drugs that target specific genetic alterations in tumors are important for promoting personalized cancer therapy. The goal of this project is to create a knowledge base of cancer treatment trials with annotations about genetic alterations from ClinicalTrials.gov. We developed a semi-automatic framework that combines advanced text-processing techniques with manual review to curate genetic alteration information in cancer trials. The framework consists of a document classification system to identify cancer treatment trials from ClinicalTrials.gov and an information extraction system to extract gene and alteration pairs from the Title and Eligibility Criteria sections of clinical trials. By applying the framework to trials at ClinicalTrials.gov, we created a knowledge base of cancer treatment trials with genetic alteration annotations. We then evaluated each component of the framework against manually reviewed sets of clinical trials and generated descriptive statistics of the knowledge base. The automated cancer treatment trial identification system achieved a high precision of 0.9944. Together with the manual review process, it identified 20 193 cancer treatment trials from ClinicalTrials.gov. The automated gene-alteration extraction system achieved a precision of 0.8300 and a recall of 0.6803. After validation by manual review, we generated a knowledge base of 2024 cancer trials that are labeled with specific genetic alteration information. Analysis of the knowledge base revealed the trend of increased use of targeted therapy for cancer, as well as top frequent gene-alteration pairs of interest. We expect this knowledge base to be a valuable resource for physicians and patients who are seeking information about personalized cancer therapy. © The Author 2016. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Identification of chronic rhinosinusitis phenotypes using cluster analysis.

PubMed

Soler, Zachary M; Hyer, J Madison; Ramakrishnan, Viswanathan; Smith, Timothy L; Mace, Jess; Rudmik, Luke; Schlosser, Rodney J

2015-05-01

Current clinical classifications of chronic rhinosinusitis (CRS) have been largely defined based upon preconceived notions of factors thought to be important, such as polyp or eosinophil status. Unfortunately, these classification systems have little correlation with symptom severity or treatment outcomes. Unsupervised clustering can be used to identify phenotypic subgroups of CRS patients, describe clinical differences in these clusters and define simple algorithms for classification. A multi-institutional, prospective study of 382 patients with CRS who had failed initial medical therapy completed the Sino-Nasal Outcome Test (SNOT-22), Rhinosinusitis Disability Index (RSDI), Medical Outcomes Study Short Form-12 (SF-12), Pittsburgh Sleep Quality Index (PSQI), and Patient Health Questionnaire (PHQ-2). Objective measures of CRS severity included Brief Smell Identification Test (B-SIT), CT, and endoscopy scoring. All variables were reduced and unsupervised hierarchical clustering was performed. After clusters were defined, variations in medication usage were analyzed. Discriminant analysis was performed to develop a simplified, clinically useful algorithm for clustering. Clustering was largely determined by age, severity of patient reported outcome measures, depression, and fibromyalgia. CT and endoscopy varied somewhat among clusters. Traditional clinical measures, including polyp/atopic status, prior surgery, B-SIT and asthma, did not vary among clusters. A simplified algorithm based upon productivity loss, SNOT-22 score, and age predicted clustering with 89% accuracy. Medication usage among clusters did vary significantly. A simplified algorithm based upon hierarchical clustering is able to classify CRS patients and predict medication usage. Further studies are warranted to determine if such clustering predicts treatment outcomes. © 2015 ARS-AAOA, LLC.

Validation of a new classification system for skin tears.

PubMed

LeBlanc, Kimberly; Baranoski, Sharon; Holloway, Samantha; Langemo, Diane

2013-06-01

The aim of this study was to validate and establish reliability of the International Skin Tear classification system. A consensus panel of 12 internationally recognized key opinion leaders convened in 2011 to establish consensus statements on the prevention, prediction, assessment, and treatment of skin tears. Subsequently, a new skin tear classification system was proposed. The system was then tested for interrater and intrarater reliability between the experts before being tested more widely on a sample of 327 individuals from the United States, Canada, and Europe. The results of the study indicated a substantial level of agreement for the expert panel (Fleiss κ = 0.619; 2-month follow-up = 0.653). Intrarater reliability was high (Cohen κ = 0.877). Interrater reliability was moderate (Fleiss κ = 0.555) for healthcare professionals (n = 303) and fair for non-health professionals (Fleiss κ = 0.338; n = 24). This international study established the reliability and validity of a new classification system for skin tears.

Peripheral vascular tumors and vascular malformations: imaging (magnetic resonance imaging and conventional angiography), pathologic correlation and treatment options.

PubMed

El-Merhi, Fadi; Garg, Deepak; Cura, Marco; Ghaith, Ola

2013-02-01

Vascular anomalies are classified into vascular tumors (infantile hemangioma) and vascular malformations. Vascular malformations are divided into slow flow and high flow subtypes. Magnetic resonance imaging helps in classification and assessing extent and distribution. Conventional angiography also known as digital subtraction angiography is pivotal in assessment of fine vascular details and treatment planning. Imaging correlates well with histopathology. We review recent development in imaging techniques of various vascular anomalies most of which are affecting the peripheral system which potentially may broaden understanding of their diagnosis, classification and treatment.

A personality classification system for eating disorders: a longitudinal study.

PubMed

Thompson-Brenner, Heather; Eddy, Kamryn T; Franko, Debra L; Dorer, David J; Vashchenko, Maryna; Kass, Andrea E; Herzog, David B

2008-01-01

Studies of eating disorders (EDs) suggest that empirically derived personality subtypes may explain heterogeneity in ED samples that is not captured by the current diagnostic system. Longitudinal outcomes for personality subtypes have not been examined. In this study, personality pathology was assessed by clinical interview in 213 individuals with anorexia nervosa and bulimia nervosa at baseline. Interview data on EDs, comorbid diagnoses, global functioning, and treatment utilization were collected at baseline and at 6-month follow-up intervals over a median of 9 years. Q-factor analysis of the participants based on personality items produced a 5-prototype system, including high-functioning, behaviorally dysregulated, emotionally dysregulated, avoidant-insecure, and obsessional-sensitive types. Dimensional prototype scores were associated with baseline functioning and longitudinal outcome. Avoidant-Insecure scores showed consistent associations with poor functioning and outcome, including failure to show ED improvement, poor global functioning after 5 years, and high treatment utilization after 5 years. Behavioral dysregulation was associated with poor baseline functioning but did not show strong associations with ED or global outcome when histories of major depression and substance use disorder were covaried. Emotional dysregulation and obsessional-sensitivity were not associated with negative outcomes. High-functioning prototype scores were consistently associated with positive outcomes. Longitudinal results support the importance of personality subtypes to ED classification.

A Characteristics-Based Approach to Radioactive Waste Classification in Advanced Nuclear Fuel Cycles

NASA Astrophysics Data System (ADS)

Djokic, Denia

The radioactive waste classification system currently used in the United States primarily relies on a source-based framework. This has lead to numerous issues, such as wastes that are not categorized by their intrinsic risk, or wastes that do not fall under a category within the framework and therefore are without a legal imperative for responsible management. Furthermore, in the possible case that advanced fuel cycles were to be deployed in the United States, the shortcomings of the source-based classification system would be exacerbated: advanced fuel cycles implement processes such as the separation of used nuclear fuel, which introduce new waste streams of varying characteristics. To be able to manage and dispose of these potential new wastes properly, development of a classification system that would assign appropriate level of management to each type of waste based on its physical properties is imperative. This dissertation explores how characteristics from wastes generated from potential future nuclear fuel cycles could be coupled with a characteristics-based classification framework. A static mass flow model developed under the Department of Energy's Fuel Cycle Research & Development program, called the Fuel-cycle Integration and Tradeoffs (FIT) model, was used to calculate the composition of waste streams resulting from different nuclear fuel cycle choices: two modified open fuel cycle cases (recycle in MOX reactor) and two different continuous-recycle fast reactor recycle cases (oxide and metal fuel fast reactors). This analysis focuses on the impact of waste heat load on waste classification practices, although future work could involve coupling waste heat load with metrics of radiotoxicity and longevity. The value of separation of heat-generating fission products and actinides in different fuel cycles and how it could inform long- and short-term disposal management is discussed. It is shown that the benefits of reducing the short-term fission-product heat load of waste destined for geologic disposal are neglected under the current source-based radioactive waste classification system, and that it is useful to classify waste streams based on how favorable the impact of interim storage is on increasing repository capacity. The need for a more diverse set of waste classes is discussed, and it is shown that the characteristics-based IAEA classification guidelines could accommodate wastes created from advanced fuel cycles more comprehensively than the U.S. classification framework.

Development and validation of a paediatric long-bone fracture classification. A prospective multicentre study in 13 European paediatric trauma centres

PubMed Central

2011-01-01

Background The aim of this study was to develop a child-specific classification system for long bone fractures and to examine its reliability and validity on the basis of a prospective multicentre study. Methods Using the sequentially developed classification system, three samples of between 30 and 185 paediatric limb fractures from a pool of 2308 fractures documented in two multicenter studies were analysed in a blinded fashion by eight orthopaedic surgeons, on a total of 5 occasions. Intra- and interobserver reliability and accuracy were calculated. Results The reliability improved with successive simplification of the classification. The final version resulted in an overall interobserver agreement of κ = 0.71 with no significant difference between experienced and less experienced raters. Conclusions In conclusion, the evaluation of the newly proposed classification system resulted in a reliable and routinely applicable system, for which training in its proper use may further improve the reliability. It can be recommended as a useful tool for clinical practice and offers the option for developing treatment recommendations and outcome predictions in the future. PMID:21548939

21 CFR 862.1815 - Vitamin E test system.

Code of Federal Regulations, 2010 CFR

2010-04-01

...) MEDICAL DEVICES CLINICAL CHEMISTRY AND CLINICAL TOXICOLOGY DEVICES Clinical Chemistry Test Systems § 862... treatment of infants with vitamin E deficiency syndrome. (b) Classification. Class I (general controls). The...

Analysis on Target Detection and Classification in LTE Based Passive Forward Scattering Radar.

PubMed

Raja Abdullah, Raja Syamsul Azmir; Abdul Aziz, Noor Hafizah; Abdul Rashid, Nur Emileen; Ahmad Salah, Asem; Hashim, Fazirulhisyam

2016-09-29

The passive bistatic radar (PBR) system can utilize the illuminator of opportunity to enhance radar capability. By utilizing the forward scattering technique and procedure into the specific mode of PBR can provide an improvement in target detection and classification. The system is known as passive Forward Scattering Radar (FSR). The passive FSR system can exploit the peculiar advantage of the enhancement in forward scatter radar cross section (FSRCS) for target detection. Thus, the aim of this paper is to show the feasibility of passive FSR for moving target detection and classification by experimental analysis and results. The signal source is coming from the latest technology of 4G Long-Term Evolution (LTE) base station. A detailed explanation on the passive FSR receiver circuit, the detection scheme and the classification algorithm are given. In addition, the proposed passive FSR circuit employs the self-mixing technique at the receiver; hence the synchronization signal from the transmitter is not required. The experimental results confirm the passive FSR system's capability for ground target detection and classification. Furthermore, this paper illustrates the first classification result in the passive FSR system. The great potential in the passive FSR system provides a new research area in passive radar that can be used for diverse remote monitoring applications.

Application of wavelet transformation and adaptive neighborhood based modified backpropagation (ANMBP) for classification of brain cancer

NASA Astrophysics Data System (ADS)

Werdiningsih, Indah; Zaman, Badrus; Nuqoba, Barry

2017-08-01

This paper presents classification of brain cancer using wavelet transformation and Adaptive Neighborhood Based Modified Backpropagation (ANMBP). Three stages of the processes, namely features extraction, features reduction, and classification process. Wavelet transformation is used for feature extraction and ANMBP is used for classification process. The result of features extraction is feature vectors. Features reduction used 100 energy values per feature and 10 energy values per feature. Classifications of brain cancer are normal, alzheimer, glioma, and carcinoma. Based on simulation results, 10 energy values per feature can be used to classify brain cancer correctly. The correct classification rate of proposed system is 95 %. This research demonstrated that wavelet transformation can be used for features extraction and ANMBP can be used for classification of brain cancer.

Auto-SEIA: simultaneous optimization of image processing and machine learning algorithms

NASA Astrophysics Data System (ADS)

Negro Maggio, Valentina; Iocchi, Luca

2015-02-01

Object classification from images is an important task for machine vision and it is a crucial ingredient for many computer vision applications, ranging from security and surveillance to marketing. Image based object classification techniques properly integrate image processing and machine learning (i.e., classification) procedures. In this paper we present a system for automatic simultaneous optimization of algorithms and parameters for object classification from images. More specifically, the proposed system is able to process a dataset of labelled images and to return a best configuration of image processing and classification algorithms and of their parameters with respect to the accuracy of classification. Experiments with real public datasets are used to demonstrate the effectiveness of the developed system.

Efficient Fingercode Classification

NASA Astrophysics Data System (ADS)

Sun, Hong-Wei; Law, Kwok-Yan; Gollmann, Dieter; Chung, Siu-Leung; Li, Jian-Bin; Sun, Jia-Guang

In this paper, we present an efficient fingerprint classification algorithm which is an essential component in many critical security application systems e. g. systems in the e-government and e-finance domains. Fingerprint identification is one of the most important security requirements in homeland security systems such as personnel screening and anti-money laundering. The problem of fingerprint identification involves searching (matching) the fingerprint of a person against each of the fingerprints of all registered persons. To enhance performance and reliability, a common approach is to reduce the search space by firstly classifying the fingerprints and then performing the search in the respective class. Jain et al. proposed a fingerprint classification algorithm based on a two-stage classifier, which uses a K-nearest neighbor classifier in its first stage. The fingerprint classification algorithm is based on the fingercode representation which is an encoding of fingerprints that has been demonstrated to be an effective fingerprint biometric scheme because of its ability to capture both local and global details in a fingerprint image. We enhance this approach by improving the efficiency of the K-nearest neighbor classifier for fingercode-based fingerprint classification. Our research firstly investigates the various fast search algorithms in vector quantization (VQ) and the potential application in fingerprint classification, and then proposes two efficient algorithms based on the pyramid-based search algorithms in VQ. Experimental results on DB1 of FVC 2004 demonstrate that our algorithms can outperform the full search algorithm and the original pyramid-based search algorithms in terms of computational efficiency without sacrificing accuracy.

Inter-rater reliability of a modified version of Delitto et al.’s classification-based system for low back pain: a pilot study

PubMed Central

Apeldoorn, Adri T.; van Helvoirt, Hans; Ostelo, Raymond W.; Meihuizen, Hanneke; Kamper, Steven J.; van Tulder, Maurits W.; de Vet, Henrica C. W.

2016-01-01

Study design Observational inter-rater reliability study. Objectives To examine: (1) the inter-rater reliability of a modified version of Delitto et al.’s classification-based algorithm for patients with low back pain; (2) the influence of different levels of familiarity with the system; and (3) the inter-rater reliability of algorithm decisions in patients who clearly fit into a subgroup (clear classifications) and those who do not (unclear classifications). Methods Patients were examined twice on the same day by two of three participating physical therapists with different levels of familiarity with the system. Patients were classified into one of four classification groups. Raters were blind to the others’ classification decision. In order to quantify the inter-rater reliability, percentages of agreement and Cohen’s Kappa were calculated. Results A total of 36 patients were included (clear classification n = 23; unclear classification n = 13). The overall rate of agreement was 53% and the Kappa value was 0·34 [95% confidence interval (CI): 0·11–0·57], which indicated only fair inter-rater reliability. Inter-rater reliability for patients with a clear classification (agreement 52%, Kappa value 0·29) was not higher than for patients with an unclear classification (agreement 54%, Kappa value 0·33). Familiarity with the system (i.e. trained with written instructions and previous research experience with the algorithm) did not improve the inter-rater reliability. Conclusion Our pilot study challenges the inter-rater reliability of the classification procedure in clinical practice. Therefore, more knowledge is needed about factors that affect the inter-rater reliability, in order to improve the clinical applicability of the classification scheme. PMID:27559279

A study of machine-learning-based approaches to extract clinical entities and their assertions from discharge summaries.

PubMed

Jiang, Min; Chen, Yukun; Liu, Mei; Rosenbloom, S Trent; Mani, Subramani; Denny, Joshua C; Xu, Hua

2011-01-01

The authors' goal was to develop and evaluate machine-learning-based approaches to extracting clinical entities-including medical problems, tests, and treatments, as well as their asserted status-from hospital discharge summaries written using natural language. This project was part of the 2010 Center of Informatics for Integrating Biology and the Bedside/Veterans Affairs (VA) natural-language-processing challenge. The authors implemented a machine-learning-based named entity recognition system for clinical text and systematically evaluated the contributions of different types of features and ML algorithms, using a training corpus of 349 annotated notes. Based on the results from training data, the authors developed a novel hybrid clinical entity extraction system, which integrated heuristic rule-based modules with the ML-base named entity recognition module. The authors applied the hybrid system to the concept extraction and assertion classification tasks in the challenge and evaluated its performance using a test data set with 477 annotated notes. Standard measures including precision, recall, and F-measure were calculated using the evaluation script provided by the Center of Informatics for Integrating Biology and the Bedside/VA challenge organizers. The overall performance for all three types of clinical entities and all six types of assertions across 477 annotated notes were considered as the primary metric in the challenge. Systematic evaluation on the training set showed that Conditional Random Fields outperformed Support Vector Machines, and semantic information from existing natural-language-processing systems largely improved performance, although contributions from different types of features varied. The authors' hybrid entity extraction system achieved a maximum overall F-score of 0.8391 for concept extraction (ranked second) and 0.9313 for assertion classification (ranked fourth, but not statistically different than the first three systems) on the test data set in the challenge.

Mixed-phenotype acute leukemia: state-of-the-art of the diagnosis, classification and treatment.

PubMed

Cernan, Martin; Szotkowski, Tomas; Pikalova, Zuzana

2017-09-01

Mixed-phenotype acute leukemia (MPAL) is a heterogeneous group of hematopoietic malignancies in which blasts show markers of multiple developmental lineages and cannot be clearly classified as acute myeloid or lymphoblastic leukemias. Historically, various names and classifications were used for this rare entity accounting for 2-5% of all acute leukemias depending on the diagnostic criterias used. The currently valid classification of myeloid neoplasms and acute leukemia published by the World Health Organization (WHO) in 2016 refers to this group of diseases as MPAL. Because adverse cytogenetic abnormalities are frequently present, MPAL is generally considered a disease with a poor prognosis. Knowledge of its treatment is limited to retrospective analyses of small patient cohorts. So far, no treatment recommendations verified by prospective studies have been published. The reported data suggest that induction therapy for acute lymphoblastic leukemia followed by allogeneic hematopoietic cell transplantation is more effective than induction therapy for acute myeloid leukemia or consolidation chemotherapy. The establishment of cooperative groups and international registries based on the recent WHO criterias are required to ensure further progress in understanding and treatment of MPAL. This review summarizes current knowledge on the diagnosis, classification, prognosis and treatment of MPAL patients.

Prevention of musculoskeletal disorders in workers: classification and health surveillance - statements of the Scientific Committee on Musculoskeletal Disorders of the International Commission on Occupational Health.

PubMed

Hagberg, Mats; Violante, Francesco Saverio; Bonfiglioli, Roberta; Descatha, Alexis; Gold, Judith; Evanoff, Brad; Sluiter, Judith K

2012-06-21

The underlying purpose of this commentary and position paper is to achieve evidence-based recommendations on prevention of work-related musculoskeletal disorders (MSDs). Such prevention can take different forms (primary, secondary and tertiary), occur at different levels (i.e. in a clinical setting, at the workplace, at national level) and involve several types of activities. Members of the Scientific Committee (SC) on MSDs of the International Commission on Occupational Health (ICOH) and other interested scientists and members of the public recently discussed the scientific and clinical future of prevention of (work-related) MSDs during five round-table sessions at two ICOH conferences (in Cape Town, South Africa, in 2009, and in Angers, France, in 2010). Approximately 50 researchers participated in each of the sessions. More specifically, the sessions aimed to discuss new developments since 1996 in measures and classification systems used both in research and in practice, and agree on future needs in the field. The discussion focused on three questions: At what degree of severity does musculoskeletal ill health, and do health problems related to MSDs, in an individual worker or in a group of workers justify preventive action in occupational health? What reliable and valid instruments do we have in research to distinguish 'normal musculoskeletal symptoms' from 'serious musculoskeletal symptoms' in workers? What measures or classification system of musculoskeletal health will we need in the near future to address musculoskeletal health and related work ability? Four new, agreed-upon statements were extrapolated from the discussions: 1. Musculoskeletal discomfort that is at risk of worsening with work activities, and that affects work ability or quality of life, needs to be identified. 2. We need to know our options of actions before identifying workers at risk (providing evidence-based medicine and applying the principle of best practice). 3. Classification systems and measures must include aspects such as the severity, frequency, and intensity of pain, as well as measures of impairment of functioning, which can help in prevention, treatment and prognosis. 4. We need to be aware of economic and/or socio-cultural consequences of classification systems and measures.

Classifying breast cancer surgery: a novel, complexity-based system for oncological, oncoplastic and reconstructive procedures, and proof of principle by analysis of 1225 operations in 1166 patients.

PubMed

Hoffmann, Jürgen; Wallwiener, Diethelm

2009-04-08

One of the basic prerequisites for generating evidence-based data is the availability of classification systems. Attempts to date to classify breast cancer operations have focussed on specific problems, e.g. the avoidance of secondary corrective surgery for surgical defects, rather than taking a generic approach. Starting from an existing, simpler empirical scheme based on the complexity of breast surgical procedures, which was used in-house primarily in operative report-writing, a novel classification of ablative and breast-conserving procedures initially needed to be developed and elaborated systematically. To obtain proof of principle, a prospectively planned analysis of patient records for all major breast cancer-related operations performed at our breast centre in 2005 and 2006 was conducted using the new classification. Data were analysed using basic descriptive statistics such as frequency tables. A novel two-type, six-tier classification system comprising 12 main categories, 13 subcategories and 39 sub-subcategories of oncological, oncoplastic and reconstructive breast cancer-related surgery was successfully developed. Our system permitted unequivocal classification, without exception, of all 1225 procedures performed in 1166 breast cancer patients in 2005 and 2006. Breast cancer-related surgical procedures can be generically classified according to their surgical complexity. Analysis of all major procedures performed at our breast centre during the study period provides proof of principle for this novel classification system. We envisage various applications for this classification, including uses in randomised clinical trials, guideline development, specialist surgical training, continuing professional development as well as quality of care and public health research.

A comparative study: classification vs. user-based collaborative filtering for clinical prediction.

PubMed

Hao, Fang; Blair, Rachael Hageman

2016-12-08

Recommender systems have shown tremendous value for the prediction of personalized item recommendations for individuals in a variety of settings (e.g., marketing, e-commerce, etc.). User-based collaborative filtering is a popular recommender system, which leverages an individuals' prior satisfaction with items, as well as the satisfaction of individuals that are "similar". Recently, there have been applications of collaborative filtering based recommender systems for clinical risk prediction. In these applications, individuals represent patients, and items represent clinical data, which includes an outcome. Application of recommender systems to a problem of this type requires the recasting a supervised learning problem as unsupervised. The rationale is that patients with similar clinical features carry a similar disease risk. As the "Big Data" era progresses, it is likely that approaches of this type will be reached for as biomedical data continues to grow in both size and complexity (e.g., electronic health records). In the present study, we set out to understand and assess the performance of recommender systems in a controlled yet realistic setting. User-based collaborative filtering recommender systems are compared to logistic regression and random forests with different types of imputation and varying amounts of missingness on four different publicly available medical data sets: National Health and Nutrition Examination Survey (NHANES, 2011-2012 on Obesity), Study to Understand Prognoses Preferences Outcomes and Risks of Treatment (SUPPORT), chronic kidney disease, and dermatology data. We also examined performance using simulated data with observations that are Missing At Random (MAR) or Missing Completely At Random (MCAR) under various degrees of missingness and levels of class imbalance in the response variable. Our results demonstrate that user-based collaborative filtering is consistently inferior to logistic regression and random forests with different imputations on real and simulated data. The results warrant caution for the collaborative filtering for the purpose of clinical risk prediction when traditional classification is feasible and practical. CF may not be desirable in datasets where classification is an acceptable alternative. We describe some natural applications related to "Big Data" where CF would be preferred and conclude with some insights as to why caution may be warranted in this context.

A Proposal for a Dimensional Classification System Based on the Shared Features of the DSM-IV Anxiety and Mood Disorders: Implications for Assessment and Treatment

PubMed Central

Brown, Timothy A.; Barlow, David H.

2010-01-01

A wealth of evidence attests to the extensive current and lifetime diagnostic comorbidity of the DSM-IV anxiety and mood disorders. Research has shown that the considerable cross-sectional covariation of DSM-IV emotional disorders is accounted for by common higher-order dimensions such as neuroticism/behavioral inhibition (N/BI) and low positive affect/behavioral activation. Longitudinal studies have indicated that the temporal covariation of these disorders can be explained by changes in N/BI and in some cases, initial levels of N/BI are predictive of the temporal course of emotional disorders. Moreover, the marked phenotypal overlap of the DSM-IV anxiety and mood disorder constructs is a frequent source of diagnostic unreliability (e.g., temporal overlap in the shared features of generalized anxiety disorder and mood disorders, situation specificity of panic attacks in panic disorder and specific phobia). Although dimensional approaches have been considered as a method to address the drawbacks associated with the extant prototypical nosology (e.g., inadequate assessment of individual differences in disorder severity), these proposals do not reconcile key problems in current classification such as modest reliability and high comorbidity. The current paper considers an alternative approach that emphasizes empirically supported common dimensions of emotional disorders over disorder-specific criteria sets. The selection and assessment of these dimensions are discussed along with how these methods could be implemented to promote more reliable and valid diagnosis, prognosis, and treatment planning. For instance, the advantages of this classification system are discussed in context of current transdiagnostic treatment protocols that are efficaciously applied to a variety of disorders by targeting their shared features. PMID:19719339

Proposal of a Classification System for the Assessment and Treatment of Prominent Ear Deformity.

PubMed

Lee, Youngdae; Kim, Young Seok; Lee, Won Jai; Rha, Dong Kyun; Kim, Jiye

2018-06-01

Prominent ear is the most common external ear deformity. To comprehensively treat prominent ear deformity, adequate comprehension of its pathophysiology is crucial. In this article, we analyze cases of prominent ear and suggest a simple classification system and treatment algorithm according to pathophysiology. We retrospectively reviewed a total of 205 Northeast Asian patients' clinical data who underwent an operation for prominent ear deformity. Follow-up assessments were conducted 3, 6, and 12 months after surgery. Prominent ear deformities were classified by diagnostic checkpoints. Class I (simple prominent ear) includes prominent ear that developed with the absence of the antihelix without conchal hypertrophy. Class II (mixed-type prominent ear) is defined as having not only a flat antihelix, but also conchal excess. Class III (conchal-type prominent ear) has an enlarged conchal bowl with a well-developed antihelix. Among the three types of prominent ear, class I was most frequent (162 patients, 81.6%). Class II was observed in 28 patients (13.6%) and class III in 10 patients (4.8%). We used the scaphomastoid suture method for correction of antihelical effacement, the anterior approach conchal resection for correction of conchal hypertrophy, and Bauer's squid incision for lobule prominence. The complication rate was 9.2% including early hematoma, hypersensitivity, and suture extrusion. Unfavorable results occurred in 4% including partial recurrence, overcorrection, and undercorrection. To reduce unfavorable results and avoid recurrence, we propose the use of a classification and treatment algorithm in preoperative evaluation of prominent ear. This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .

System Complexity Reduction via Feature Selection

ERIC Educational Resources Information Center

Deng, Houtao

2011-01-01

This dissertation transforms a set of system complexity reduction problems to feature selection problems. Three systems are considered: classification based on association rules, network structure learning, and time series classification. Furthermore, two variable importance measures are proposed to reduce the feature selection bias in tree…

Spatial-temporal discriminant analysis for ERP-based brain-computer interface.

PubMed

Zhang, Yu; Zhou, Guoxu; Zhao, Qibin; Jin, Jing; Wang, Xingyu; Cichocki, Andrzej

2013-03-01

Linear discriminant analysis (LDA) has been widely adopted to classify event-related potential (ERP) in brain-computer interface (BCI). Good classification performance of the ERP-based BCI usually requires sufficient data recordings for effective training of the LDA classifier, and hence a long system calibration time which however may depress the system practicability and cause the users resistance to the BCI system. In this study, we introduce a spatial-temporal discriminant analysis (STDA) to ERP classification. As a multiway extension of the LDA, the STDA method tries to maximize the discriminant information between target and nontarget classes through finding two projection matrices from spatial and temporal dimensions collaboratively, which reduces effectively the feature dimensionality in the discriminant analysis, and hence decreases significantly the number of required training samples. The proposed STDA method was validated with dataset II of the BCI Competition III and dataset recorded from our own experiments, and compared to the state-of-the-art algorithms for ERP classification. Online experiments were additionally implemented for the validation. The superior classification performance in using few training samples shows that the STDA is effective to reduce the system calibration time and improve the classification accuracy, thereby enhancing the practicability of ERP-based BCI.

A mutual information-Dempster-Shafer based decision ensemble system for land cover classification of hyperspectral data

NASA Astrophysics Data System (ADS)

Pahlavani, Parham; Bigdeli, Behnaz

2017-12-01

Hyperspectral images contain extremely rich spectral information that offer great potential to discriminate between various land cover classes. However, these images are usually composed of tens or hundreds of spectrally close bands, which result in high redundancy and great amount of computation time in hyperspectral classification. Furthermore, in the presence of mixed coverage pixels, crisp classifiers produced errors, omission and commission. This paper presents a mutual information-Dempster-Shafer system through an ensemble classification approach for classification of hyperspectral data. First, mutual information is applied to split data into a few independent partitions to overcome high dimensionality. Then, a fuzzy maximum likelihood classifies each band subset. Finally, Dempster-Shafer is applied to fuse the results of the fuzzy classifiers. In order to assess the proposed method, a crisp ensemble system based on a support vector machine as the crisp classifier and weighted majority voting as the crisp fusion method are applied on hyperspectral data. Furthermore, a dimension reduction system is utilized to assess the effectiveness of mutual information band splitting of the proposed method. The proposed methodology provides interesting conclusions on the effectiveness and potentiality of mutual information-Dempster-Shafer based classification of hyperspectral data.

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.

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

Searching bioremediation patents through Cooperative Patent Classification (CPC).

PubMed

Prasad, Rajendra

2016-03-01

Patent classification systems have traditionally evolved independently at each patent jurisdiction to classify patents handled by their examiners to be able to search previous patents while dealing with new patent applications. As patent databases maintained by them went online for free access to public as also for global search of prior art by examiners, the need arose for a common platform and uniform structure of patent databases. The diversity of different classification, however, posed problems of integrating and searching relevant patents across patent jurisdictions. To address this problem of comparability of data from different sources and searching patents, WIPO in the recent past developed what is known as International Patent Classification (IPC) system which most countries readily adopted to code their patents with IPC codes along with their own codes. The Cooperative Patent Classification (CPC) is the latest patent classification system based on IPC/European Classification (ECLA) system, developed by the European Patent Office (EPO) and the United States Patent and Trademark Office (USPTO) which is likely to become a global standard. This paper discusses this new classification system with reference to patents on bioremediation.

Building a common pipeline for rule-based document classification.

PubMed

Patterson, Olga V; Ginter, Thomas; DuVall, Scott L

2013-01-01

Instance-based classification of clinical text is a widely used natural language processing task employed as a step for patient classification, document retrieval, or information extraction. Rule-based approaches rely on concept identification and context analysis in order to determine the appropriate class. We propose a five-step process that enables even small research teams to develop simple but powerful rule-based NLP systems by taking advantage of a common UIMA AS based pipeline for classification. Our proposed methodology coupled with the general-purpose solution provides researchers with access to the data locked in clinical text in cases of limited human resources and compact timelines.

An online sleep apnea detection method based on recurrence quantification analysis.

PubMed

Nguyen, Hoa Dinh; Wilkins, Brek A; Cheng, Qi; Benjamin, Bruce Allen

2014-07-01

This paper introduces an online sleep apnea detection method based on heart rate complexity as measured by recurrence quantification analysis (RQA) statistics of heart rate variability (HRV) data. RQA statistics can capture nonlinear dynamics of a complex cardiorespiratory system during obstructive sleep apnea. In order to obtain a more robust measurement of the nonstationarity of the cardiorespiratory system, we use different fixed amount of neighbor thresholdings for recurrence plot calculation. We integrate a feature selection algorithm based on conditional mutual information to select the most informative RQA features for classification, and hence, to speed up the real-time classification process without degrading the performance of the system. Two types of binary classifiers, i.e., support vector machine and neural network, are used to differentiate apnea from normal sleep. A soft decision fusion rule is developed to combine the results of these classifiers in order to improve the classification performance of the whole system. Experimental results show that our proposed method achieves better classification results compared with the previous recurrence analysis-based approach. We also show that our method is flexible and a strong candidate for a real efficient sleep apnea detection system.

A wavelet-based technique to predict treatment outcome for Major Depressive Disorder.

PubMed

Mumtaz, Wajid; Xia, Likun; Mohd Yasin, Mohd Azhar; Azhar Ali, Syed Saad; Malik, Aamir Saeed

2017-01-01

Treatment management for Major Depressive Disorder (MDD) has been challenging. However, electroencephalogram (EEG)-based predictions of antidepressant's treatment outcome may help during antidepressant's selection and ultimately improve the quality of life for MDD patients. In this study, a machine learning (ML) method involving pretreatment EEG data was proposed to perform such predictions for Selective Serotonin Reuptake Inhibitor (SSRIs). For this purpose, the acquisition of experimental data involved 34 MDD patients and 30 healthy controls. Consequently, a feature matrix was constructed involving time-frequency decomposition of EEG data based on wavelet transform (WT) analysis, termed as EEG data matrix. However, the resultant EEG data matrix had high dimensionality. Therefore, dimension reduction was performed based on a rank-based feature selection method according to a criterion, i.e., receiver operating characteristic (ROC). As a result, the most significant features were identified and further be utilized during the training and testing of a classification model, i.e., the logistic regression (LR) classifier. Finally, the LR model was validated with 100 iterations of 10-fold cross-validation (10-CV). The classification results were compared with short-time Fourier transform (STFT) analysis, and empirical mode decompositions (EMD). The wavelet features extracted from frontal and temporal EEG data were found statistically significant. In comparison with other time-frequency approaches such as the STFT and EMD, the WT analysis has shown highest classification accuracy, i.e., accuracy = 87.5%, sensitivity = 95%, and specificity = 80%. In conclusion, significant wavelet coefficients extracted from frontal and temporal pre-treatment EEG data involving delta and theta frequency bands may predict antidepressant's treatment outcome for the MDD patients.

Kyoto global consensus report on Helicobacter pylori gastritis.

PubMed

Sugano, Kentaro; Tack, Jan; Kuipers, Ernst J; Graham, David Y; El-Omar, Emad M; Miura, Soichiro; Haruma, Ken; Asaka, Masahiro; Uemura, Naomi; Malfertheiner, Peter

2015-09-01

To present results of the Kyoto Global Consensus Meeting, which was convened to develop global consensus on (1) classification of chronic gastritis and duodenitis, (2) clinical distinction of dyspepsia caused by Helicobacter pylori from functional dyspepsia, (3) appropriate diagnostic assessment of gastritis and (4) when, whom and how to treat H. pylori gastritis. Twenty-three clinical questions addressing the above-mentioned four domains were drafted for which expert panels were asked to formulate relevant statements. A Delphi method using an anonymous electronic system was adopted to develop the consensus, the level of which was predefined as ≥80%. Final modifications of clinical questions and consensus were achieved at the face-to-face meeting in Kyoto. All 24 statements for 22 clinical questions after extensive modifications and omission of one clinical question were achieved with a consensus level of >80%. To better organise classification of gastritis and duodenitis based on aetiology, a new classification of gastritis and duodenitis is recommended for the 11th international classification. A new category of H. pylori-associated dyspepsia together with a diagnostic algorithm was proposed. The adoption of grading systems for gastric cancer risk stratification, and modern image-enhancing endoscopy for the diagnosis of gastritis, were recommended. Treatment to eradicate H. pylori infection before preneoplastic changes develop, if feasible, was recommended to minimise the risk of more serious complications of the infection. A global consensus for gastritis was developed for the first time, which will be the basis for an international classification system and for further research on the subject. 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.

Assimilation of a knowledge base and physical models to reduce errors in passive-microwave classifications of sea ice

NASA Technical Reports Server (NTRS)

Maslanik, J. A.; Key, J.

1992-01-01

An expert system framework has been developed to classify sea ice types using satellite passive microwave data, an operational classification algorithm, spatial and temporal information, ice types estimated from a dynamic-thermodynamic model, output from a neural network that detects the onset of melt, and knowledge about season and region. The rule base imposes boundary conditions upon the ice classification, modifies parameters in the ice algorithm, determines a `confidence' measure for the classified data, and under certain conditions, replaces the algorithm output with model output. Results demonstrate the potential power of such a system for minimizing overall error in the classification and for providing non-expert data users with a means of assessing the usefulness of the classification results for their applications.

Classification and authentication of unknown water samples using machine learning algorithms.

PubMed

Kundu, Palash K; Panchariya, P C; Kundu, Madhusree

2011-07-01

This paper proposes the development of water sample classification and authentication, in real life which is based on machine learning algorithms. The proposed techniques used experimental measurements from a pulse voltametry method which is based on an electronic tongue (E-tongue) instrumentation system with silver and platinum electrodes. E-tongue include arrays of solid state ion sensors, transducers even of different types, data collectors and data analysis tools, all oriented to the classification of liquid samples and authentication of unknown liquid samples. The time series signal and the corresponding raw data represent the measurement from a multi-sensor system. The E-tongue system, implemented in a laboratory environment for 6 numbers of different ISI (Bureau of Indian standard) certified water samples (Aquafina, Bisleri, Kingfisher, Oasis, Dolphin, and McDowell) was the data source for developing two types of machine learning algorithms like classification and regression. A water data set consisting of 6 numbers of sample classes containing 4402 numbers of features were considered. A PCA (principal component analysis) based classification and authentication tool was developed in this study as the machine learning component of the E-tongue system. A proposed partial least squares (PLS) based classifier, which was dedicated as well; to authenticate a specific category of water sample evolved out as an integral part of the E-tongue instrumentation system. The developed PCA and PLS based E-tongue system emancipated an overall encouraging authentication percentage accuracy with their excellent performances for the aforesaid categories of water samples. Copyright © 2011 ISA. Published by Elsevier Ltd. All rights reserved.

Meta-learning framework applied in bioinformatics inference system design.

PubMed

Arredondo, Tomás; Ormazábal, Wladimir

2015-01-01

This paper describes a meta-learner inference system development framework which is applied and tested in the implementation of bioinformatic inference systems. These inference systems are used for the systematic classification of the best candidates for inclusion in bacterial metabolic pathway maps. This meta-learner-based approach utilises a workflow where the user provides feedback with final classification decisions which are stored in conjunction with analysed genetic sequences for periodic inference system training. The inference systems were trained and tested with three different data sets related to the bacterial degradation of aromatic compounds. The analysis of the meta-learner-based framework involved contrasting several different optimisation methods with various different parameters. The obtained inference systems were also contrasted with other standard classification methods with accurate prediction capabilities observed.

International consensus for neuroblastoma molecular diagnostics: report from the International Neuroblastoma Risk Group (INRG) Biology Committee

PubMed Central

Ambros, P F; Ambros, I M; Brodeur, G M; Haber, M; Khan, J; Nakagawara, A; Schleiermacher, G; Speleman, F; Spitz, R; London, W B; Cohn, S L; Pearson, A D J; Maris, J M

2009-01-01

Neuroblastoma serves as a paradigm for utilising tumour genomic data for determining patient prognosis and treatment allocation. However, before the establishment of the International Neuroblastoma Risk Group (INRG) Task Force in 2004, international consensus on markers, methodology, and data interpretation did not exist, compromising the reliability of decisive genetic markers and inhibiting translational research efforts. The objectives of the INRG Biology Committee were to identify highly prognostic genetic aberrations to be included in the new INRG risk classification schema and to develop precise definitions, decisive biomarkers, and technique standardisation. The review of the INRG database (n=8800 patients) by the INRG Task Force finally enabled the identification of the most significant neuroblastoma biomarkers. In addition, the Biology Committee compared the standard operating procedures of different cooperative groups to arrive at international consensus for methodology, nomenclature, and future directions. Consensus was reached to include MYCN status, 11q23 allelic status, and ploidy in the INRG classification system on the basis of an evidence-based review of the INRG database. Standardised operating procedures for analysing these genetic factors were adopted, and criteria for proper nomenclature were developed. Neuroblastoma treatment planning is highly dependant on tumour cell genomic features, and it is likely that a comprehensive panel of DNA-based biomarkers will be used in future risk assignment algorithms applying genome-wide techniques. Consensus on methodology and interpretation is essential for uniform INRG classification and will greatly facilitate international and cooperative clinical and translational research studies. PMID:19401703

Perspectives on current tumor-node-metastasis (TNM) staging of cancers of the colon and rectum.

PubMed

Hu, Huankai; Krasinskas, Alyssa; Willis, Joseph

2011-08-01

Improvements in classifications of cancers based on discovery and validation of important histopathological parameters and new molecular markers continue unabated. Though still not perfect, recent updates of classification schemes in gastrointestinal oncology by the American Joint Commission on Cancer (tumor-node-metastasis [TNM] staging) and the World Health Organization further stratify patients and guide optimization of treatment strategies and better predict patient outcomes. These updates recognize the heterogeneity of patient populations with significant subgrouping of each tumor stage and use of tumor deposits to significantly "up-stage" some cancers; change staging parameters for subsets of IIIB and IIIC cancers; and introduce of several new subtypes of colon carcinomas. By the nature of the process, recent discoveries that are important to improving even routine standards of patient care, especially new advances in molecular medicine, are not incorporated into these systems. Nonetheless, these classifications significantly advance clinical standards and are welcome enhancements to our current methods of cancer reporting. Copyright © 2011 Elsevier Inc. All rights reserved.

Using the International Classification of Functioning, Disability, and Health to identify outcome domains for a core outcome set for aphasia: a comparison of stakeholder perspectives.

PubMed

Wallace, Sarah J; Worrall, Linda; Rose, Tanya; Le Dorze, Guylaine

2017-11-12

This study synthesised the findings of three separate consensus processes exploring the perspectives of key stakeholder groups about important aphasia treatment outcomes. This process was conducted to generate recommendations for outcome domains to be included in a core outcome set for aphasia treatment trials. International Classification of Functioning, Disability, and Health codes were examined to identify where the groups of: (1) people with aphasia, (2) family members, (3) aphasia researchers, and (4) aphasia clinicians/managers, demonstrated congruence in their perspectives regarding important treatment outcomes. Codes were contextualized using qualitative data. Congruence across three or more stakeholder groups was evident for ICF chapters: Mental functions; Communication; and Services, systems, and policies. Quality of life was explicitly identified by clinicians/managers and researchers, while people with aphasia and their families identified outcomes known to be determinants of quality of life. Core aphasia outcomes include: language, emotional wellbeing, communication, patient-reported satisfaction with treatment and impact of treatment, and quality of life. International Classification of Functioning, Disability, and Health coding can be used to compare stakeholder perspectives and identify domains for core outcome sets. Pairing coding with qualitative data may ensure important nuances of meaning are retained. Implications for rehabilitation The outcomes measured in treatment research should be relevant to stakeholders and support health care decision making. Core outcome sets (agreed, minimum set of outcomes, and outcome measures) are increasingly being used to ensure the relevancy and consistency of the outcomes measured in treatment studies. Important aphasia treatment outcomes span all components of the International Classification of Functioning, Disability, and Health. Stakeholders demonstrated congruence in the identification of important outcomes which related Mental functions; Communication; Services, systems, and policies; and Quality of life. A core outcome set for aphasia treatment research should include measures relating to: language, emotional wellbeing, communication, patient-reported satisfaction with treatment and impact of treatment, and quality of life. Coding using the International Classification of Functioning, Disability, and Health, presents a novel methodology for the comparison of stakeholder perspectives to inform recommendations for outcome constructs to be included in a core outcome set. Coding can be paired with qualitative data to ensure nuances of meaning are retained.

Numeric pathologic lymph node classification shows prognostic superiority to topographic pN classification in esophageal squamous cell carcinoma.

PubMed

Sugawara, Kotaro; Yamashita, Hiroharu; Uemura, Yukari; Mitsui, Takashi; Yagi, Koichi; Nishida, Masato; Aikou, Susumu; Mori, Kazuhiko; Nomura, Sachiyo; Seto, Yasuyuki

2017-10-01

The current eighth tumor node metastasis lymph node category pathologic lymph node staging system for esophageal squamous cell carcinoma is based solely on the number of metastatic nodes and does not consider anatomic distribution. We aimed to assess the prognostic capability of the eighth tumor node metastasis pathologic lymph node staging system (numeric-based) compared with the 11th Japan Esophageal Society (topography-based) pathologic lymph node staging system in patients with esophageal squamous cell carcinoma. We retrospectively reviewed the clinical records of 289 patients with esophageal squamous cell carcinoma who underwent esophagectomy with extended lymph node dissection during the period from January 2006 through June 2016. We compared discrimination abilities for overall survival, recurrence-free survival, and cancer-specific survival between these 2 staging systems using C-statistics. The median number of dissected and metastatic nodes was 61 (25% to 75% quartile range, 45 to 79) and 1 (25% to 75% quartile range, 0 to 3), respectively. The eighth tumor node metastasis pathologic lymph node staging system had a greater ability to accurately determine overall survival (C-statistics: tumor node metastasis classification, 0.69, 95% confidence interval, 0.62-0.76; Japan Esophageal Society classification; 0.65, 95% confidence interval, 0.58-0.71; P = .014) and cancer-specific survival (C-statistics: tumor node metastasis classification, 0.78, 95% confidence interval, 0.70-0.87; Japan Esophageal Society classification; 0.72, 95% confidence interval, 0.64-0.80; P = .018). Rates of total recurrence rose as the eighth tumor node metastasis pathologic lymph node stage increased, while stratification of patients according to the topography-based node classification system was not feasible. Numeric nodal staging is an essential tool for stratifying the oncologic outcomes of patients with esophageal squamous cell carcinoma even in the cohort in which adequate numbers of lymph nodes were harvested. Copyright © 2017 Elsevier Inc. All rights reserved.

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.

Optimizing Input/Output Using Adaptive File System Policies

NASA Technical Reports Server (NTRS)

Madhyastha, Tara M.; Elford, Christopher L.; Reed, Daniel A.

1996-01-01

Parallel input/output characterization studies and experiments with flexible resource management algorithms indicate that adaptivity is crucial to file system performance. In this paper we propose an automatic technique for selecting and refining file system policies based on application access patterns and execution environment. An automatic classification framework allows the file system to select appropriate caching and pre-fetching policies, while performance sensors provide feedback used to tune policy parameters for specific system environments. To illustrate the potential performance improvements possible using adaptive file system policies, we present results from experiments involving classification-based and performance-based steering.

Classification of cancerous cells based on the one-class problem approach

NASA Astrophysics Data System (ADS)

Murshed, Nabeel A.; Bortolozzi, Flavio; Sabourin, Robert

1996-03-01

One of the most important factors in reducing the effect of cancerous diseases is the early diagnosis, which requires a good and a robust method. With the advancement of computer technologies and digital image processing, the development of a computer-based system has become feasible. In this paper, we introduce a new approach for the detection of cancerous cells. This approach is based on the one-class problem approach, through which the classification system need only be trained with patterns of cancerous cells. This reduces the burden of the training task by about 50%. Based on this approach, a computer-based classification system is developed, based on the Fuzzy ARTMAP neural networks. Experimental results were performed using a set of 542 patterns taken from a sample of breast cancer. Results of the experiment show 98% correct identification of cancerous cells and 95% correct identification of non-cancerous cells.

Expert Systems: Implications for the Diagnosis and Treatment of Learning Disabilities.

ERIC Educational Resources Information Center

Hofmeister, Alan M.; Lubke, Margaret M.

1986-01-01

Expert systems are briefly reviewed and applications in special education diagnosis and classification are described. Future applications are noted to include text interpretation and pupil performance monitoring. (CL)

Occupational Disease Registries-Characteristics and Experiences.

PubMed

Davoodi, Somayeh; Haghighi, Khosro Sadeghniat; Kalhori, Sharareh Rostam Niakan; Hosseini, Narges Shams; Mohammadzadeh, Zeinab; Safdari, Reza

2017-06-01

Due to growth of occupational diseases and also increase of public awareness about their consequences, attention to various aspects of diseases and improve occupational health and safety has found great importance. Therefore, there is the need for appropriate information management tools such as registries in order to recognitions of diseases patterns and then making decision about prevention, early detection and treatment of them. These registries have different characteristics in various countries according to their occupational health priorities. Aim of this study is evaluate dimensions of occupational diseases registries including objectives, data sources, responsible institutions, minimum data set, classification systems and process of registration in different countries. In this study, the papers were searched using the MEDLINE (PubMed) Google scholar, Scopus, ProQuest and Google. The search was done based on keyword in English for all motor engines including "occupational disease", "work related disease", "surveillance", "reporting", "registration system" and "registry" combined with name of the countries including all subheadings. After categorizing search findings in tables, results were compared with each other. Important aspects of the registries studied in ten countries including Finland, France, United Kingdom, Australia, Czech Republic, Malaysia, United States, Singapore, Russia and Turkey. The results show that surveyed countries have statistical, treatment and prevention objectives. Data sources in almost the rest of registries were physicians and employers. The minimum data sets in most of them consist of information about patient, disease, occupation and employer. Some of countries have special occupational related classification systems for themselves and some of them apply international classification systems such as ICD-10. Finally, the process of registration system was different in countries. Because occupational diseases are often preventable, but not curable, it is necessary to all countries, to consider prevention and early detection of occupational diseases as the objectives of their registry systems. Also it is recommended that all countries reach an agreement about global characteristics of occupational disease registries. This enables country to compare their data at international levels.

Classification and evaluation for forest sites on the Mid-Cumberland Plateau

Treesearch

Glendon W. Smalley

1982-01-01

Presents a comprehensive forest site classification system for the central portion of the Cumberland Plateau in northeast Alabama, and east-central Tennessee. The system is based on physiography, geology, soils, topography, and vegetation.

An ordinal classification approach for CTG categorization.

PubMed

Georgoulas, George; Karvelis, Petros; Gavrilis, Dimitris; Stylios, Chrysostomos D; Nikolakopoulos, George

2017-07-01

Evaluation of cardiotocogram (CTG) is a standard approach employed during pregnancy and delivery. But, its interpretation requires high level expertise to decide whether the recording is Normal, Suspicious or Pathological. Therefore, a number of attempts have been carried out over the past three decades for development automated sophisticated systems. These systems are usually (multiclass) classification systems that assign a category to the respective CTG. However most of these systems usually do not take into consideration the natural ordering of the categories associated with CTG recordings. In this work, an algorithm that explicitly takes into consideration the ordering of CTG categories, based on binary decomposition method, is investigated. Achieved results, using as a base classifier the C4.5 decision tree classifier, prove that the ordinal classification approach is marginally better than the traditional multiclass classification approach, which utilizes the standard C4.5 algorithm for several performance criteria.

Proposal for a new risk stratification classification for meningioma based on patient age, WHO tumor grade, size, localization, and karyotype

PubMed Central

Domingues, Patrícia Henriques; Sousa, Pablo; Otero, Álvaro; Gonçalves, Jesus Maria; Ruiz, Laura; de Oliveira, Catarina; Lopes, Maria Celeste; Orfao, Alberto; Tabernero, Maria Dolores

2014-01-01

Background Tumor recurrence remains the major clinical complication of meningiomas, the majority of recurrences occurring among WHO grade I/benign tumors. In the present study, we propose a new scoring system for the prognostic stratification of meningioma patients based on analysis of a large series of meningiomas followed for a median of >5 years. Methods Tumor cytogenetics were systematically investigated by interphase fluorescence in situ hybridization in 302 meningioma samples, and the proposed classification was further validated in an independent series of cases (n = 132) analyzed by high-density (500K) single-nucleotide polymorphism (SNP) arrays. Results Overall, we found an adverse impact on patient relapse-free survival (RFS) for males, presence of brain edema, younger patients (<55 years), tumor size >50 mm, tumor localization at intraventricular and anterior cranial base areas, WHO grade II/III meningiomas, and complex karyotypes; the latter 5 variables showed an independent predictive value in multivariate analysis. Based on these parameters, a prognostic score was established for each individual case, and patients were stratified into 4 risk categories with significantly different (P < .001) outcomes. These included a good prognosis group, consisting of approximately 20% of cases, that showed a RFS of 100% ± 0% at 10 years and a very poor-prognosis group with a RFS rate of 0% ± 0% at 10 years. The prognostic impact of the scoring system proposed here was also retained when WHO grade I cases were considered separately (P < .001). Conclusions Based on this risk-stratification classification, different strategies may be adopted for follow-up, and eventually also for treatment, of meningioma patients at different risks for relapse. PMID:24536048

Rule groupings in expert systems using nearest neighbour decision rules, and convex hulls

NASA Technical Reports Server (NTRS)

Anastasiadis, Stergios

1991-01-01

Expert System shells are lacking in many areas of software engineering. Large rule based systems are not semantically comprehensible, difficult to debug, and impossible to modify or validate. Partitioning a set of rules found in CLIPS (C Language Integrated Production System) into groups of rules which reflect the underlying semantic subdomains of the problem, will address adequately the concerns stated above. Techniques are introduced to structure a CLIPS rule base into groups of rules that inherently have common semantic information. The concepts involved are imported from the field of A.I., Pattern Recognition, and Statistical Inference. Techniques focus on the areas of feature selection, classification, and a criteria of how 'good' the classification technique is, based on Bayesian Decision Theory. A variety of distance metrics are discussed for measuring the 'closeness' of CLIPS rules and various Nearest Neighbor classification algorithms are described based on the above metric.

An XML-based system for the flexible classification and retrieval of clinical practice guidelines.

PubMed Central

Ganslandt, T.; Mueller, M. L.; Krieglstein, C. F.; Senninger, N.; Prokosch, H. U.

2002-01-01

Beneficial effects of clinical practice guidelines (CPGs) have not yet reached expectations due to limited routine adoption. Electronic distribution and reminder systems have the potential to overcome implementation barriers. Existing electronic CPG repositories like the National Guideline Clearinghouse (NGC) provide individual access but lack standardized computer-readable interfaces necessary for automated guideline retrieval. The aim of this paper was to facilitate automated context-based selection and presentation of CPGs. Using attributes from the NGC classification scheme, an XML-based metadata repository was successfully implemented, providing document storage, classification and retrieval functionality. Semi-automated extraction of attributes was implemented for the import of XML guideline documents using XPath. A hospital information system interface was exemplarily implemented for diagnosis-based guideline invocation. Limitations of the implemented system are discussed and possible future work is outlined. Integration of standardized computer-readable search interfaces into existing CPG repositories is proposed. PMID:12463831

Improving Emergency Department Triage Classification with Computerized Clinical Decision Support at a Pediatric Hospital

ERIC Educational Resources Information Center

Kunisch, Joseph Martin

2012-01-01

Background: The Emergency Severity Index (ESI) is an emergency department (ED) triage classification system based on estimated patient-specific resource utilization. Rules for a computerized clinical decision support (CDS) system based on a patient's chief complaint were developed and tested using a stochastic model for predicting ESI scores.…

Diagnostic criteria, severity classification and guidelines of localized scleroderma.

PubMed

Asano, Yoshihide; Fujimoto, Manabu; Ishikawa, Osamu; Sato, Shinichi; Jinnin, Masatoshi; Takehara, Kazuhiko; Hasegawa, Minoru; Yamamoto, Toshiyuki; Ihn, Hironobu

2018-04-23

We established diagnostic criteria and severity classification of localized scleroderma because there is no established diagnostic criteria or widely accepted severity classification of the disease. Also, there has been no clinical guideline for localized scleroderma, so we established its clinical guideline ahead of all over the world. In particular, the clinical guideline was established by clinical questions based on evidence-based medicine according to the New Minds Clinical Practice Guideline Creation Manual (version 1.0). We aimed to make the guideline easy to use and reliable based on the newest evidence, and to present guidance as specific as possible for various clinical problems in treatment of localized scleroderma. © 2018 Japanese Dermatological Association.

[Histological diagnosis and complications of celiac disease. Update according to the new S2k guidelines].

PubMed

Aust, D E; Bläker, H

2015-03-01

Celiac disease is a relatively common immunological systemic disease triggered by the protein gluten in genetically predisposed individuals. Classical symptoms like chronic diarrhea, steatorrhea, weight loss and growth retardation are nowadays relatively uncommon. Diagnostic workup includes serological tests for IgA antibodies against tissue transglutaminase 2 (anti-TG2-IgA) and total IgA and histology of duodenal biopsies. Histomorphological classification should be done according to the modified Marsh-Oberhuber classification. Diagnosis of celiac disease should be based on serological, clinical, and histological findings. The only treatment is a life-long gluten-free diet. Unchanged or recurrent symptoms under gluten-free diet may indicate refractory celiac disease. Enteropathy-associated T-cell lymphoma and adenocarcinomas of the small intestine are known complications of celiac disease.

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.

A Study on the Correlation of Pertrochanteric Osteoporotic Fracture Severity with the Severity of Osteoporosis.

PubMed

Hayer, Prabhnoor Singh; Deane, Anit Kumar Samuel; Agrawal, Atul; Maheshwari, Rajesh; Juyal, Anil

2016-04-01

Osteoporosis is a metabolic bone disease caused by progressive bone loss. It is characterized by low Bone Mineral Density (BMD) and structural deterioration of bone tissue leading to bone fragility and increased risk of fractures. When classifying a fracture, high reliability and validity are crucial for successful treatment. Furthermore, a classification system should include severity, method of treatment, and prognosis for any given fracture. Since it is known that treatment significantly influences prognosis, a classification system claiming to include both would be desirable. Since there is no such classification system, which includes both the fracture type and the osteoporosis severity, we tried to find a correlation between fracture severity and osteoporosis severity. The aim of the study was to evaluate whether the AO/ASIF fracture classification system, which indicates the severity of fractures, has any relationship with the bone mineral status in patients with primary osteoporosis. We hypothesized that fracture severity and severity of osteoporosis should show some correlation. An observational analytical study was conducted over a period of one year during which 49 patients were included in the study at HIMS, SRH University, Dehradun. The osteoporosis status of all the included patients with a pertrochanteric fracture was documented using a DEXA scan and T-Score (BMD) was calculated. All patients had a trivial trauma. All the fractures were classified as per AO/ASIF classification. Pearson Correlation between BMD and fracture type was calculated. Data was entered on Microsoft Office Excel version 2007 and Interpretation and analysis of obtained data was done using summary statistics. Pearson Correlation between BMD and fracture type was calculated using the SPSS software version 22.0. The average age of the patients included in the study was 71.2 years and the average bone mineral density was -4.9. The correlation between BMD and fracture type was calculated and the r-values obtained was 0.180, which showed low a correlation and p-value was 0.215, which was insignificant. Statistically the pertrochanteric fracture configuration as per AO Classification does not correlate with the osteoporosis severity of the patient.

Development of a database of health insurance claims: standardization of disease classifications and anonymous record linkage.

PubMed

Kimura, Shinya; Sato, Toshihiko; Ikeda, Shunya; Noda, Mitsuhiko; Nakayama, Takeo

2010-01-01

Health insurance claims (ie, receipts) record patient health care treatments and expenses and, although created for the health care payment system, are potentially useful for research. Combining different types of receipts generated for the same patient would dramatically increase the utility of these receipts. However, technical problems, including standardization of disease names and classifications, and anonymous linkage of individual receipts, must be addressed. In collaboration with health insurance societies, all information from receipts (inpatient, outpatient, and pharmacy) was collected. To standardize disease names and classifications, we developed a computer-aided post-entry standardization method using a disease name dictionary based on International Classification of Diseases (ICD)-10 classifications. We also developed an anonymous linkage system by using an encryption code generated from a combination of hash values and stream ciphers. Using different sets of the original data (data set 1: insurance certificate number, name, and sex; data set 2: insurance certificate number, date of birth, and relationship status), we compared the percentage of successful record matches obtained by using data set 1 to generate key codes with the percentage obtained when both data sets were used. The dictionary's automatic conversion of disease names successfully standardized 98.1% of approximately 2 million new receipts entered into the database. The percentage of anonymous matches was higher for the combined data sets (98.0%) than for data set 1 (88.5%). The use of standardized disease classifications and anonymous record linkage substantially contributed to the construction of a large, chronologically organized database of receipts. This database is expected to aid in epidemiologic and health services research using receipt information.

Reclassification of clinical sleep disorders using traditional models of syndromic, neuroanatomic, pathophysiological and etiological diagnosis.

PubMed

Spitzer, A Robert

2014-09-01

Existing classifications of central nervous system sleep disorders do not often provide tools to diagnose the majority of patients complaining of sleep-related symptoms, nor always guide effective treatment. I present a novel classification system that completely separates clinical syndromes from anatomical localization, pathophysiology, and etiology. The clinical syndrome I present can describe the majority of patients, but can be fractionated into individual subgroups for further study. By then separating the anatomy and physiology from the symptoms, an avenue of research becomes available to study the different possible structures that regulate sleep, that may be damaged and cause syndromes of sleep dysfunction. Some of these may produce symptoms that overlap with narcolepsy and some may be distinct. Because the clinical syndrome should be distinguished from anatomy or physiology, I have proposed the term narcoleptiform syndrome for the clinical syndrome. The model also clearly separates etiology from anatomy in a classical neurological manner. This allows etiology, localization and symptoms to be studied separately. It is likely that different etiologies may produce damage in areas that produce similar syndromes. For example, in this model, different causes of damage to the orexin nucleus would result in the same clinical syndrome. This reinforces the concept of studying anatomy, symptoms and etiology separately. By studying the relationship of syndromes or symptoms to anatomic localization and pathophysiology, it should be possible to test novel approaches to treatment based on different underlying structure or function. For example, patients with lesions in the ventrolateral preoptic nucleus or the thalamic intralaminar nuclei may both present with insomnia symptoms but need different treatment; or they might present with symptoms overlapping narcolepsy (a narcoleptiform syndrome) yet need different treatment. In some cases, a single treatment may cross over more than one location, and the best predictor might be symptoms. These are issues that need to undergo careful study on a syndromic, anatomic and physiological bases. This novel model opens up new avenues for understanding central nervous system sleep disorders, providing testable hypotheses regarding diagnosis and treatment. Copyright © 2014 The Author. Published by Elsevier Ltd.. All rights reserved.

Refining the definition of mandibular osteoradionecrosis in clinical trials: The cancer research UK HOPON trial (Hyperbaric Oxygen for the Prevention of Osteoradionecrosis).

PubMed

Shaw, Richard; Tesfaye, Binyam; Bickerstaff, Matt; Silcocks, Paul; Butterworth, Christopher

2017-01-01

Mandibular osteoradionecrosis (ORN) is a common and serious complication of head and neck radiotherapy for which there is little reliable evidence for prevention or treatment. The diagnosis and classification of ORN have been inconsistently and imprecisely defined, even in clinical trials. A systematic review of diagnosis and classifications of ORN with specific focus on clinical trials is presented. The most suitable classification was evaluated for consistency using blinded independent review of outcome data (clinical photographs and radiographs) in the HOPON trial. Of 16 ORN classifications found, only one (Notani) appeared suitable as an endpoint in clinical trials. Clinical records of 217 timepoints were analysed amongst 94 randomised patients in the HOPON trial. The only inconsistency in classification arose where minor bone spicules (MBS) were apparent, which occurred in 19% of patients. Some trial investigators judged MBS as clinically unimportant and not reflecting ORN, others classified as ORN based on rigid definitions in common clinical use. When MBS was added as a distinct category to the Notani classification this ambiguity was resolved and agreement between observers was achieved. Most definitions and clinical classifications are based on retrospective case series and may be unsuitable for prospective interventional trials of ORN prevention or treatment. When ORN is used as a primary or secondary outcome in prospective clinical trials, the use of Notani classification with the additional category of MBS is recommended as it avoids subjectivity and enhances reliability and consistency of reporting. Copyright © 2016 Elsevier Ltd. All rights reserved.

Automatic parquet block sorting using real-time spectral classification

NASA Astrophysics Data System (ADS)

Astrom, Anders; Astrand, Erik; Johansson, Magnus

1999-03-01

This paper presents a real-time spectral classification system based on the PGP spectrograph and a smart image sensor. The PGP is a spectrograph which extracts the spectral information from a scene and projects the information on an image sensor, which is a method often referred to as Imaging Spectroscopy. The classification is based on linear models and categorizes a number of pixels along a line. Previous systems adopting this method have used standard sensors, which often resulted in poor performance. The new system, however, is based on a patented near-sensor classification method, which exploits analogue features on the smart image sensor. The method reduces the enormous amount of data to be processed at an early stage, thus making true real-time spectral classification possible. The system has been evaluated on hardwood parquet boards showing very good results. The color defects considered in the experiments were blue stain, white sapwood, yellow decay and red decay. In addition to these four defect classes, a reference class was used to indicate correct surface color. The system calculates a statistical measure for each parquet block, giving the pixel defect percentage. The patented method makes it possible to run at very high speeds with a high spectral discrimination ability. Using a powerful illuminator, the system can run with a line frequency exceeding 2000 line/s. This opens up the possibility to maintain high production speed and still measure with good resolution.

Analysis on Target Detection and Classification in LTE Based Passive Forward Scattering Radar

PubMed Central

Raja Abdullah, Raja Syamsul Azmir; Abdul Aziz, Noor Hafizah; Abdul Rashid, Nur Emileen; Ahmad Salah, Asem; Hashim, Fazirulhisyam

2016-01-01

The passive bistatic radar (PBR) system can utilize the illuminator of opportunity to enhance radar capability. By utilizing the forward scattering technique and procedure into the specific mode of PBR can provide an improvement in target detection and classification. The system is known as passive Forward Scattering Radar (FSR). The passive FSR system can exploit the peculiar advantage of the enhancement in forward scatter radar cross section (FSRCS) for target detection. Thus, the aim of this paper is to show the feasibility of passive FSR for moving target detection and classification by experimental analysis and results. The signal source is coming from the latest technology of 4G Long-Term Evolution (LTE) base station. A detailed explanation on the passive FSR receiver circuit, the detection scheme and the classification algorithm are given. In addition, the proposed passive FSR circuit employs the self-mixing technique at the receiver; hence the synchronization signal from the transmitter is not required. The experimental results confirm the passive FSR system’s capability for ground target detection and classification. Furthermore, this paper illustrates the first classification result in the passive FSR system. The great potential in the passive FSR system provides a new research area in passive radar that can be used for diverse remote monitoring applications. PMID:27690051

Controlling a human-computer interface system with a novel classification method that uses electrooculography signals.

PubMed

Wu, Shang-Lin; Liao, Lun-De; Lu, Shao-Wei; Jiang, Wei-Ling; Chen, Shi-An; Lin, Chin-Teng

2013-08-01

Electrooculography (EOG) signals can be used to control human-computer interface (HCI) systems, if properly classified. The ability to measure and process these signals may help HCI users to overcome many of the physical limitations and inconveniences in daily life. However, there are currently no effective multidirectional classification methods for monitoring eye movements. Here, we describe a classification method used in a wireless EOG-based HCI device for detecting eye movements in eight directions. This device includes wireless EOG signal acquisition components, wet electrodes and an EOG signal classification algorithm. The EOG classification algorithm is based on extracting features from the electrical signals corresponding to eight directions of eye movement (up, down, left, right, up-left, down-left, up-right, and down-right) and blinking. The recognition and processing of these eight different features were achieved in real-life conditions, demonstrating that this device can reliably measure the features of EOG signals. This system and its classification procedure provide an effective method for identifying eye movements. Additionally, it may be applied to study eye functions in real-life conditions in the near future.

Classification of ligand molecules in PDB with graph match-based structural superposition.

PubMed

Shionyu-Mitsuyama, Clara; Hijikata, Atsushi; Tsuji, Toshiyuki; Shirai, Tsuyoshi

2016-12-01

The fast heuristic graph match algorithm for small molecules, COMPLIG, was improved by adding a structural superposition process to verify the atom-atom matching. The modified method was used to classify the small molecule ligands in the Protein Data Bank (PDB) by their three-dimensional structures, and 16,660 types of ligands in the PDB were classified into 7561 clusters. In contrast, a classification by a previous method (without structure superposition) generated 3371 clusters from the same ligand set. The characteristic feature in the current classification system is the increased number of singleton clusters, which contained only one ligand molecule in a cluster. Inspections of the singletons in the current classification system but not in the previous one implied that the major factors for the isolation were differences in chirality, cyclic conformations, separation of substructures, and bond length. Comparisons between current and previous classification systems revealed that the superposition-based classification was effective in clustering functionally related ligands, such as drugs targeted to specific biological processes, owing to the strictness of the atom-atom matching.

Analysis of A Drug Target-based Classification System using Molecular Descriptors.

PubMed

Lu, Jing; Zhang, Pin; Bi, Yi; Luo, Xiaomin

2016-01-01

Drug-target interaction is an important topic in drug discovery and drug repositioning. KEGG database offers a drug annotation and classification using a target-based classification system. In this study, we gave an investigation on five target-based classes: (I) G protein-coupled receptors; (II) Nuclear receptors; (III) Ion channels; (IV) Enzymes; (V) Pathogens, using molecular descriptors to represent each drug compound. Two popular feature selection methods, maximum relevance minimum redundancy and incremental feature selection, were adopted to extract the important descriptors. Meanwhile, an optimal prediction model based on nearest neighbor algorithm was constructed, which got the best result in identifying drug target-based classes. Finally, some key descriptors were discussed to uncover their important roles in the identification of drug-target classes.

Classification and Progression Based on CFS-GA and C5.0 Boost Decision Tree of TCM Zheng in Chronic Hepatitis B.

PubMed

Chen, Xiao Yu; Ma, Li Zhuang; Chu, Na; Zhou, Min; Hu, Yiyang

2013-01-01

Chronic hepatitis B (CHB) is a serious public health problem, and Traditional Chinese Medicine (TCM) plays an important role in the control and treatment for CHB. In the treatment of TCM, zheng discrimination is the most important step. In this paper, an approach based on CFS-GA (Correlation based Feature Selection and Genetic Algorithm) and C5.0 boost decision tree is used for zheng classification and progression in the TCM treatment of CHB. The CFS-GA performs better than the typical method of CFS. By CFS-GA, the acquired attribute subset is classified by C5.0 boost decision tree for TCM zheng classification of CHB, and C5.0 decision tree outperforms two typical decision trees of NBTree and REPTree on CFS-GA, CFS, and nonselection in comparison. Based on the critical indicators from C5.0 decision tree, important lab indicators in zheng progression are obtained by the method of stepwise discriminant analysis for expressing TCM zhengs in CHB, and alterations of the important indicators are also analyzed in zheng progression. In conclusion, all the three decision trees perform better on CFS-GA than on CFS and nonselection, and C5.0 decision tree outperforms the two typical decision trees both on attribute selection and nonselection.

Fuzzy support vector machine: an efficient rule-based classification technique for microarrays.

PubMed

Hajiloo, Mohsen; Rabiee, Hamid R; Anooshahpour, Mahdi

2013-01-01

The abundance of gene expression microarray data has led to the development of machine learning algorithms applicable for tackling disease diagnosis, disease prognosis, and treatment selection problems. However, these algorithms often produce classifiers with weaknesses in terms of accuracy, robustness, and interpretability. This paper introduces fuzzy support vector machine which is a learning algorithm based on combination of fuzzy classifiers and kernel machines for microarray classification. Experimental results on public leukemia, prostate, and colon cancer datasets show that fuzzy support vector machine applied in combination with filter or wrapper feature selection methods develops a robust model with higher accuracy than the conventional microarray classification models such as support vector machine, artificial neural network, decision trees, k nearest neighbors, and diagonal linear discriminant analysis. Furthermore, the interpretable rule-base inferred from fuzzy support vector machine helps extracting biological knowledge from microarray data. Fuzzy support vector machine as a new classification model with high generalization power, robustness, and good interpretability seems to be a promising tool for gene expression microarray classification.

R-parametrization and its role in classification of linear multivariable feedback systems

NASA Technical Reports Server (NTRS)

Chen, Robert T. N.

1988-01-01

A classification of all the compensators that stabilize a given general plant in a linear, time-invariant multi-input, multi-output feedback system is developed. This classification, along with the associated necessary and sufficient conditions for stability of the feedback system, is achieved through the introduction of a new parameterization, referred to as R-Parameterization, which is a dual of the familiar Q-Parameterization. The classification is made to the stability conditions of the compensators and the plant by themselves; and necessary and sufficient conditions are based on the stability of Q and R themselves.

Neural attractor network for application in visual field data classification.

PubMed

Fink, Wolfgang

2004-07-07

The purpose was to introduce a novel method for computer-based classification of visual field data derived from perimetric examination, that may act as a 'counsellor', providing an independent 'second opinion' to the diagnosing physician. The classification system consists of a Hopfield-type neural attractor network that obtains its input data from perimetric examination results. An iterative relaxation process determines the states of the neurons dynamically. Therefore, even 'noisy' perimetric output, e.g., early stages of a disease, may eventually be classified correctly according to the predefined idealized visual field defect (scotoma) patterns, stored as attractors of the network, that are found with diseases of the eye, optic nerve and the central nervous system. Preliminary tests of the classification system on real visual field data derived from perimetric examinations have shown a classification success of over 80%. Some of the main advantages of the Hopfield-attractor-network-based approach over feed-forward type neural networks are: (1) network architecture is defined by the classification problem; (2) no training is required to determine the neural coupling strengths; (3) assignment of an auto-diagnosis confidence level is possible by means of an overlap parameter and the Hamming distance. In conclusion, the novel method for computer-based classification of visual field data, presented here, furnishes a valuable first overview and an independent 'second opinion' in judging perimetric examination results, pointing towards a final diagnosis by a physician. It should not be considered a substitute for the diagnosing physician. Thanks to the worldwide accessibility of the Internet, the classification system offers a promising perspective towards modern computer-assisted diagnosis in both medicine and tele-medicine, for example and in particular, with respect to non-ophthalmic clinics or in communities where perimetric expertise is not readily available.

Classification and evaluation for forest sites on the Eastern Highland Rim and Pennyroyal.

Treesearch

Glendon W. Smalley

1983-01-01

Presents a comprehensive forest site classification system for the Eastern Highland Rim and Pennyroyal in north Alabama, east-central Tennessee, and central Kentucky. The system is based on physiography, geology, soils, topography, and vegetation.

Reliability of Smartphone-Based Instant Messaging Application for Diagnosis, Classification, and Decision-making in Pediatric Orthopedic Trauma.

PubMed

Stahl, Ido; Katsman, Alexander; Zaidman, Michael; Keshet, Doron; Sigal, Amit; Eidelman, Mark

2017-07-11

Smartphones have the ability to capture and send images, and their use has become common in the emergency setting for transmitting radiographic images with the intent to consult an off-site specialist. Our objective was to evaluate the reliability of smartphone-based instant messaging applications for the evaluation of various pediatric limb traumas, as compared with the standard method of viewing images of a workstation-based picture archiving and communication system (PACS). X-ray images of 73 representative cases of pediatric limb trauma were captured and transmitted to 5 pediatric orthopedic surgeons by the Whatsapp instant messaging application on an iPhone 6 smartphone. Evaluators were asked to diagnose, classify, and determine the course of treatment for each case over their personal smartphones. Following a 4-week interval, revaluation was conducted using the PACS. Intraobserver agreement was calculated for overall agreement and per fracture site. The overall results indicate "near perfect agreement" between interpretations of the radiographs on smartphones compared with computer-based PACS, with κ of 0.84, 0.82, and 0.89 for diagnosis, classification, and treatment planning, respectively. Looking at the results per fracture site, we also found substantial to near perfect agreement. Smartphone-based instant messaging applications are reliable for evaluation of a wide range of pediatric limb fractures. This method of obtaining an expert opinion from the off-site specialist is immediately accessible and inexpensive, making smartphones a powerful tool for doctors in the emergency department, primary care clinics, or remote medical centers, enabling timely and appropriate treatment for the injured child. This method is not a substitution for evaluation of the images in the standard method over computer-based PACS, which should be performed before final decision-making.

Correlation of the Rock Mass Rating (RMR) System with the Unified Soil Classification System (USCS): Introduction of the Weak Rock Mass Rating System (W-RMR)

NASA Astrophysics Data System (ADS)

Warren, Sean N.; Kallu, Raj R.; Barnard, Chase K.

2016-11-01

Underground gold mines in Nevada are exploiting increasingly deeper ore bodies comprised of weak to very weak rock masses. The Rock Mass Rating (RMR) classification system is widely used at underground gold mines in Nevada and is applicable in fair to good-quality rock masses, but is difficult to apply and loses reliability in very weak rock mass to soil-like material. Because very weak rock masses are transition materials that border engineering rock mass and soil classification systems, soil classification may sometimes be easier and more appropriate to provide insight into material behavior and properties. The Unified Soil Classification System (USCS) is the most likely choice for the classification of very weak rock mass to soil-like material because of its accepted use in tunnel engineering projects and its ability to predict soil-like material behavior underground. A correlation between the RMR and USCS systems was developed by comparing underground geotechnical RMR mapping to laboratory testing of bulk samples from the same locations, thereby assigning a numeric RMR value to the USCS classification that can be used in spreadsheet calculations and geostatistical analyses. The geotechnical classification system presented in this paper including a USCS-RMR correlation, RMR rating equations, and the Geo-Pick Strike Index is collectively introduced as the Weak Rock Mass Rating System (W-RMR). It is the authors' hope that this system will aid in the classification of weak rock masses and more usable design tools based on the RMR system. More broadly, the RMR-USCS correlation and the W-RMR system help define the transition between engineering soil and rock mass classification systems and may provide insight for geotechnical design in very weak rock masses.

Twenty-four signature genes predict the prognosis of oral squamous cell carcinoma with high accuracy and repeatability

PubMed Central

Gao, Jianyong; Tian, Gang; Han, Xu; Zhu, Qiang

2018-01-01

Oral squamous cell carcinoma (OSCC) is the sixth most common type cancer worldwide, with poor prognosis. The present study aimed to identify gene signatures that could classify OSCC and predict prognosis in different stages. A training data set (GSE41613) and two validation data sets (GSE42743 and GSE26549) were acquired from the online Gene Expression Omnibus database. In the training data set, patients were classified based on the tumor-node-metastasis staging system, and subsequently grouped into low stage (L) or high stage (H). Signature genes between L and H stages were selected by disparity index analysis, and classification was performed by the expression of these signature genes. The established classification was compared with the L and H classification, and fivefold cross validation was used to evaluate the stability. Enrichment analysis for the signature genes was implemented by the Database for Annotation, Visualization and Integration Discovery. Two validation data sets were used to determine the precise of classification. Survival analysis was conducted followed each classification using the package ‘survival’ in R software. A set of 24 signature genes was identified based on the classification model with the Fi value of 0.47, which was used to distinguish OSCC samples in two different stages. Overall survival of patients in the H stage was higher than those in the L stage. Signature genes were primarily enriched in ‘ether lipid metabolism’ pathway and biological processes such as ‘positive regulation of adaptive immune response’ and ‘apoptotic cell clearance’. The results provided a novel 24-gene set that may be used as biomarkers to predict OSCC prognosis with high accuracy, which may be used to determine an appropriate treatment program for patients with OSCC in addition to the traditional evaluation index. PMID:29257303

NCCN Guidelines Insights: Central Nervous System Cancers, Version 1.2017.

PubMed

Nabors, Louis Burt; Portnow, Jana; Ammirati, Mario; Baehring, Joachim; Brem, Henry; Butowski, Nicholas; Fenstermaker, Robert A; Forsyth, Peter; Hattangadi-Gluth, Jona; Holdhoff, Matthias; Howard, Steven; Junck, Larry; Kaley, Thomas; Kumthekar, Priya; Loeffler, Jay S; Moots, Paul L; Mrugala, Maciej M; Nagpal, Seema; Pandey, Manjari; Parney, Ian; Peters, Katherine; Puduvalli, Vinay K; Ragsdale, John; Rockhill, Jason; Rogers, Lisa; Rusthoven, Chad; Shonka, Nicole; Shrieve, Dennis C; Sills, Allen K; Swinnen, Lode J; Tsien, Christina; Weiss, Stephanie; Wen, Patrick Yung; Willmarth, Nicole; Bergman, Mary Anne; Engh, Anita

2017-11-01

For many years, the diagnosis and classification of gliomas have been based on histology. Although studies including large populations of patients demonstrated the prognostic value of histologic phenotype, variability in outcomes within histologic groups limited the utility of this system. Nonetheless, histology was the only proven and widely accessible tool available at the time, thus it was used for clinical trial entry criteria, and therefore determined the recommended treatment options. Research to identify molecular changes that underlie glioma progression has led to the discovery of molecular features that have greater diagnostic and prognostic value than histology. Analyses of these molecular markers across populations from randomized clinical trials have shown that some of these markers are also predictive of response to specific types of treatment, which has prompted significant changes to the recommended treatment options for grade III (anaplastic) gliomas. Copyright © 2017 by the National Comprehensive Cancer Network.

Classification and Quality Evaluation of Tobacco Leaves Based on Image Processing and Fuzzy Comprehensive Evaluation

PubMed Central

Zhang, Fan; Zhang, Xinhong

2011-01-01

Most of classification, quality evaluation or grading of the flue-cured tobacco leaves are manually operated, which relies on the judgmental experience of experts, and inevitably limited by personal, physical and environmental factors. The classification and the quality evaluation are therefore subjective and experientially based. In this paper, an automatic classification method of tobacco leaves based on the digital image processing and the fuzzy sets theory is presented. A grading system based on image processing techniques was developed for automatically inspecting and grading flue-cured tobacco leaves. This system uses machine vision for the extraction and analysis of color, size, shape and surface texture. Fuzzy comprehensive evaluation provides a high level of confidence in decision making based on the fuzzy logic. The neural network is used to estimate and forecast the membership function of the features of tobacco leaves in the fuzzy sets. The experimental results of the two-level fuzzy comprehensive evaluation (FCE) show that the accuracy rate of classification is about 94% for the trained tobacco leaves, and the accuracy rate of the non-trained tobacco leaves is about 72%. We believe that the fuzzy comprehensive evaluation is a viable way for the automatic classification and quality evaluation of the tobacco leaves. PMID:22163744

Clinical limitations of the International Federation of Gynecology and Obstetrics (FIGO) classification of uterine fibroids.

PubMed

Laughlin-Tommaso, Shannon K; Hesley, Gina K; Hopkins, Matthew R; Brandt, Kathleen R; Zhu, Yunxiao; Stewart, Elizabeth A

2017-11-01

To determine the reproducibility of classifying uterine fibroids using the 2011 International Federation of Gynecology and Obstetrics (FIGO) staging system. The present retrospective cohort study included patients presenting for the treatment of symptomatic uterine fibroids at the Gynecology Fibroid Clinic at Mayo Clinic, Rochester, USA, between April 1, 2013 and April 1, 2014. Magnetic resonance imaging of fibroid uteri was performed and the images were independently reviewed by two academic gynecologists and two radiologists specializing in fibroid care. Fibroid classifications assigned by each physician were compared and the significance of the variations was graded by whether they would affect surgical planning. There were 42 fibroids from 23 patients; only 6 (14%) fibroids had unanimous classification agreement. The majority (36 [86%]) had at least two unique answers and 4 (10%) fibroids had four unique classifications. Variations in classification were not associated with physician specialty. More than one-third of the classification discrepancies would have impacted surgical planning. FIGO fibroid classification was not consistent among four fibroid specialists. The variation was clinically significant for 36% of the fibroids. Additional validation of the FIGO fibroid classification system is needed. © 2017 International Federation of Gynecology and Obstetrics.

An artificial neural networks approach for assessment treatment response in oncological patients using PET/CT images.

PubMed

Nogueira, Mariana A; Abreu, Pedro H; Martins, Pedro; Machado, Penousal; Duarte, Hugo; Santos, João

2017-02-13

Positron Emission Tomography - Computed Tomography (PET/CT) imaging is the basis for the evaluation of response-to-treatment of several oncological diseases. In practice, such evaluation is manually performed by specialists, which is rather complex and time-consuming. Evaluation measures have been proposed, but with questionable reliability. The usage of before and after-treatment image descriptors of the lesions for treatment response evaluation is still a territory to be explored. In this project, Artificial Neural Network approaches were implemented to automatically assess treatment response of patients suffering from neuroendocrine tumors and Hodgkyn lymphoma, based on image features extracted from PET/CT. The results show that the considered set of features allows for the achievement of very high classification performances, especially when data is properly balanced. After synthetic data generation and PCA-based dimensionality reduction to only two components, LVQNN assured classification accuracies of 100%, 100%, 96.3% and 100% regarding the 4 response-to-treatment classes.

A vegetation classification system applied to southern California

Treesearch

Timothy E. Paysen; Jeanine A. Derby; Hugh Black; Vernon C. Bleich; John W. Mincks

1980-01-01

A classification system for use in describing vegetation has been developed and is being applied to southern California. It is based upon a hierarchical stratification of vegetation, using physiognomic and taxonomic criteria. The system categories are Formation, Subformation. Series, Association, and Phase. Formations, Subformations, and Series have been specified for...

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.

Phenomenology and classification of dystonia: a consensus update.

PubMed

Albanese, Alberto; Bhatia, Kailash; Bressman, Susan B; Delong, Mahlon R; Fahn, Stanley; Fung, Victor S C; Hallett, Mark; Jankovic, Joseph; Jinnah, Hyder A; Klein, Christine; Lang, Anthony E; Mink, Jonathan W; Teller, Jan K

2013-06-15

This report describes the consensus outcome of an international panel consisting of investigators with years of experience in this field that reviewed the definition and classification of dystonia. Agreement was obtained based on a consensus development methodology during 3 in-person meetings and manuscript review by mail. Dystonia is defined as a movement disorder characterized by sustained or intermittent muscle contractions causing abnormal, often repetitive, movements, postures, or both. Dystonic movements are typically patterned and twisting, and may be tremulous. Dystonia is often initiated or worsened by voluntary action and associated with overflow muscle activation. Dystonia is classified along 2 axes: clinical characteristics, including age at onset, body distribution, temporal pattern and associated features (additional movement disorders or neurological features); and etiology, which includes nervous system pathology and inheritance. The clinical characteristics fall into several specific dystonia syndromes that help to guide diagnosis and treatment. We provide here a new general definition of dystonia and propose a new classification. We encourage clinicians and researchers to use these innovative definition and classification and test them in the clinical setting on a variety of patients with dystonia. © 2013 Movement Disorder Society. © 2013 Movement Disorder Society.

Investigation of Pharmaceutical Residues in Hospital Effluents, in Ground- and Drinking Water from Bundeswehr Facilities, and their Removal During Drinking Water Purification (Arzneimittelrueckstaende in Trinkwasser(versorgungsanlagen) und Krankenhausabwaessern der Bundeswehr: Methodenentwicklung - Verkommen - Wasseraufbereitung)

DTIC Science & Technology

1999-11-01

Drinking water processing plant , Analysis, Calculation model, Field experiment 16. PRICE CODE 17. SECURITY CLASSIFICATION 18. SECURITY CLASSIFICATION...sewage effluents and from the sewer of the municipal sewage treatment plant in Berlin-Ruhleben. In the field trials, the MDWPUs that both apply reverse...waste water samples, along the municipal sewer system and In the influents and effluents of the receiving sewage treatment plants . To estimate the

A low-cost mobile adaptive tracking system for chronic pulmonary patients in home environment.

PubMed

Işik, Ali Hakan; Güler, Inan; Sener, Melahat Uzel

2013-01-01

The main objective of this study is presenting a real-time mobile adaptive tracking system for patients diagnosed with diseases such as asthma or chronic obstructive pulmonary disease and application results at home. The main role of the system is to support and track chronic pulmonary patients in real time who are comfortable in their home environment. It is not intended to replace the doctor, regular treatment, and diagnosis. In this study, the Java 2 micro edition-based system is integrated with portable spirometry, smartphone, extensible markup language-based Web services, Web server, and Web pages for visualizing pulmonary function test results. The Bluetooth(®) (Bluetooth SIG, Kirkland, WA) virtual serial port protocol is used to obtain the test results from spirometry. General packet radio service, wireless local area network, or third-generation-based wireless networks are used to send the test results from a smartphone to the remote database. The system provides real-time classification of test results with the back propagation artificial neural network algorithm on a mobile smartphone. It also provides the generation of appropriate short message service-based notification and sending of all data to the Web server. In this study, the test results of 486 patients, obtained from Atatürk Chest Diseases and Thoracic Surgery Training and Research Hospital in Ankara, Turkey, are used as the training and test set in the algorithm. The algorithm has 98.7% accuracy, 97.83% specificity, 97.63% sensitivity, and 0.946 correlation values. The results show that the system is cheap (900 Euros) and reliable. The developed real-time system provides improvement in classification accuracy and facilitates tracking of chronic pulmonary patients.

Feasibility Study on a Portable Field Pest Classification System Design Based on DSP and 3G Wireless Communication Technology

PubMed Central

Han, Ruizhen; He, Yong; Liu, Fei

2012-01-01

This paper presents a feasibility study on a real-time in field pest classification system design based on Blackfin DSP and 3G wireless communication technology. This prototype system is composed of remote on-line classification platform (ROCP), which uses a digital signal processor (DSP) as a core CPU, and a host control platform (HCP). The ROCP is in charge of acquiring the pest image, extracting image features and detecting the class of pest using an Artificial Neural Network (ANN) classifier. It sends the image data, which is encoded using JPEG 2000 in DSP, to the HCP through the 3G network at the same time for further identification. The image transmission and communication are accomplished using 3G technology. Our system transmits the data via a commercial base station. The system can work properly based on the effective coverage of base stations, no matter the distance from the ROCP to the HCP. In the HCP, the image data is decoded and the pest image displayed in real-time for further identification. Authentication and performance tests of the prototype system were conducted. The authentication test showed that the image data were transmitted correctly. Based on the performance test results on six classes of pests, the average accuracy is 82%. Considering the different live pests’ pose and different field lighting conditions, the result is satisfactory. The proposed technique is well suited for implementation in field pest classification on-line for precision agriculture. PMID:22736996

Feasibility study on a portable field pest classification system design based on DSP and 3G wireless communication technology.

PubMed

Han, Ruizhen; He, Yong; Liu, Fei

2012-01-01

This paper presents a feasibility study on a real-time in field pest classification system design based on Blackfin DSP and 3G wireless communication technology. This prototype system is composed of remote on-line classification platform (ROCP), which uses a digital signal processor (DSP) as a core CPU, and a host control platform (HCP). The ROCP is in charge of acquiring the pest image, extracting image features and detecting the class of pest using an Artificial Neural Network (ANN) classifier. It sends the image data, which is encoded using JPEG 2000 in DSP, to the HCP through the 3G network at the same time for further identification. The image transmission and communication are accomplished using 3G technology. Our system transmits the data via a commercial base station. The system can work properly based on the effective coverage of base stations, no matter the distance from the ROCP to the HCP. In the HCP, the image data is decoded and the pest image displayed in real-time for further identification. Authentication and performance tests of the prototype system were conducted. The authentication test showed that the image data were transmitted correctly. Based on the performance test results on six classes of pests, the average accuracy is 82%. Considering the different live pests' pose and different field lighting conditions, the result is satisfactory. The proposed technique is well suited for implementation in field pest classification on-line for precision agriculture.

The First AO Classification System for Fractures of the Craniomaxillofacial Skeleton: Rationale, Methodological Background, Developmental Process, and Objectives

PubMed Central

Audigé, Laurent; Cornelius, Carl-Peter; Ieva, Antonio Di; Prein, Joachim

2014-01-01

Validated trauma classification systems are the sole means to provide the basis for reliable documentation and evaluation of patient care, which will open the gateway to evidence-based procedures and healthcare in the coming years. With the support of AO Investigation and Documentation, a classification group was established to develop and evaluate a comprehensive classification system for craniomaxillofacial (CMF) fractures. Blueprints for fracture classification in the major constituents of the human skull were drafted and then evaluated by a multispecialty group of experienced CMF surgeons and a radiologist in a structured process during iterative agreement sessions. At each session, surgeons independently classified the radiological imaging of up to 150 consecutive cases with CMF fractures. During subsequent review meetings, all discrepancies in the classification outcome were critically appraised for clarification and improvement until consensus was reached. The resulting CMF classification system is structured in a hierarchical fashion with three levels of increasing complexity. The most elementary level 1 simply distinguishes four fracture locations within the skull: mandible (code 91), midface (code 92), skull base (code 93), and cranial vault (code 94). Levels 2 and 3 focus on further defining the fracture locations and for fracture morphology, achieving an almost individual mapping of the fracture pattern. This introductory article describes the rationale for the comprehensive AO CMF classification system, discusses the methodological framework, and provides insight into the experiences and interactions during the evaluation process within the core groups. The details of this system in terms of anatomy and levels are presented in a series of focused tutorials illustrated with case examples in this special issue of the Journal. PMID:25489387

The First AO Classification System for Fractures of the Craniomaxillofacial Skeleton: Rationale, Methodological Background, Developmental Process, and Objectives.

PubMed

Audigé, Laurent; Cornelius, Carl-Peter; Di Ieva, Antonio; Prein, Joachim

2014-12-01

Validated trauma classification systems are the sole means to provide the basis for reliable documentation and evaluation of patient care, which will open the gateway to evidence-based procedures and healthcare in the coming years. With the support of AO Investigation and Documentation, a classification group was established to develop and evaluate a comprehensive classification system for craniomaxillofacial (CMF) fractures. Blueprints for fracture classification in the major constituents of the human skull were drafted and then evaluated by a multispecialty group of experienced CMF surgeons and a radiologist in a structured process during iterative agreement sessions. At each session, surgeons independently classified the radiological imaging of up to 150 consecutive cases with CMF fractures. During subsequent review meetings, all discrepancies in the classification outcome were critically appraised for clarification and improvement until consensus was reached. The resulting CMF classification system is structured in a hierarchical fashion with three levels of increasing complexity. The most elementary level 1 simply distinguishes four fracture locations within the skull: mandible (code 91), midface (code 92), skull base (code 93), and cranial vault (code 94). Levels 2 and 3 focus on further defining the fracture locations and for fracture morphology, achieving an almost individual mapping of the fracture pattern. This introductory article describes the rationale for the comprehensive AO CMF classification system, discusses the methodological framework, and provides insight into the experiences and interactions during the evaluation process within the core groups. The details of this system in terms of anatomy and levels are presented in a series of focused tutorials illustrated with case examples in this special issue of the Journal.

Hydrologic Landscape Classification to Estimate Bristol Bay Watershed Hydrology

EPA Science Inventory

The use of hydrologic landscapes has proven to be a useful tool for broad scale assessment and classification of landscapes across the United States. These classification systems help organize larger geographical areas into areas of similar hydrologic characteristics based on cl...

76 FR 9541 - Submission for OMB Review; Comment Request

Federal Register 2010, 2011, 2012, 2013, 2014

2011-02-18

....S. Census Bureau. Title: 2012 Economic Census General Classification Report. OMB Control Number... Business Register is that establishments are assigned an accurate economic classification, based on the North American Industry Classification System (NAICS). The primary purpose of the ``2012 Economic Census...

[Cervical cancer : Update on morphology].

PubMed

Horn, L-C; Brambs, C E; Handzel, R; Lax, S; Sändig, I; Schmidt, D; Schierle, K

2016-11-01

The World Health Organization (WHO) classification from 2014 differentiates between different subtypes of mucinous adenocarcinoma of the uterine cervix. A gastric subtype was recently described that showed no association with high-risk human papillomavirus (HPV) infections, has a poor prognosis, is mainly diagnosed in women of Asian origin and can occur in patients with Peutz-Jeghers syndrome. Although no clear grading system has been recommended in the WHO classification, it is likely that grading of adenocarcinomas of the uterine cervix will partly be based on the different patterns of invasion. Deep stromal infiltration of macroinvasive carcinomas is defined as an infiltration of >66 % of the cervical stroma. In the near future a maximum tumor size of 2 cm could act as a discriminator for planning of less radical surgery. Parameters of the histopathological report that are relevant for the prognostic assessment as well as the choice of adjuvant treatment and function as quality indicators during certification are described. The histological type of an adenocarcinoma alone is of no predictive or prognostic relevance for patients undergoing primary surgical treatment, neoadjuvant chemotherapy, combined chemo-radiotherapy or treatment with angiogenesis inhibitors. Currently, molecular parameters and biomarkers are of no relevance.

A clinical decision support system for diagnosis of Allergic Rhinitis based on intradermal skin tests.

PubMed

Jabez Christopher, J; Khanna Nehemiah, H; Kannan, A

2015-10-01

Allergic Rhinitis is a universal common disease, especially in populated cities and urban areas. Diagnosis and treatment of Allergic Rhinitis will improve the quality of life of allergic patients. Though skin tests remain the gold standard test for diagnosis of allergic disorders, clinical experts are required for accurate interpretation of test outcomes. This work presents a clinical decision support system (CDSS) to assist junior clinicians in the diagnosis of Allergic Rhinitis. Intradermal Skin tests were performed on patients who had plausible allergic symptoms. Based on patient׳s history, 40 clinically relevant allergens were tested. 872 patients who had allergic symptoms were considered for this study. The rule based classification approach and the clinical test results were used to develop and validate the CDSS. Clinical relevance of the CDSS was compared with the Score for Allergic Rhinitis (SFAR). Tests were conducted for junior clinicians to assess their diagnostic capability in the absence of an expert. The class based Association rule generation approach provides a concise set of rules that is further validated by clinical experts. The interpretations of the experts are considered as the gold standard. The CDSS diagnoses the presence or absence of rhinitis with an accuracy of 88.31%. The allergy specialist and the junior clinicians prefer the rule based approach for its comprehendible knowledge model. The Clinical Decision Support Systems with rule based classification approach assists junior doctors and clinicians in the diagnosis of Allergic Rhinitis to make reliable decisions based on the reports of intradermal skin tests. Copyright © 2015 Elsevier Ltd. All rights reserved.

Supervised machine learning algorithms to diagnose stress for vehicle drivers based on physiological sensor signals.

PubMed

Barua, Shaibal; Begum, Shahina; Ahmed, Mobyen Uddin

2015-01-01

Machine learning algorithms play an important role in computer science research. Recent advancement in sensor data collection in clinical sciences lead to a complex, heterogeneous data processing, and analysis for patient diagnosis and prognosis. Diagnosis and treatment of patients based on manual analysis of these sensor data are difficult and time consuming. Therefore, development of Knowledge-based systems to support clinicians in decision-making is important. However, it is necessary to perform experimental work to compare performances of different machine learning methods to help to select appropriate method for a specific characteristic of data sets. This paper compares classification performance of three popular machine learning methods i.e., case-based reasoning, neutral networks and support vector machine to diagnose stress of vehicle drivers using finger temperature and heart rate variability. The experimental results show that case-based reasoning outperforms other two methods in terms of classification accuracy. Case-based reasoning has achieved 80% and 86% accuracy to classify stress using finger temperature and heart rate variability. On contrary, both neural network and support vector machine have achieved less than 80% accuracy by using both physiological signals.

The difference between a dynamic and mechanical approach to stroke treatment.

PubMed

Helgason, Cathy M

2007-06-01

The current classification of stroke is based on causation, also called pathogenesis, and relies on binary logic faithful to the Aristotelian tradition. Accordingly, a pathology is or is not the cause of the stroke, is considered independent of others, and is the target for treatment. It is the subject for large double-blind randomized clinical therapeutic trials. The scientific view behind clinical trials is the fundamental concept that information is statistical, and causation is determined by probabilities. Therefore, the cause and effect relation will be determined by probability-theory-based statistics. This is the basis of evidence-based medicine, which calls for the results of such trials to be the basis for physician decisions regarding diagnosis and treatment. However, there are problems with the methodology behind evidence-based medicine. Calculations using probability-theory-based statistics regarding cause and effect are performed within an automatic system where there are known inputs and outputs. This method of research provides a framework of certainty with no surprise elements or outcomes. However, it is not a system or method that will come up with previously unknown variables, concepts, or universal principles; it is not a method that will give a new outcome; and it is not a method that allows for creativity, expertise, or new insight for problem solving.

A signature dissimilarity measure for trabecular bone texture in knee radiographs

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

Woloszynski, T.; Podsiadlo, P.; Stachowiak, G. W.

Purpose: The purpose of this study is to develop a dissimilarity measure for the classification of trabecular bone (TB) texture in knee radiographs. Problems associated with the traditional extraction and selection of texture features and with the invariance to imaging conditions such as image size, anisotropy, noise, blur, exposure, magnification, and projection angle were addressed. Methods: In the method developed, called a signature dissimilarity measure (SDM), a sum of earth mover's distances calculated for roughness and orientation signatures is used to quantify dissimilarities between textures. Scale-space theory was used to ensure scale and rotation invariance. The effects of image size,more » anisotropy, noise, and blur on the SDM developed were studied using computer generated fractal texture images. The invariance of the measure to image exposure, magnification, and projection angle was studied using x-ray images of human tibia head. For the studies, Mann-Whitney tests with significance level of 0.01 were used. A comparison study between the performances of a SDM based classification system and other two systems in the classification of Brodatz textures and the detection of knee osteoarthritis (OA) were conducted. The other systems are based on weighted neighbor distance using compound hierarchy of algorithms representing morphology (WND-CHARM) and local binary patterns (LBP). Results: Results obtained indicate that the SDM developed is invariant to image exposure (2.5-30 mA s), magnification (x1.00-x1.35), noise associated with film graininess and quantum mottle (<25%), blur generated by a sharp film screen, and image size (>64x64 pixels). However, the measure is sensitive to changes in projection angle (>5 deg.), image anisotropy (>30 deg.), and blur generated by a regular film screen. For the classification of Brodatz textures, the SDM based system produced comparable results to the LBP system. For the detection of knee OA, the SDM based system achieved 78.8% classification accuracy and outperformed the WND-CHARM system (64.2%). Conclusions: The SDM is well suited for the classification of TB texture images in knee OA detection and may be useful for the texture classification of medical images in general.« less

A patch-based convolutional neural network for remote sensing image classification.

PubMed

Sharma, Atharva; Liu, Xiuwen; Yang, Xiaojun; Shi, Di

2017-11-01

Availability of accurate land cover information over large areas is essential to the global environment sustainability; digital classification using medium-resolution remote sensing data would provide an effective method to generate the required land cover information. However, low accuracy of existing per-pixel based classification methods for medium-resolution data is a fundamental limiting factor. While convolutional neural networks (CNNs) with deep layers have achieved unprecedented improvements in object recognition applications that rely on fine image structures, they cannot be applied directly to medium-resolution data due to lack of such fine structures. In this paper, considering the spatial relation of a pixel to its neighborhood, we propose a new deep patch-based CNN system tailored for medium-resolution remote sensing data. The system is designed by incorporating distinctive characteristics of medium-resolution data; in particular, the system computes patch-based samples from multidimensional top of atmosphere reflectance data. With a test site from the Florida Everglades area (with a size of 771 square kilometers), the proposed new system has outperformed pixel-based neural network, pixel-based CNN and patch-based neural network by 24.36%, 24.23% and 11.52%, respectively, in overall classification accuracy. By combining the proposed deep CNN and the huge collection of medium-resolution remote sensing data, we believe that much more accurate land cover datasets can be produced over large areas. Copyright © 2017 Elsevier Ltd. All rights reserved.

A wavelet-based technique to predict treatment outcome for Major Depressive Disorder

PubMed Central

Xia, Likun; Mohd Yasin, Mohd Azhar; Azhar Ali, Syed Saad

2017-01-01

Treatment management for Major Depressive Disorder (MDD) has been challenging. However, electroencephalogram (EEG)-based predictions of antidepressant’s treatment outcome may help during antidepressant’s selection and ultimately improve the quality of life for MDD patients. In this study, a machine learning (ML) method involving pretreatment EEG data was proposed to perform such predictions for Selective Serotonin Reuptake Inhibitor (SSRIs). For this purpose, the acquisition of experimental data involved 34 MDD patients and 30 healthy controls. Consequently, a feature matrix was constructed involving time-frequency decomposition of EEG data based on wavelet transform (WT) analysis, termed as EEG data matrix. However, the resultant EEG data matrix had high dimensionality. Therefore, dimension reduction was performed based on a rank-based feature selection method according to a criterion, i.e., receiver operating characteristic (ROC). As a result, the most significant features were identified and further be utilized during the training and testing of a classification model, i.e., the logistic regression (LR) classifier. Finally, the LR model was validated with 100 iterations of 10-fold cross-validation (10-CV). The classification results were compared with short-time Fourier transform (STFT) analysis, and empirical mode decompositions (EMD). The wavelet features extracted from frontal and temporal EEG data were found statistically significant. In comparison with other time-frequency approaches such as the STFT and EMD, the WT analysis has shown highest classification accuracy, i.e., accuracy = 87.5%, sensitivity = 95%, and specificity = 80%. In conclusion, significant wavelet coefficients extracted from frontal and temporal pre-treatment EEG data involving delta and theta frequency bands may predict antidepressant’s treatment outcome for the MDD patients. PMID:28152063

Proposal for a functional classification system of heart failure in patients with end-stage renal disease: proceedings of the acute dialysis quality initiative (ADQI) XI workgroup.

PubMed

Chawla, Lakhmir S; Herzog, Charles A; Costanzo, Maria Rosa; Tumlin, James; Kellum, John A; McCullough, Peter A; Ronco, Claudio

2014-04-08

Structural heart disease is highly prevalent in patients with chronic kidney disease requiring dialysis. More than 80% of patients with end-stage renal disease (ESRD) are reported to have cardiovascular disease. This observation has enormous clinical relevance because the leading causes of death for patients with ESRD are of cardiovascular disease etiology, including heart failure, myocardial infarction, and sudden cardiac death. The 2 systems most commonly used to classify the severity of heart failure are the New York Heart Association (NYHA) functional classification and the American Heart Association (AHA)/American College of Cardiology (ACC) staging system. With rare exceptions, patients with ESRD who do not receive renal replacement therapy (RRT) develop signs and symptoms of heart failure, including dyspnea and edema due to inability of the severely diseased kidneys to excrete sodium and water. Thus, by definition, nearly all patients with ESRD develop a symptomatology consistent with heart failure if fluid removal by RRT is delayed. Neither the AHA/ACC heart failure staging nor the NYHA functional classification system identifies the variable symptomatology that patients with ESRD experience depending upon whether evaluation occurs before or after fluid removal by RRT. Consequently, the incidence, severity, and outcomes of heart failure in patients with ESRD are poorly characterized. The 11th Acute Dialysis Quality Initiative has identified this issue as a critical unmet need for the proper evaluation and treatment of heart failure in patients with ESRD. We propose a classification schema based on patient-reported dyspnea assessed both pre- and post-ultrafiltration, in conjunction with echocardiography. Copyright © 2014 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.

Scapula fractures: interobserver reliability of classification and treatment.

PubMed

Neuhaus, Valentin; Bot, Arjan G J; Guitton, Thierry G; Ring, David C; Abdel-Ghany, Mahmoud I; Abrams, Jeffrey; Abzug, Joshua M; Adolfsson, Lars E; Balfour, George W; Bamberger, H Brent; Barquet, Antonio; Baskies, Michael; Batson, W Arnold; Baxamusa, Taizoon; Bayne, Grant J; Begue, Thierry; Behrman, Michael; Beingessner, Daphne; Biert, Jan; Bishop, Julius; Alves, Mateus Borges Oliveira; Boyer, Martin; Brilej, Drago; Brink, Peter R G; Brunton, Lance M; Buckley, Richard; Cagnone, Juan Carlos; Calfee, Ryan P; Campinhos, Luiz Augusto B; Cassidy, Charles; Catalano, Louis; Chivers, Karel; Choudhari, Pradeep; Cimerman, Matej; Conflitti, Joseph M; Costanzo, Ralph M; Crist, Brett D; Cross, Brian J; Dantuluri, Phani; Darowish, Michael; de Bedout, Ramon; DeCoster, Thomas; Dennison, David G; DeNoble, Peter H; DeSilva, Gregory; Dienstknecht, Thomas; Duncan, Scott F; Duralde, Xavier A; Durchholz, Holger; Egol, Kenneth; Ekholm, Carl; Elias, Nelson; Erickson, John M; Esparza, J Daniel Espinosa; Fernandes, C H; Fischer, Thomas J; Fischmeister, Martin; Forigua Jaime, E; Getz, Charles L; Gilbert, Richard S; Giordano, Vincenzo; Glaser, David L; Gosens, Taco; Grafe, Michael W; Filho, Jose Eduardo Grandi Ribeiro; Gray, Robert R L; Gulotta, Lawrence V; Gummerson, Nigel William; Hammerberg, Eric Mark; Harvey, Edward; Haverlag, R; Henry, Patrick D G; Hobby, Jonathan L; Hofmeister, Eric P; Hughes, Thomas; Itamura, John; Jebson, Peter; Jenkinson, Richard; Jeray, Kyle; Jones, Christopher M; Jones, Jedediah; Jubel, Axel; Kaar, Scott G; Kabir, K; Kaplan, F Thomas D; Kennedy, Stephen A; Kessler, Michael W; Kimball, Hervey L; Kloen, Peter; Klostermann, Cyrus; Kohut, Georges; Kraan, G A; Kristan, Anze; Loebenberg, Mark I; Malone, Kevin J; Marsh, L; Martineau, Paul A; McAuliffe, John; McGraw, Iain; Mehta, Samir; Merchant, Milind; Metzger, Charles; Meylaerts, S A; Miller, Anna N; Wolf, Jennifer Moriatis; Murachovsky, Joel; Murthi, Anand; Nancollas, Michael; Nolan, Betsy M; Omara, Timothy; Omid, Reza; Ortiz, Jose A; Overbeck, Joachim P; Castillo, Alberto Pérez; Pesantez, Rodrigo; Polatsch, Daniel; Porcellini, G; Prayson, Michael; Quell, M; Ragsdell, Matthew M; Reid, James G; Reuver, J M; Richard, Marc J; Richardson, Martin; Rizzo, Marco; Rowinski, Sergio; Rubio, Jorge; Guerrero, Carlos G Sánchez; Satora, Wojciech; Schandelmaier, Peter; Scheer, Johan H; Schmidt, Andrew; Schubkegel, Todd A; Schulte, Leah M; Schumer, Evan D; Sears, Benjamin W; Shafritz, Adam B; Shortt, Nicholas L; Siff, Todd; Silva, Dario Mejia; Smith, Raymond Malcolm; Spruijt, Sander; Stein, Jason A; Pemovska, Emilija Stojkovska; Streubel, Philipp N; Swigart, Carrie; Swiontkowski, Marc; Thomas, George; Tolo, Eric T; Turina, Matthias; Tyllianakis, Minos; van den Bekerom, Michel P J; van der Heide, Huub; van de Sande, M A J; van Eerten, P V; Verbeek, Diederik O F; Hoffmann, David Victoria; Vochteloo, A J H; Wagenmakers, Robert; Wall, Christopher J; Wallensten, Richard; Wascher, Daniel C; Weiss, Lawrence; Wiater, J Michael; Wills, Brian P D; Wint, Jeffrey; Wright, Thomas; Young, Jason P; Zalavras, Charalampos; Zura, Robert D; Zyto, Karol

2014-03-01

There is substantial variation in the classification and management of scapula fractures. The first purpose of this study was to analyze the interobserver reliability of the OTA/AO classification and the New International Classification for Scapula Fractures. The second purpose was to assess the proportion of agreement among orthopaedic surgeons on operative or nonoperative treatment. Web-based reliability study. Independent orthopaedic surgeons from several countries were invited to classify scapular fractures in an online survey. One hundred three orthopaedic surgeons evaluated 35 movies of three-dimensional computerized tomography reconstruction of selected scapular fractures, representing a full spectrum of fracture patterns. Fleiss kappa (κ) was used to assess the reliability of agreement between the surgeons. The overall agreement on the OTA/AO classification was moderate for the types (A, B, and C, κ = 0.54) with a 71% proportion of rater agreement (PA) and for the 9 groups (A1 to C3, κ = 0.47) with a 57% PA. For the New International Classification, the agreement about the intraarticular extension of the fracture (Fossa (F), κ = 0.79) was substantial and the agreement about a fractured body (Body (B), κ = 0.57) or process was moderate (Process (P), κ = 0.53); however, PAs were more than 81%. The agreement on the treatment recommendation was moderate (κ = 0.57) with a 73% PA. The New International Classification was more reliable. Body and process fractures generated more disagreement than intraarticular fractures and need further clear definitions.

A clinico-pathological study of lupus nephritis based on the International Society of Nephrology-Renal Pathology Society 2003 classification system.

PubMed

Satish, Suchitha; Deka, Pallavi; Shetty, Manjunath Sanjeev

2017-01-01

Lupus nephritis (LN) is a major complication of systemic lupus erythematosus (SLE). Renal involvement is a major determinant of the prognosis of SLE. The histological classification of LN is a key factor in determining the renal survival of patients with LN. Prompt recognition and treatment of renal disease are important, as early response to therapy is correlated with better outcome and renal biopsy plays an important role in achieving this. The objective of this study was to correlate the clinical and laboratory findings with histopathological classes of LN as per the 2003 International Society of Nephrology-Renal Pathology Society (ISN/RPS) classification system. Fifty-six patients with SLE, undergoing a renal biopsy for renal dysfunction were studied. The comparison of data from multiple groups was made by Pearson's Chi-square test and between two groups by independent samples t -test. The values of P < 0.05 were considered statistically significant. Of the 56 cases studied, 51 (91.1%) were females. The most common presenting symptoms were edema, arthralgia, and hypertension. Class IV (55.4%) was the most common class. Thirty-nine (69.6%) cases showed full house immunostaining. Hypertension, hematuria, proteinuria, and tubulo-interstitial disease showed a significant correlation ( P < 0.05) with ISN/RPS classification, 2003. Assessment and management of patients with suspected LN are greatly facilitated through information obtained by renal biopsy. Since renal morphology may predict long-term prognosis, and no clinical or laboratory feature uniformly predicts prognosis, it is important to study the constellation of features in LN for better patient management.

[A comparative study of coding and information systems for the evaluation of medical and social conditions: the case of addictive disorders].

PubMed

Bourdais-Mannone, Claire; Cherikh, Faredj; Gicquel, Nathalie; Gelsi, Eve; Jove, Frédérique; Staccini, Pascal

2011-01-01

The purpose of this study was to conduct a descriptive and comparative analysis of the tools used by healthcare professionals specializing in addictive disorders to promote a rapprochement of information systems. The evaluation guide used to assess the compensation needs of disabled persons treated in "Maisons Départementales des Personnes Handicapées" (centres for disabled people) organizes information in different areas, including a psychological component. The guide includes social and environmental information in the "Recueil Commun sur les Addictions et les Prises en charges" (Joint Report on Drug Addiction and Drug Treatment). While the program for the medicalization of information systems includes care data, the current information about social situations remains inadequate. The international classification of diseases provides synthetic diagnostic codes to describe substance use, etiologic factors and the somatic and psychological complications inherent to addictive disorders. The current system could be radically simplified and harmonized and would benefit from adopting a more individualized approach to non-substance behavioral addictions. The international classification of disabilities provides tools for evaluating the psychological component included in the recent definition of addictive disorders. Legal information should play an integral role in the structure of the information system and in international classifications. The prevalence of episodes of care and treatment of addictive and psychological disorders was assessed at Nice University Hospital in all disciplines. Except in addiction treatment units, very few patients were found to have a RECAP file.

Real time workload classification from an ambulatory wireless EEG system using hybrid EEG electrodes.

PubMed

Matthews, R; Turner, P J; McDonald, N J; Ermolaev, K; Manus, T; Shelby, R A; Steindorf, M

2008-01-01

This paper describes a compact, lightweight and ultra-low power ambulatory wireless EEG system based upon QUASAR's innovative noninvasive bioelectric sensor technologies. The sensors operate through hair without skin preparation or conductive gels. Mechanical isolation built into the harness permits the recording of high quality EEG data during ambulation. Advanced algorithms developed for this system permit real time classification of workload during subject motion. Measurements made using the EEG system during ambulation are presented, including results for real time classification of subject workload.

Feature selection and classification of multiparametric medical images using bagging and SVM

NASA Astrophysics Data System (ADS)

Fan, Yong; Resnick, Susan M.; Davatzikos, Christos

2008-03-01

This paper presents a framework for brain classification based on multi-parametric medical images. This method takes advantage of multi-parametric imaging to provide a set of discriminative features for classifier construction by using a regional feature extraction method which takes into account joint correlations among different image parameters; in the experiments herein, MRI and PET images of the brain are used. Support vector machine classifiers are then trained based on the most discriminative features selected from the feature set. To facilitate robust classification and optimal selection of parameters involved in classification, in view of the well-known "curse of dimensionality", base classifiers are constructed in a bagging (bootstrap aggregating) framework for building an ensemble classifier and the classification parameters of these base classifiers are optimized by means of maximizing the area under the ROC (receiver operating characteristic) curve estimated from their prediction performance on left-out samples of bootstrap sampling. This classification system is tested on a sex classification problem, where it yields over 90% classification rates for unseen subjects. The proposed classification method is also compared with other commonly used classification algorithms, with favorable results. These results illustrate that the methods built upon information jointly extracted from multi-parametric images have the potential to perform individual classification with high sensitivity and specificity.

Impact of Information based Classification on Network Epidemics

PubMed Central

Mishra, Bimal Kumar; Haldar, Kaushik; Sinha, Durgesh Nandini

2016-01-01

Formulating mathematical models for accurate approximation of malicious propagation in a network is a difficult process because of our inherent lack of understanding of several underlying physical processes that intrinsically characterize the broader picture. The aim of this paper is to understand the impact of available information in the control of malicious network epidemics. A 1-n-n-1 type differential epidemic model is proposed, where the differentiality allows a symptom based classification. This is the first such attempt to add such a classification into the existing epidemic framework. The model is incorporated into a five class system called the DifEpGoss architecture. Analysis reveals an epidemic threshold, based on which the long-term behavior of the system is analyzed. In this work three real network datasets with 22002, 22469 and 22607 undirected edges respectively, are used. The datasets show that classification based prevention given in the model can have a good role in containing network epidemics. Further simulation based experiments are used with a three category classification of attack and defense strengths, which allows us to consider 27 different possibilities. These experiments further corroborate the utility of the proposed model. The paper concludes with several interesting results. PMID:27329348

A classification system for characterization of physical and non-physical work factors.

PubMed

Genaidy, A; Karwowski, W; Succop, P; Kwon, Y G; Alhemoud, A; Goyal, D

2000-01-01

A comprehensive evaluation of work-related performance factors is a prerequisite to developing integrated and long-term solutions to workplace performance improvement. This paper describes a work-factor classification system that categorizes the entire domain of workplace factors impacting performance. A questionnaire-based instrument was developed to implement this classification system in industry. Fifty jobs were evaluated in 4 different service and manufacturing companies using the proposed questionnaire-based instrument. The reliability coefficients obtained from the analyzed jobs were considered good (0.589 to 0.862). In general, the physical work factors resulted in higher reliability coefficients (0.847 to 0.862) than non-physical work factors (0.589 to 0.768).

Drug safety: Pregnancy rating classifications and controversies.

PubMed

Wilmer, Erin; Chai, Sandy; Kroumpouzos, George

2016-01-01

This contribution consolidates data on international pregnancy rating classifications, including the former US Food and Drug Administration (FDA), Swedish, and Australian classification systems, as well as the evidence-based medicine system, and discusses discrepancies among them. It reviews the new Pregnancy and Lactation Labeling Rule (PLLR) that replaced the former FDA labeling system with narrative-based labeling requirements. PLLR emphasizes on human data and highlights pregnancy exposure registry information. In this context, the review discusses important data on the safety of most medications used in the management of skin disease in pregnancy. There are also discussions of controversies relevant to the safety of certain dermatologic medications during gestation. Copyright © 2016 Elsevier Inc. All rights reserved.

How Many Kingdoms? Current Views of Biological Classification.

ERIC Educational Resources Information Center

Margulis, Lynn

1981-01-01

Argues for the acceptance and use of a five-kingdom classification system for biology comprised of monera, protoctista, fungi, animals, and plants. Justifies the new system based upon the difference between prokaryotes and eukaryotes. Outlines each kingdom and describes its members. (DC)

Classification and evaluation for forest sites on the Western Highland Rim and Pennyroyal

Treesearch

Glendon W. Smalley

1980-01-01

Presents a comprehensive forest site classification system for the Western Highland Rim and Western Pennyroyal-Limestone area in northwest Alabama, west-central Tennessee, and western Kentucky. The system is based on physiography, geology, soils, topography, and vegetation.

Treatment outcomes of temporal bone osteoradionecrosis.

PubMed

Kammeijer, Quinten; van Spronsen, Erik; Mirck, Piet G B; Dreschler, Wouter A

2015-04-01

To investigate the clinical relevance of the classification systems used for temporal bone osteoradionecrosis (ORN) and to define a treatment protocol for temporal bone ORN. Retrospective case series. Amsterdam, department of otorhinolaryngology and head and neck surgery. Classification of temporal bone ORN was performed through use of clinical data and radiologic imaging. Outcomes of conservative and surgical treatment were investigated and compared for different grades of ORN. Of the 49 ears included in this study, 35 were primarily treated conservatively. At start of conservative treatment, 23 were classified as a localized and 8 as a diffuse form of ORN; 4 could not be classified. There was a significant difference in clinical outcome between the localized and diffuse forms of ORN (χ(2) = 5.862, P = .015), and mastoid air cell destruction on preoperative computed tomography scan was found to be a significant predictor for a negative outcome of conservative treatment (χ(2) = 4.34, P = .037). Fourteen ears with diffuse ORN were primarily treated surgically, and 11 were secondarily treated surgically following a period of conservative treatment. Twenty-two patients were treated with subtotal petrosectomy, of which 20 were cured. Three patients were treated with canal wall down mastoidectomy, and 2 had recurrence of disease. Ramsden's classification system is clinically relevant in predicting conservative treatment outcomes. Mastoid air cell destruction on computed tomography differentiates between the localized and diffuse forms of ORN. Given our results and experience with treating temporal bone ORN, we propose a treatment protocol. © American Academy of Otolaryngology—Head and Neck Surgery Foundation 2015.

Data Clustering and Evolving Fuzzy Decision Tree for Data Base Classification Problems

NASA Astrophysics Data System (ADS)

Chang, Pei-Chann; Fan, Chin-Yuan; Wang, Yen-Wen

Data base classification suffers from two well known difficulties, i.e., the high dimensionality and non-stationary variations within the large historic data. This paper presents a hybrid classification model by integrating a case based reasoning technique, a Fuzzy Decision Tree (FDT), and Genetic Algorithms (GA) to construct a decision-making system for data classification in various data base applications. The model is major based on the idea that the historic data base can be transformed into a smaller case-base together with a group of fuzzy decision rules. As a result, the model can be more accurately respond to the current data under classifying from the inductions by these smaller cases based fuzzy decision trees. Hit rate is applied as a performance measure and the effectiveness of our proposed model is demonstrated by experimentally compared with other approaches on different data base classification applications. The average hit rate of our proposed model is the highest among others.

Speech Enhancement based on the Dominant Classification Between Speech and Noise Using Feature Data in Spectrogram of Observation Signal

NASA Astrophysics Data System (ADS)

Nomura, Yukihiro; Lu, Jianming; Sekiya, Hiroo; Yahagi, Takashi

This paper presents a speech enhancement using the classification between the dominants of speech and noise. In our system, a new classification scheme between the dominants of speech and noise is proposed. The proposed classifications use the standard deviation of the spectrum of observation signal in each band. We introduce two oversubtraction factors for the dominants of speech and noise, respectively. And spectral subtraction is carried out after the classification. The proposed method is tested on several noise types from the Noisex-92 database. From the investigation of segmental SNR, Itakura-Saito distance measure, inspection of spectrograms and listening tests, the proposed system is shown to be effective to reduce background noise. Moreover, the enhanced speech using our system generates less musical noise and distortion than that of conventional systems.

The biopsychosocial domains and the functions of the medical interview in primary care: construct validity of the Verona Medical Interview Classification System.

PubMed

Del Piccolo, Lidia; Putnam, Samuel M; Mazzi, Maria Angela; Zimmermann, Christa

2004-04-01

Factor analysis (FA) is a powerful method of testing the construct validity of coding systems of the medical interview. The study uses FA to test the underlying assumptions of the Verona Medical Interview Classification System (VR-MICS). The relationship between factor scores and patient characteristics was also examined. The VR-MICS coding categories consider the three domains of the biopsychosocial model and the main functions of the medical interview-data gathering, relationship building and patient education. FA was performed on the frequencies of the VR-MICS categories based on 238 medical interviews. Seven factors (62.5% of variance explained) distinguished different strategies patients and physicians use to exchange information, build a relationship and negotiate treatment within the domains of the biopsychosocial model. Three factors, Psychological, Social Inquiry and Management of Patient Agenda, were related to patient data: sociodemographic (female gender, age and employment), social (stressful events), clinical (GHQ-12 score), personality (chance external health locus of control) and clinical characteristics (psychiatric history, chronic illness, attributed presence of emotional distress).

Simple adaptive sparse representation based classification schemes for EEG based brain-computer interface applications.

PubMed

Shin, Younghak; Lee, Seungchan; Ahn, Minkyu; Cho, Hohyun; Jun, Sung Chan; Lee, Heung-No

2015-11-01

One of the main problems related to electroencephalogram (EEG) based brain-computer interface (BCI) systems is the non-stationarity of the underlying EEG signals. This results in the deterioration of the classification performance during experimental sessions. Therefore, adaptive classification techniques are required for EEG based BCI applications. In this paper, we propose simple adaptive sparse representation based classification (SRC) schemes. Supervised and unsupervised dictionary update techniques for new test data and a dictionary modification method by using the incoherence measure of the training data are investigated. The proposed methods are very simple and additional computation for the re-training of the classifier is not needed. The proposed adaptive SRC schemes are evaluated using two BCI experimental datasets. The proposed methods are assessed by comparing classification results with the conventional SRC and other adaptive classification methods. On the basis of the results, we find that the proposed adaptive schemes show relatively improved classification accuracy as compared to conventional methods without requiring additional computation. Copyright © 2015 Elsevier Ltd. All rights reserved.

Understanding similarity of groundwater systems with empirical copulas

NASA Astrophysics Data System (ADS)

Haaf, Ezra; Kumar, Rohini; Samaniego, Luis; Barthel, Roland

2016-04-01

Within the classification framework for groundwater systems that aims for identifying similarity of hydrogeological systems and transferring information from a well-observed to an ungauged system (Haaf and Barthel, 2015; Haaf and Barthel, 2016), we propose a copula-based method for describing groundwater-systems similarity. Copulas are an emerging method in hydrological sciences that make it possible to model the dependence structure of two groundwater level time series, independently of the effects of their marginal distributions. This study is based on Samaniego et al. (2010), which described an approach calculating dissimilarity measures from bivariate empirical copula densities of streamflow time series. Subsequently, streamflow is predicted in ungauged basins by transferring properties from similar catchments. The proposed approach is innovative because copula-based similarity has not yet been applied to groundwater systems. Here we estimate the pairwise dependence structure of 600 wells in Southern Germany using 10 years of weekly groundwater level observations. Based on these empirical copulas, dissimilarity measures are estimated, such as the copula's lower- and upper corner cumulated probability, copula-based Spearman's rank correlation - as proposed by Samaniego et al. (2010). For the characterization of groundwater systems, copula-based metrics are compared with dissimilarities obtained from precipitation signals corresponding to the presumed area of influence of each groundwater well. This promising approach provides a new tool for advancing similarity-based classification of groundwater system dynamics. 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. Haaf, E., Barthel, R., 2016. An approach for classification of hydrogeological systems at the regional scale based on groundwater hydrographs EGU General Assembly 2016, Vienna, Austria. Samaniego, L., Bardossy, A., Kumar, R., 2010. Streamflow prediction in ungauged catchments using copula-based dissimilarity measures. Water Resources Research, 46. DOI:10.1029/2008wr007695

Discriminant forest classification method and system

DOEpatents

Chen, Barry Y.; Hanley, William G.; Lemmond, Tracy D.; Hiller, Lawrence J.; Knapp, David A.; Mugge, Marshall J.

2012-11-06

A hybrid machine learning methodology and system for classification that combines classical random forest (RF) methodology with discriminant analysis (DA) techniques to provide enhanced classification capability. A DA technique which uses feature measurements of an object to predict its class membership, such as linear discriminant analysis (LDA) or Andersen-Bahadur linear discriminant technique (AB), is used to split the data at each node in each of its classification trees to train and grow the trees and the forest. When training is finished, a set of n DA-based decision trees of a discriminant forest is produced for use in predicting the classification of new samples of unknown class.

The dawn of a new era in onco-cardiology: The Kumamoto Classification.

PubMed

Sueta, Daisuke; Tabata, Noriaki; Akasaka, Tomonori; Yamashita, Takayoshi; Ikemoto, Tomokazu; Hokimoto, Seiji

2016-10-01

The term "onco-cardiology" has been used in reference to cardiotoxicity in the treatment of malignant disease. In actual clinical situations, however, cardiovascular disease (CVD) associated with malignant disease and the concurrence of atherosclerotic disease with malignant disease are commonly observed, complicating the course of treatment. Patients with malignant disease associated with coronary artery disease often die from the cardiovascular disease, so it is essential to classify these disease states. Additionally, the prevalence of these classifications makes it easy to manage patients with malignant disease and coronary artery disease. We divided the broad field of onco-cardiology into 4 classifications based on clinical scenarios (CSs): CS1 represents the so-called paraneoplastic syndrome. CS2 represents cardiotoxicity during treatment of malignant diseases. CS3 represents the concurrence of atherosclerotic disease with malignant disease, and CS4 represents cardiovascular disease with benign tumors. This classification facilitates the management of patients with malignant disease and coronary artery disease by promoting not only the primary but also the secondary prevention of CVD. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

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

Underwater target classification using wavelet packets and neural networks.

PubMed

Azimi-Sadjadi, M R; Yao, D; Huang, Q; Dobeck, G J

2000-01-01

In this paper, a new subband-based classification scheme is developed for classifying underwater mines and mine-like targets from the acoustic backscattered signals. The system consists of a feature extractor using wavelet packets in conjunction with linear predictive coding (LPC), a feature selection scheme, and a backpropagation neural-network classifier. The data set used for this study consists of the backscattered signals from six different objects: two mine-like targets and four nontargets for several aspect angles. Simulation results on ten different noisy realizations and for signal-to-noise ratio (SNR) of 12 dB are presented. The receiver operating characteristic (ROC) curve of the classifier generated based on these results demonstrated excellent classification performance of the system. The generalization ability of the trained network was demonstrated by computing the error and classification rate statistics on a large data set. A multiaspect fusion scheme was also adopted in order to further improve the classification performance.

A CLASSIFICATION OF U.S. ESTUARIES BASED ON PHYSICAL, HYDROLOGIC ATTRIBUTES

EPA Science Inventory

A classification of U.S. estuaries is presented based on estuarine characteristics that have been identified as important for quantifying stressor-response

relationships in coastal systems. Estuaries within a class have similar physical/hydrologic and land use characteris...

Apples to committee consensus: the challenge of gender identity classification.

PubMed

Rettew, David C

2012-01-01

The debate surrounding the inclusion of gender dysphoria/gender variant behavior (GD/GV) as a psychiatric diagnosis exposes many of the fundamental shortcomings and inconsistencies of our current diagnostic classification system. Proposals raised by the authors of this special issue, including basing diagnosis on cause rather than overt behavior, reclassifying GD/GV behavior as a physical rather than mental condition, and basing diagnosis on impairment or distress, offer some solutions but have limitations themselves given the available database. In contrast to most accepted psychiatric conditions where emphasis is placed on ultimately changing internal thoughts, feelings, and behaviors, consensus treatment for most GD/GV individuals, at least from adolescence onward, focuses on modifying the external body and external environment to maximize positive outcomes. This series of articles illustrating the diversity of opinions on when and if gender incongruence should be considered pathological reflects the relative lack of scientific indicators of disease in this area, similar to many other domains of mental functioning.

Feature Selection and Parameters Optimization of SVM Using Particle Swarm Optimization for Fault Classification in Power Distribution Systems.

PubMed

Cho, Ming-Yuan; Hoang, Thi Thom

2017-01-01

Fast and accurate fault classification is essential to power system operations. In this paper, in order to classify electrical faults in radial distribution systems, a particle swarm optimization (PSO) based support vector machine (SVM) classifier has been proposed. The proposed PSO based SVM classifier is able to select appropriate input features and optimize SVM parameters to increase classification accuracy. Further, a time-domain reflectometry (TDR) method with a pseudorandom binary sequence (PRBS) stimulus has been used to generate a dataset for purposes of classification. The proposed technique has been tested on a typical radial distribution network to identify ten different types of faults considering 12 given input features generated by using Simulink software and MATLAB Toolbox. The success rate of the SVM classifier is over 97%, which demonstrates the effectiveness and high efficiency of the developed method.

Acute Oral Toxicity of Nitroguanidine in Male and Female Rats

DTIC Science & Technology

1988-03-01

results place nitroguanidlne in the practically nontoxic category based on the toxicity classification system of Hodge and Sterner. 20 DISTRIBUTION...nose and mouth. These results place nitroguanidine in the practically nontoxic category based on the toxicity classification system of Hodge and...O. Lollini, DVM, VC, Diplomate, American College of Veterinary Pathologists DATA MANAGERS: Carolyn M. Lewis, MS, Yvonne C. Le Tellier , BS REPORT

Model-based object classification using unification grammars and abstract representations

NASA Astrophysics Data System (ADS)

Liburdy, Kathleen A.; Schalkoff, Robert J.

1993-04-01

The design and implementation of a high level computer vision system which performs object classification is described. General object labelling and functional analysis require models of classes which display a wide range of geometric variations. A large representational gap exists between abstract criteria such as `graspable' and current geometric image descriptions. The vision system developed and described in this work addresses this problem and implements solutions based on a fusion of semantics, unification, and formal language theory. Object models are represented using unification grammars, which provide a framework for the integration of structure and semantics. A methodology for the derivation of symbolic image descriptions capable of interacting with the grammar-based models is described and implemented. A unification-based parser developed for this system achieves object classification by determining if the symbolic image description can be unified with the abstract criteria of an object model. Future research directions are indicated.

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

Genomic Classification of Tumors | Center for Cancer Research

Cancer.gov

CCR investigators were among the first to classify tumors based on genetics, laying the groundwork for today’s common practice to molecularly characterize tumors based on their genetic fingerprints for personalized treatments.

[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.

Method and System for Controlling a Dexterous Robot Execution Sequence Using State Classification

NASA Technical Reports Server (NTRS)

Sanders, Adam M. (Inventor); Quillin, Nathaniel (Inventor); Platt, Robert J., Jr. (Inventor); Pfeiffer, Joseph (Inventor); Permenter, Frank Noble (Inventor)

2014-01-01

A robotic system includes a dexterous robot and a controller. The robot includes a plurality of robotic joints, actuators for moving the joints, and sensors for measuring a characteristic of the joints, and for transmitting the characteristics as sensor signals. The controller receives the sensor signals, and is configured for executing instructions from memory, classifying the sensor signals into distinct classes via the state classification module, monitoring a system state of the robot using the classes, and controlling the robot in the execution of alternative work tasks based on the system state. A method for controlling the robot in the above system includes receiving the signals via the controller, classifying the signals using the state classification module, monitoring the present system state of the robot using the classes, and controlling the robot in the execution of alternative work tasks based on the present system state.

Robust spike classification based on frequency domain neural waveform features.

PubMed

Yang, Chenhui; Yuan, Yuan; Si, Jennie

2013-12-01

We introduce a new spike classification algorithm based on frequency domain features of the spike snippets. The goal for the algorithm is to provide high classification accuracy, low false misclassification, ease of implementation, robustness to signal degradation, and objectivity in classification outcomes. In this paper, we propose a spike classification algorithm based on frequency domain features (CFDF). It makes use of frequency domain contents of the recorded neural waveforms for spike classification. The self-organizing map (SOM) is used as a tool to determine the cluster number intuitively and directly by viewing the SOM output map. After that, spike classification can be easily performed using clustering algorithms such as the k-Means. In conjunction with our previously developed multiscale correlation of wavelet coefficient (MCWC) spike detection algorithm, we show that the MCWC and CFDF detection and classification system is robust when tested on several sets of artificial and real neural waveforms. The CFDF is comparable to or outperforms some popular automatic spike classification algorithms with artificial and real neural data. The detection and classification of neural action potentials or neural spikes is an important step in single-unit-based neuroscientific studies and applications. After the detection of neural snippets potentially containing neural spikes, a robust classification algorithm is applied for the analysis of the snippets to (1) extract similar waveforms into one class for them to be considered coming from one unit, and to (2) remove noise snippets if they do not contain any features of an action potential. Usually, a snippet is a small 2 or 3 ms segment of the recorded waveform, and differences in neural action potentials can be subtle from one unit to another. Therefore, a robust, high performance classification system like the CFDF is necessary. In addition, the proposed algorithm does not require any assumptions on statistical properties of the noise and proves to be robust under noise contamination.

A Three-Phase Decision Model of Computer-Aided Coding for the Iranian Classification of Health Interventions (IRCHI).

PubMed

Azadmanjir, Zahra; Safdari, Reza; Ghazisaeedi, Marjan; Mokhtaran, Mehrshad; Kameli, Mohammad Esmail

2017-06-01

Accurate coded data in the healthcare are critical. Computer-Assisted Coding (CAC) is an effective tool to improve clinical coding in particular when a new classification will be developed and implemented. But determine the appropriate method for development need to consider the specifications of existing CAC systems, requirements for each type, our infrastructure and also, the classification scheme. The aim of the study was the development of a decision model for determining accurate code of each medical intervention in Iranian Classification of Health Interventions (IRCHI) that can be implemented as a suitable CAC system. first, a sample of existing CAC systems was reviewed. Then feasibility of each one of CAC types was examined with regard to their prerequisites for their implementation. The next step, proper model was proposed according to the structure of the classification scheme and was implemented as an interactive system. There is a significant relationship between the level of assistance of a CAC system and integration of it with electronic medical documents. Implementation of fully automated CAC systems is impossible due to immature development of electronic medical record and problems in using language for medical documenting. So, a model was proposed to develop semi-automated CAC system based on hierarchical relationships between entities in the classification scheme and also the logic of decision making to specify the characters of code step by step through a web-based interactive user interface for CAC. It was composed of three phases to select Target, Action and Means respectively for an intervention. The proposed model was suitable the current status of clinical documentation and coding in Iran and also, the structure of new classification scheme. Our results show it was practical. However, the model needs to be evaluated in the next stage of the research.

21 CFR 862.1335 - Glucagon test system.

Code of Federal Regulations, 2011 CFR

2011-04-01

... and treatment of patients with various disorders of carbohydrate metabolism, including diabetes mellitus, hypoglycemia, and hyperglycemia. (b) Classification. Class I (general controls). The device is...

Functional classification of pulmonary hypertension in children: Report from the PVRI pediatric taskforce, Panama 2011.

PubMed

Lammers, Astrid E; Adatia, Ian; Cerro, Maria Jesus Del; Diaz, Gabriel; Freudenthal, Alexandra Heath; Freudenthal, Franz; Harikrishnan, S; Ivy, Dunbar; Lopes, Antonio A; Raj, J Usha; Sandoval, Julio; Stenmark, Kurt; Haworth, Sheila G

2011-08-02

The members of the Pediatric Task Force of the Pulmonary Vascular Research Institute (PVRI) were aware of the need to develop a functional classification of pulmonary hypertension in children. The proposed classification follows the same pattern and uses the same criteria as the Dana Point pulmonary hypertension specific classification for adults. Modifications were necessary for children, since age, physical growth and maturation influences the way in which the functional effects of a disease are expressed. It is essential to encapsulate a child's clinical status, to make it possible to review progress with time as he/she grows up, as consistently and as objectively as possible. Particularly in younger children we sought to include objective indicators such as thriving, need for supplemental feeds and the record of school or nursery attendance. This helps monitor the clinical course of events and response to treatment over the years. It also facilitates the development of treatment algorithms for children. We present a consensus paper on a functional classification system for children with pulmonary hypertension, discussed at the Annual Meeting of the PVRI in Panama City, February 2011.

Maxillectomy defects: a suggested classification scheme.

PubMed

Akinmoladun, V I; Dosumu, O O; Olusanya, A A; Ikusika, O F

2013-06-01

The term "maxillectomy" has been used to describe a variety of surgical procedures for a spectrum of diseases involving a diverse anatomical site. Hence, classifications of maxillectomy defects have often made communication difficult. This article highlights this problem, emphasises the need for a uniform system of classification and suggests a classification system which is simple and comprehensive. Articles related to this subject, especially those with specified classifications of maxillary surgical defects were sourced from the internet through Google, Scopus and PubMed using the search terms maxillectomy defects classification. A manual search through available literature was also done. The review of the materials revealed many classifications and modifications of classifications from the descriptive, reconstructive and prosthodontic perspectives. No globally acceptable classification exists among practitioners involved in the management of diseases in the mid-facial region. There were over 14 classifications of maxillary defects found in the English literature. Attempts made to address the inadequacies of previous classifications have tended to result in cumbersome and relatively complex classifications. A single classification that is based on both surgical and prosthetic considerations is most desirable and is hereby proposed.

Natural Language Processing Based Instrument for Classification of Free Text Medical Records

PubMed Central

2016-01-01

According to the Ministry of Labor, Health and Social Affairs of Georgia a new health management system has to be introduced in the nearest future. In this context arises the problem of structuring and classifying documents containing all the history of medical services provided. The present work introduces the instrument for classification of medical records based on the Georgian language. It is the first attempt of such classification of the Georgian language based medical records. On the whole 24.855 examination records have been studied. The documents were classified into three main groups (ultrasonography, endoscopy, and X-ray) and 13 subgroups using two well-known methods: Support Vector Machine (SVM) and K-Nearest Neighbor (KNN). The results obtained demonstrated that both machine learning methods performed successfully, with a little supremacy of SVM. In the process of classification a “shrink” method, based on features selection, was introduced and applied. At the first stage of classification the results of the “shrink” case were better; however, on the second stage of classification into subclasses 23% of all documents could not be linked to only one definite individual subclass (liver or binary system) due to common features characterizing these subclasses. The overall results of the study were successful. PMID:27668260

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.

Current Assessment and Classification of Suicidal Phenomena using the FDA 2012 Draft Guidance Document on Suicide Assessment: A Critical Review.

PubMed

Sheehan, David V; Giddens, Jennifer M; Sheehan, Kathy Harnett

2014-09-01

Standard international classification criteria require that classification categories be comprehensive to avoid type II error. Categories should be mutually exclusive and definitions should be clear and unambiguous (to avoid type I and type II errors). In addition, the classification system should be robust enough to last over time and provide comparability between data collections. This article was designed to evaluate the extent to which the classification system contained in the United States Food and Drug Administration 2012 Draft Guidance for the prospective assessment and classification of suicidal ideation and behavior in clinical trials meets these criteria. A critical review is used to assess the extent to which the proposed categories contained in the Food and Drug Administration 2012 Draft Guidance are comprehensive, unambiguous, and robust. Assumptions that underlie the classification system are also explored. The Food and Drug Administration classification system contained in the 2012 Draft Guidance does not capture the full range of suicidal ideation and behavior (type II error). Definitions, moreover, are frequently ambiguous (susceptible to multiple interpretations), and the potential for misclassification (type I and type II errors) is compounded by frequent mismatches in category titles and definitions. These issues have the potential to compromise data comparability within clinical trial sites, across sites, and over time. These problems need to be remedied because of the potential for flawed data output and consequent threats to public health, to research on the safety of medications, and to the search for effective medication treatments for suicidality.

Iatrogenic Bone and Soft Tissue Trauma in Robotic-Arm Assisted Total Knee Arthroplasty Compared With Conventional Jig-Based Total Knee Arthroplasty: A Prospective Cohort Study and Validation of a New Classification System.

PubMed

Kayani, Babar; Konan, Sujith; Pietrzak, Jurek R T; Haddad, Fares S

2018-03-27

The objective of this study was to compare macroscopic bone and soft tissue injury between robotic-arm assisted total knee arthroplasty (RA-TKA) and conventional jig-based total knee arthroplasty (CJ-TKA) and create a validated classification system for reporting iatrogenic bone and periarticular soft tissue injury after TKA. This study included 30 consecutive CJ-TKAs followed by 30 consecutive RA-TKAs performed by a single surgeon. Intraoperative photographs of the femur, tibia, and periarticular soft tissues were taken before implantation of prostheses. Using these outcomes, the macroscopic soft tissue injury (MASTI) classification system was developed to grade iatrogenic bone and soft tissue injuries. Interobserver and Intraobserver validity of the proposed classification system was assessed. Patients undergoing RA-TKA had reduced medial soft tissue injury in both passively correctible (P < .05) and noncorrectible varus deformities (P < .05); more pristine femoral (P < .05) and tibial (P < .05) bone resection cuts; and improved MASTI scores compared to CJ-TKA (P < .05). There was high interobserver (intraclass correlation coefficient 0.92 [95% confidence interval: 0.88-0.96], P < .05) and intraobserver agreement (intraclass correlation coefficient 0.94 [95% confidence interval: 0.92-0.97], P < .05) of the proposed MASTI classification system. There is reduced bone and periarticular soft tissue injury in patients undergoing RA-TKA compared to CJ-TKA. The proposed MASTI classification system is a reproducible grading scheme for describing iatrogenic bone and soft tissue injury in TKA. RA-TKA is associated with reduced bone and soft tissue injury compared with conventional jig-based TKA. The proposed MASTI classification may facilitate further research correlating macroscopic soft tissue injury during TKA to long-term clinical and functional outcomes. Copyright © 2018 Elsevier Inc. All rights reserved.

Land cover change detection using a GIS-guided, feature-based classification of Landsat thematic mapper data. [Geographic Information System

NASA Technical Reports Server (NTRS)

Enslin, William R.; Ton, Jezching; Jain, Anil

1987-01-01

Landsat TM data were combined with land cover and planimetric data layers contained in the State of Michigan's geographic information system (GIS) to identify changes in forestlands, specifically new oil/gas wells. A GIS-guided feature-based classification method was developed. The regions extracted by the best image band/operator combination were studied using a set of rules based on the characteristics of the GIS oil/gas pads.

An Intelligent Tutoring System for Classifying Students into Instructional Treatments with Mastery Scores. Research Report 94-15.

ERIC Educational Resources Information Center

Vos, Hans J.

As part of a project formulating optimal rules for decision making in computer assisted instructional systems in which the computer is used as a decision support tool, an approach that simultaneously optimizes classification of students into two treatments, each followed by a mastery decision, is presented using the framework of Bayesian decision…

Symbolic rule-based classification of lung cancer stages from free-text pathology reports.

PubMed

Nguyen, Anthony N; Lawley, Michael J; Hansen, David P; Bowman, Rayleen V; Clarke, Belinda E; Duhig, Edwina E; Colquist, Shoni

2010-01-01

To classify automatically lung tumor-node-metastases (TNM) cancer stages from free-text pathology reports using symbolic rule-based classification. By exploiting report substructure and the symbolic manipulation of systematized nomenclature of medicine-clinical terms (SNOMED CT) concepts in reports, statements in free text can be evaluated for relevance against factors relating to the staging guidelines. Post-coordinated SNOMED CT expressions based on templates were defined and populated by concepts in reports, and tested for subsumption by staging factors. The subsumption results were used to build logic according to the staging guidelines to calculate the TNM stage. The accuracy measure and confusion matrices were used to evaluate the TNM stages classified by the symbolic rule-based system. The system was evaluated against a database of multidisciplinary team staging decisions and a machine learning-based text classification system using support vector machines. Overall accuracy on a corpus of pathology reports for 718 lung cancer patients against a database of pathological TNM staging decisions were 72%, 78%, and 94% for T, N, and M staging, respectively. The system's performance was also comparable to support vector machine classification approaches. A system to classify lung TNM stages from free-text pathology reports was developed, and it was verified that the symbolic rule-based approach using SNOMED CT can be used for the extraction of key lung cancer characteristics from free-text reports. Future work will investigate the applicability of using the proposed methodology for extracting other cancer characteristics and types.

Automatic intelligibility classification of sentence-level pathological speech

PubMed Central

Kim, Jangwon; Kumar, Naveen; Tsiartas, Andreas; Li, Ming; Narayanan, Shrikanth S.

2014-01-01

Pathological speech usually refers to the condition of speech distortion resulting from atypicalities in voice and/or in the articulatory mechanisms owing to disease, illness or other physical or biological insult to the production system. Although automatic evaluation of speech intelligibility and quality could come in handy in these scenarios to assist experts in diagnosis and treatment design, the many sources and types of variability often make it a very challenging computational processing problem. In this work we propose novel sentence-level features to capture abnormal variation in the prosodic, voice quality and pronunciation aspects in pathological speech. In addition, we propose a post-classification posterior smoothing scheme which refines the posterior of a test sample based on the posteriors of other test samples. Finally, we perform feature-level fusions and subsystem decision fusion for arriving at a final intelligibility decision. The performances are tested on two pathological speech datasets, the NKI CCRT Speech Corpus (advanced head and neck cancer) and the TORGO database (cerebral palsy or amyotrophic lateral sclerosis), by evaluating classification accuracy without overlapping subjects’ data among training and test partitions. Results show that the feature sets of each of the voice quality subsystem, prosodic subsystem, and pronunciation subsystem, offer significant discriminating power for binary intelligibility classification. We observe that the proposed posterior smoothing in the acoustic space can further reduce classification errors. The smoothed posterior score fusion of subsystems shows the best classification performance (73.5% for unweighted, and 72.8% for weighted, average recalls of the binary classes). PMID:25414544

Reliability testing of two classification systems for osteoarthritis and post-traumatic arthritis of the elbow.

PubMed

Amini, Michael H; Sykes, Joshua B; Olson, Stephen T; Smith, Richard A; Mauck, Benjamin M; Azar, Frederick M; Throckmorton, Thomas W

2015-03-01

The severity of elbow arthritis is one of many factors that surgeons must evaluate when considering treatment options for a given patient. Elbow surgeons have historically used the Broberg and Morrey (BM) and Hastings and Rettig (HR) classification systems to radiographically stage the severity of post-traumatic arthritis (PTA) and primary osteoarthritis (OA). We proposed to compare the intraobserver and interobserver reliability between systems for patients with either PTA or OA. The radiographs of 45 patients were evaluated at least 2 weeks apart by 6 evaluators of different levels of training. Intraobserver and interobserver reliability were calculated by Spearman correlation coefficients with 95% confidence intervals. Agreement was considered almost perfect for coefficients >0.80 and substantial for coefficients of 0.61 to 0.80. In patients with both PTA and OA, intraobserver reliability and interobserver reliability were substantial, with no difference between classification systems. There were no significant differences in intraobserver or interobserver reliability between attending physicians and trainees for either classification system (all P > .10). The presence of fracture implants did not affect reliability in the BM system but did substantially worsen reliability in the HR system (intraobserver P = .04 and interobserver P = .001). The BM and HR classifications both showed substantial intraobserver and interobserver reliability for PTA and OA. Training level differences did not affect reliability for either system. Both trainees and fellowship-trained surgeons may easily and reliably apply each classification system to the evaluation of primary elbow OA and PTA, although the HR system was less reliable in the presence of fracture implants. Copyright © 2015 Journal of Shoulder and Elbow Surgery Board of Trustees. Published by Elsevier Inc. All rights reserved.

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

Optimal two-stage dynamic treatment regimes from a classification perspective with censored survival data.

PubMed

Hager, Rebecca; Tsiatis, Anastasios A; Davidian, Marie

2018-05-18

Clinicians often make multiple treatment decisions at key points over the course of a patient's disease. A dynamic treatment regime is a sequence of decision rules, each mapping a patient's observed history to the set of available, feasible treatment options at each decision point, and thus formalizes this process. An optimal regime is one leading to the most beneficial outcome on average if used to select treatment for the patient population. We propose a method for estimation of an optimal regime involving two decision points when the outcome of interest is a censored survival time, which is based on maximizing a locally efficient, doubly robust, augmented inverse probability weighted estimator for average outcome over a class of regimes. By casting this optimization as a classification problem, we exploit well-studied classification techniques such as support vector machines to characterize the class of regimes and facilitate implementation via a backward iterative algorithm. Simulation studies of performance and application of the method to data from a sequential, multiple assignment randomized clinical trial in acute leukemia are presented. © 2018, The International Biometric Society.

Recognition of Banknote Fitness Based on a Fuzzy System Using Visible Light Reflection and Near-infrared Light Transmission Images.

PubMed

Kwon, Seung Yong; Pham, Tuyen Danh; Park, Kang Ryoung; Jeong, Dae Sik; Yoon, Sungsoo

2016-06-11

Fitness classification is a technique to assess the quality of banknotes in order to determine whether they are usable. Banknote classification techniques are useful in preventing problems that arise from the circulation of substandard banknotes (such as recognition failures, or bill jams in automated teller machines (ATMs) or bank counting machines). By and large, fitness classification continues to be carried out by humans, and this can cause the problem of varying fitness classifications for the same bill by different evaluators, and requires a lot of time. To address these problems, this study proposes a fuzzy system-based method that can reduce the processing time needed for fitness classification, and can determine the fitness of banknotes through an objective, systematic method rather than subjective judgment. Our algorithm was an implementation to actual banknote counting machine. Based on the results of tests on 3856 banknotes in United States currency (USD), 3956 in Korean currency (KRW), and 2300 banknotes in Indian currency (INR) using visible light reflection (VR) and near-infrared light transmission (NIRT) imaging, the proposed method was found to yield higher accuracy than prevalent banknote fitness classification methods. Moreover, it was confirmed that the proposed algorithm can operate in real time, not only in a normal PC environment, but also in an embedded system environment of a banknote counting machine.

Recognition of Banknote Fitness Based on a Fuzzy System Using Visible Light Reflection and Near-infrared Light Transmission Images

PubMed Central

Kwon, Seung Yong; Pham, Tuyen Danh; Park, Kang Ryoung; Jeong, Dae Sik; Yoon, Sungsoo

2016-01-01

Fitness classification is a technique to assess the quality of banknotes in order to determine whether they are usable. Banknote classification techniques are useful in preventing problems that arise from the circulation of substandard banknotes (such as recognition failures, or bill jams in automated teller machines (ATMs) or bank counting machines). By and large, fitness classification continues to be carried out by humans, and this can cause the problem of varying fitness classifications for the same bill by different evaluators, and requires a lot of time. To address these problems, this study proposes a fuzzy system-based method that can reduce the processing time needed for fitness classification, and can determine the fitness of banknotes through an objective, systematic method rather than subjective judgment. Our algorithm was an implementation to actual banknote counting machine. Based on the results of tests on 3856 banknotes in United States currency (USD), 3956 in Korean currency (KRW), and 2300 banknotes in Indian currency (INR) using visible light reflection (VR) and near-infrared light transmission (NIRT) imaging, the proposed method was found to yield higher accuracy than prevalent banknote fitness classification methods. Moreover, it was confirmed that the proposed algorithm can operate in real time, not only in a normal PC environment, but also in an embedded system environment of a banknote counting machine. PMID:27294940

Early developed ASD (adjacent segmental disease) in patients after surgical treatment of the spine due to cancer metastases.

PubMed

Guzik, Grzegorz

2017-05-12

The causes of ASD are still relatively unknown. Correlation between clinical status of patients and radiological MRI findings is of primary importance. The radiological classifications proposed by Pfirmann and Oner are most commonly used to assess intradiscal degenerative changes. The aim of the study was to assess the influence of the extension of spine fixation on the risk of developing ASD in a short time after surgery. A total of 332 patients with spinal tumors were treated in our hospital between 2010 and 2013. Of these patients, 287 underwent surgeries. A follow-up MRI examination was performed 12 months after surgical treatment. The study population comprised of 194 patients. Among metastases, breast cancer was predominant (29%); neurological deficits were detected in 76 patients. Metastases were seen in the thoracic (45%) and lumbar (30%) spine; in 25% of cases, they were of multisegmental character. Pathological fractures concerned 88% of the patients. Statistical calculations were made using the χ2 test. Statistical analysis was done using the Statistica v. 10 software. A p value <0.05 was accepted as statistically significant. The study population was divided on seven groups according to applied treatment. Clinical signs of ASD were noted in only seven patients. Two patients had symptoms of nerve root irritation in the lumbar spine. Twenty-two patients (11%) were diagnosed with ASD according to the MRI classifications by Oner, Rijt, and Ramos, while the more sensitive Pfirmann classification allowed to detect the disease in 46 patients (24%). Healthy or almost healthy discs of Oner type I correlated with the criteria of Pfirmann types II and III. The percentage of the incidence of ASD diagnosed 1 year after the surgery using the Pfirmann classifications was significantly higher than diagnosed according to the clinical examination. The incidence of ASD in patients after spine surgeries due to cancer metastases does not differ between the study groups. ASD detectability based on clinical signs is significantly lower than ASD detectability based on MR images according to the system by Pfirrmann et.al. ASD risk increase among patients with multilevel fixation.

Molecular classification of gastric adenocarcinoma: translating new insights from the cancer genome atlas research network.

PubMed

Sunakawa, Yu; Lenz, Heinz-Josef

2015-04-01

Gastric cancer is a heterogenous cancer, which may be classified into several distinct subtypes based on pathology and epidemiology, each with different initiating pathological processes and each possibly having different tumor biology. A classification of gastric cancer should be important to select patients who can benefit from the targeted therapies or to precisely predict prognosis. The Cancer Genome Atlas (TCGA) study collaborated with previous reports regarding subtyping gastric cancer but also proposed a refined classification based on molecular characteristics. The addition of the new molecular classification strategy to a current classical subtyping may be a promising option, particularly stratification by Epstein-Barr virus (EBV) and microsatellite instability (MSI) statuses. According to TCGA study, EBV gastric cancer patients may benefit the programmed cell death protein 1 (PD-1)/programmed death-ligand 1 (PD-L1) antibodies or phosphoinositide 3-kinase (PI3K) inhibitors which are now being developed. The discoveries of predictive biomarkers should improve patient care and individualized medicine in the management since the targeted therapies may have the potential to change the landscape of gastric cancer treatment, moreover leading to both better understanding of the heterogeneity and better outcomes. Patient enrichment by predictive biomarkers for new treatment strategies will be critical to improve clinical outcomes. Additionally, liquid biopsies will be able to enable us to monitor in real-time molecular escape mechanism, resulting in better treatment strategies.

The Drug Abuse Prevention and Control Act of 1970: Retrospective Assessments of Disparate Treatment and Consequential Impact.

PubMed

Yamatani, Hide; Feit, Marvin; Mann, Aaron

2017-01-01

Although the basic paradigm of the U.S. federal drug policy targeting the supply and demand reduction has not changed since its enactment in 1970, there have been seriously undesirable disparate treatments and impacts among various population groups. Although U.S. Congress could not define what is discrimination, it did provide two major criteria for the assessment of discriminatory practices as follows: (a) disparate treatment-basing a key decision on association with any of the five prohibited individual's demographic classifications (race, color, religion, sex, or national origin); and (b) disparate impact-correlation between any of the five prohibited demographic classifications and the key outcomes. In reference to those criteria, this article describes evidence-based indicators of national failure of the Comprehensive Drug Abuse Prevention and Control Act.

Automated simultaneous multiple feature classification of MTI data

NASA Astrophysics Data System (ADS)

Harvey, Neal R.; Theiler, James P.; Balick, Lee K.; Pope, Paul A.; Szymanski, John J.; Perkins, Simon J.; Porter, Reid B.; Brumby, Steven P.; Bloch, Jeffrey J.; David, Nancy A.; Galassi, Mark C.

2002-08-01

Los Alamos National Laboratory has developed and demonstrated a highly capable system, GENIE, for the two-class problem of detecting a single feature against a background of non-feature. In addition to the two-class case, however, a commonly encountered remote sensing task is the segmentation of multispectral image data into a larger number of distinct feature classes or land cover types. To this end we have extended our existing system to allow the simultaneous classification of multiple features/classes from multispectral data. The technique builds on previous work and its core continues to utilize a hybrid evolutionary-algorithm-based system capable of searching for image processing pipelines optimized for specific image feature extraction tasks. We describe the improvements made to the GENIE software to allow multiple-feature classification and describe the application of this system to the automatic simultaneous classification of multiple features from MTI image data. We show the application of the multiple-feature classification technique to the problem of classifying lava flows on Mauna Loa volcano, Hawaii, using MTI image data and compare the classification results with standard supervised multiple-feature classification techniques.

Classification of nasolabial folds in Asians and the corresponding surgical approaches: By Shanghai 9th People's Hospital.

PubMed

Zhang, Lu; Tang, Meng-Yao; Jin, Rong; Zhang, Ying; Shi, Yao-Ming; Sun, Bao-Shan; Zhang, Yu-Guang

2015-07-01

One of the earliest signs of aging appears in the nasolabial fold, which is a special anatomical region that requires many factors for comprehensive assessment. Hence, it is inadequate to rely on a single index to facilitate the classification of nasolabial folds. Through clinical observation, we have observed that traditional filling treatments provide little improvement for some patients, which prompted us to seek a more specific and scientific classification standard and assessment system. A total of 900 patients who sought facial rejuvenation treatment in Shanghai 9th People's Hospital were invited in this study. We observed the different nasolabial fold traits for different age groups and in different states, and the results were compared with the Wrinkle Severity Rating Scale (WSRS). We summarized the data, presented a classification scheme, and proposed a selection of treatment options. Consideration of the anatomical and histological features of nasolabial folds allowed us to divide nasolabial folds into five types, namely the skin type, fat pad type, muscular type, bone retrusion type, and hybrid type. Because different types of nasolabial folds require different treatments, it is crucial to accurately assess and correctly classify the conditions. Copyright © 2015 British Association of Plastic, Reconstructive and Aesthetic Surgeons. Published by Elsevier Ltd. All rights reserved.

Comprehensible knowledge model creation for cancer treatment decision making.

PubMed

Afzal, Muhammad; Hussain, Maqbool; Ali Khan, Wajahat; Ali, Taqdir; Lee, Sungyoung; Huh, Eui-Nam; Farooq Ahmad, Hafiz; Jamshed, Arif; Iqbal, Hassan; Irfan, Muhammad; Abbas Hydari, Manzar

2017-03-01

A wealth of clinical data exists in clinical documents in the form of electronic health records (EHRs). This data can be used for developing knowledge-based recommendation systems that can assist clinicians in clinical decision making and education. One of the big hurdles in developing such systems is the lack of automated mechanisms for knowledge acquisition to enable and educate clinicians in informed decision making. An automated knowledge acquisition methodology with a comprehensible knowledge model for cancer treatment (CKM-CT) is proposed. With the CKM-CT, clinical data are acquired automatically from documents. Quality of data is ensured by correcting errors and transforming various formats into a standard data format. Data preprocessing involves dimensionality reduction and missing value imputation. Predictive algorithm selection is performed on the basis of the ranking score of the weighted sum model. The knowledge builder prepares knowledge for knowledge-based services: clinical decisions and education support. Data is acquired from 13,788 head and neck cancer (HNC) documents for 3447 patients, including 1526 patients of the oral cavity site. In the data quality task, 160 staging values are corrected. In the preprocessing task, 20 attributes and 106 records are eliminated from the dataset. The Classification and Regression Trees (CRT) algorithm is selected and provides 69.0% classification accuracy in predicting HNC treatment plans, consisting of 11 decision paths that yield 11 decision rules. Our proposed methodology, CKM-CT, is helpful to find hidden knowledge in clinical documents. In CKM-CT, the prediction models are developed to assist and educate clinicians for informed decision making. The proposed methodology is generalizable to apply to data of other domains such as breast cancer with a similar objective to assist clinicians in decision making and education. Copyright © 2017 Elsevier Ltd. All rights reserved.

Improved wavelet packet classification algorithm for vibrational intrusions in distributed fiber-optic monitoring systems

NASA Astrophysics Data System (ADS)

Wang, Bingjie; Pi, Shaohua; Sun, Qi; Jia, Bo

2015-05-01

An improved classification algorithm that considers multiscale wavelet packet Shannon entropy is proposed. Decomposition coefficients at all levels are obtained to build the initial Shannon entropy feature vector. After subtracting the Shannon entropy map of the background signal, components of the strongest discriminating power in the initial feature vector are picked out to rebuild the Shannon entropy feature vector, which is transferred to radial basis function (RBF) neural network for classification. Four types of man-made vibrational intrusion signals are recorded based on a modified Sagnac interferometer. The performance of the improved classification algorithm has been evaluated by the classification experiments via RBF neural network under different diffusion coefficients. An 85% classification accuracy rate is achieved, which is higher than the other common algorithms. The classification results show that this improved classification algorithm can be used to classify vibrational intrusion signals in an automatic real-time monitoring system.

[Landscape classification: research progress and development trend].

PubMed

Liang, Fa-Chao; Liu, Li-Ming

2011-06-01

Landscape classification is the basis of the researches on landscape structure, process, and function, and also, the prerequisite for landscape evaluation, planning, protection, and management, directly affecting the precision and practicability of landscape research. This paper reviewed the research progress on the landscape classification system, theory, and methodology, and summarized the key problems and deficiencies of current researches. Some major landscape classification systems, e. g. , LANMAP and MUFIC, were introduced and discussed. It was suggested that a qualitative and quantitative comprehensive classification based on the ideology of functional structure shape and on the integral consideration of landscape classification utility, landscape function, landscape structure, physiogeographical factors, and human disturbance intensity should be the major research directions in the future. The integration of mapping, 3S technology, quantitative mathematics modeling, computer artificial intelligence, and professional knowledge to enhance the precision of landscape classification would be the key issues and the development trend in the researches of landscape classification.

Selective classification for improved robustness of myoelectric control under nonideal conditions.

PubMed

Scheme, Erik J; Englehart, Kevin B; Hudgins, Bernard S

2011-06-01

Recent literature in pattern recognition-based myoelectric control has highlighted a disparity between classification accuracy and the usability of upper limb prostheses. This paper suggests that the conventionally defined classification accuracy may be idealistic and may not reflect true clinical performance. Herein, a novel myoelectric control system based on a selective multiclass one-versus-one classification scheme, capable of rejecting unknown data patterns, is introduced. This scheme is shown to outperform nine other popular classifiers when compared using conventional classification accuracy as well as a form of leave-one-out analysis that may be more representative of real prosthetic use. Additionally, the classification scheme allows for real-time, independent adjustment of individual class-pair boundaries making it flexible and intuitive for clinical use.

Classification of constraints and degrees of freedom for quadratic discrete actions

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

Höhn, Philipp A., E-mail: phoehn@perimeterinstitute.ca

2014-11-15

We provide a comprehensive classification of constraints and degrees of freedom for variational discrete systems governed by quadratic actions. This classification is based on the different types of null vectors of the Lagrangian two-form and employs the canonical formalism developed in Dittrich and Höhn [“Constraint analysis for variational discrete systems,” J. Math. Phys. 54, 093505 (2013); e-print http://arxiv.org/abs/arXiv:1303.4294 [math-ph

Osteogenesis imperfecta.

PubMed

Marini, Joan C; Forlino, Antonella; Bächinger, Hans Peter; Bishop, Nick J; Byers, Peter H; Paepe, Anne De; Fassier, Francois; Fratzl-Zelman, Nadja; Kozloff, Kenneth M; Krakow, Deborah; Montpetit, Kathleen; Semler, Oliver

2017-08-18

Skeletal deformity and bone fragility are the hallmarks of the brittle bone dysplasia osteogenesis imperfecta. The diagnosis of osteogenesis imperfecta usually depends on family history and clinical presentation characterized by a fracture (or fractures) during the prenatal period, at birth or in early childhood; genetic tests can confirm diagnosis. Osteogenesis imperfecta is caused by dominant autosomal mutations in the type I collagen coding genes (COL1A1 and COL1A2) in about 85% of individuals, affecting collagen quantity or structure. In the past decade, (mostly) recessive, dominant and X-linked defects in a wide variety of genes encoding proteins involved in type I collagen synthesis, processing, secretion and post-translational modification, as well as in proteins that regulate the differentiation and activity of bone-forming cells have been shown to cause osteogenesis imperfecta. The large number of causative genes has complicated the classic classification of the disease, and although a new genetic classification system is widely used, it is still debated. Phenotypic manifestations in many organs, in addition to bone, are reported, such as abnormalities in the cardiovascular and pulmonary systems, skin fragility, muscle weakness, hearing loss and dentinogenesis imperfecta. Management involves surgical and medical treatment of skeletal abnormalities, and treatment of other complications. More innovative approaches based on gene and cell therapy, and signalling pathway alterations, are under investigation.

Overview of the 8th Edition TNM Classification for Head and Neck Cancer.

PubMed

Huang, Shao Hui; O'Sullivan, Brian

2017-07-01

The main purpose of the TNM system is to provide an anatomic-based classification to adequately depict cancer prognosis. Accurate cancer staging is important for treatment selection and outcome prediction, research design, and cancer control activities. To maintain clinical relevance, periodical updates to TNM are necessary. The recently published 8th edition TNM classification institutes the following changes to the staging of head and neck (excluding thyroid cancer): new stage classifications [HPV-related oropharyngeal cancer (HPV+ OPC) and soft tissue sarcoma of the head and neck (HN-STS)] and modification of T and N categories [T and N categories for nasopharyngeal cancer (NPC), T categories for oral cavity squamous cell carcinomas (OSCC), N categories for non-viral related head and neck cancer and unknown primary (CUP), and T categories for head and neck cutaneous carcinoma]. These changes reflect better understanding tumor biology and clinical behavior (e.g., HPV+ OPC and HN-STS), improved outcomes associated with technical advances in diagnosis and treatment (e.g., NPC), evolving knowledge about additional prognostic factors and risk stratification from research and observation (e.g., inclusion of depth of invasion variable for OSCC, inclusion of extranodal extension variable for all non-viral head and neck cancer, and reintroduction of size criteria for non-Merkel cell cutaneous carcinoma of the head and neck). This review summarizes the changes and potential advantages and limitations/caveats associated with them. Further evidence is needed to evaluate whether these changes would result in improvement in TNM stage performance to better serve the needs for clinical care, research, and cancer control.

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

Safety of dermatologic medications in pregnancy and lactation: Part I. Pregnancy.

PubMed

Murase, Jenny E; Heller, Misha M; Butler, Daniel C

2014-03-01

Dermatologists are frequently faced with questions about the safety of commonly prescribed topical and systemic medications during pregnancy and lactation from women of childbearing age who are pregnant, considering pregnancy, or breastfeeding. Safety data, particularly regarding medications that are unique to dermatology, can be difficult to locate and are not consolidated in a single reference guide for clinicians. Parts I and II of this continuing medical education article provide a capsule summary of key points for the most commonly prescribed dermatologic medications to facilitate patient medication risk counseling in pregnancy. A summary table details safety classification data for 3 primary international classification systems: the US Food and Drug Administration, the Swedish Catalogue of Approved Drugs, and the Australian Drug Evaluation Committee. In addition, this table includes an alternative pregnancy classification system developed by a consortium of active members of teratology societies in the US and Europe detailed in Drugs during Pregnancy and Lactation: Treatment Options and Risk Assessment and a safety classification system developed for breastfeeding mothers detailed in Medications and Mother's Milk. Copyright © 2013 American Academy of Dermatology, Inc. Published by Mosby, Inc. All rights reserved.

Clonal Selection Based Artificial Immune System for Generalized Pattern Recognition

NASA Technical Reports Server (NTRS)

Huntsberger, Terry

2011-01-01

The last two decades has seen a rapid increase in the application of AIS (Artificial Immune Systems) modeled after the human immune system to a wide range of areas including network intrusion detection, job shop scheduling, classification, pattern recognition, and robot control. JPL (Jet Propulsion Laboratory) has developed an integrated pattern recognition/classification system called AISLE (Artificial Immune System for Learning and Exploration) based on biologically inspired models of B-cell dynamics in the immune system. When used for unsupervised or supervised classification, the method scales linearly with the number of dimensions, has performance that is relatively independent of the total size of the dataset, and has been shown to perform as well as traditional clustering methods. When used for pattern recognition, the method efficiently isolates the appropriate matches in the data set. The paper presents the underlying structure of AISLE and the results from a number of experimental studies.

Human error analysis of commercial aviation accidents using the human factors analysis and classification system (HFACS)

DOT National Transportation Integrated Search

2001-02-01

The Human Factors Analysis and Classification System (HFACS) is a general human error framework : originally developed and tested within the U.S. military as a tool for investigating and analyzing the human : causes of aviation accidents. Based upon ...

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.

Autonomous target recognition using remotely sensed surface vibration measurements

NASA Astrophysics Data System (ADS)

Geurts, James; Ruck, Dennis W.; Rogers, Steven K.; Oxley, Mark E.; Barr, Dallas N.

1993-09-01

The remotely measured surface vibration signatures of tactical military ground vehicles are investigated for use in target classification and identification friend or foe (IFF) systems. The use of remote surface vibration sensing by a laser radar reduces the effects of partial occlusion, concealment, and camouflage experienced by automatic target recognition systems using traditional imagery in a tactical battlefield environment. Linear Predictive Coding (LPC) efficiently represents the vibration signatures and nearest neighbor classifiers exploit the LPC feature set using a variety of distortion metrics. Nearest neighbor classifiers achieve an 88 percent classification rate in an eight class problem, representing a classification performance increase of thirty percent from previous efforts. A novel confidence figure of merit is implemented to attain a 100 percent classification rate with less than 60 percent rejection. The high classification rates are achieved on a target set which would pose significant problems to traditional image-based recognition systems. The targets are presented to the sensor in a variety of aspects and engine speeds at a range of 1 kilometer. The classification rates achieved demonstrate the benefits of using remote vibration measurement in a ground IFF system. The signature modeling and classification system can also be used to identify rotary and fixed-wing targets.

Image-based fall detection and classification of a user with a walking support system

NASA Astrophysics Data System (ADS)

Taghvaei, Sajjad; Kosuge, Kazuhiro

2017-10-01

The classification of visual human action is important in the development of systems that interact with humans. This study investigates an image-based classification of the human state while using a walking support system to improve the safety and dependability of these systems.We categorize the possible human behavior while utilizing a walker robot into eight states (i.e., sitting, standing, walking, and five falling types), and propose two different methods, namely, normal distribution and hidden Markov models (HMMs), to detect and recognize these states. The visual feature for the state classification is the centroid position of the upper body, which is extracted from the user's depth images. The first method shows that the centroid position follows a normal distribution while walking, which can be adopted to detect any non-walking state. The second method implements HMMs to detect and recognize these states. We then measure and compare the performance of both methods. The classification results are employed to control the motion of a passive-type walker (called "RT Walker") by activating its brakes in non-walking states. Thus, the system can be used for sit/stand support and fall prevention. The experiments are performed with four subjects, including an experienced physiotherapist. Results show that the algorithm can be adapted to the new user's motion pattern within 40 s, with a fall detection rate of 96.25% and state classification rate of 81.0%. The proposed method can be implemented to other abnormality detection/classification applications that employ depth image-sensing devices.

A classification of growth friendly spine implants.

PubMed

Skaggs, David L; Akbarnia, Behrooz A; Flynn, John M; Myung, Karen S; Sponseller, Paul D; Vitale, Michael G

2014-01-01

Various types of spinal implants have been used with the objective of minimizing spinal deformities while maximizing the spine and thoracic growth in a growing child with a spinal deformity. The aim of this study was to describe a classification system of growth friendly spinal implants to allow researchers and clinicians to have a common language and facilitate comparative studies. Growth friendly spinal implant systems fall into 3 categories based upon the forces of correction the implants exert on the spine, which are as follows: Distraction-based systems correct spinal deformities by mechanically applying a distractive force across a deformed segment with anchors at the top and bottom of the implants, which commonly attach to the spine, rib, and/or the pelvis. The present examples of distraction-based implants are spine-based or rib-based growing rods, vertical expandable titanium rib prosthesis, and remotely expandable devices. Compression-based systems correct spinal deformities with a compressive force applied to the convexity of the curve causing convex growth inhibition. This compressive force may be generated both mechanically at the time of implantation, as well as over time resulting from longitudinal growth of vertebral endplates hindered by the spinal implants. Examples of compression-based systems are vertebral staples and tethers. Guided growth systems correct spinal deformity by anchoring multiple vertebrae (usually including the apical vertebrae) to rods with mechanical forces including translation at the time of the initial implant. The majority of the anchors are not rigidly attached to the rods, thus permitting longitudinal growth over time as the anchors slide over the rods. Examples of guided growth systems include the Luque trolley and Shilla. Each system has its benefits and shortcomings. Knowledge of the fundamental principles upon which these systems are based may aid the clinician to choose an appropriate treatment for patients. Having a common language for these systems may aid in comparative research. Vertical expandable titanium rib prosthesis is used with humanitarian exemption. The other devices mentioned in this manuscript are not approved for growing constructs by the Food and Drug Administration and are used off-label.

An Expert System for Diagnosis of Sleep Disorder Using Fuzzy Rule-Based Classification Systems

NASA Astrophysics Data System (ADS)

Septem Riza, Lala; Pradini, Mila; Fitrajaya Rahman, Eka; Rasim

2017-03-01

Sleep disorder is an anomaly that could cause problems for someone’ sleeping pattern. Nowadays, it becomes an issue since people are getting busy with their own business and have no time to visit the doctors. Therefore, this research aims to develop a system used for diagnosis of sleep disorder using Fuzzy Rule-Based Classification System (FRBCS). FRBCS is a method based on the fuzzy set concepts. It consists of two steps: (i) constructing a model/knowledge involving rulebase and database, and (ii) prediction over new data. In this case, the knowledge is obtained from experts whereas in the prediction stage, we perform fuzzification, inference, and classification. Then, a platform implementing the method is built with a combination between PHP and the R programming language using the “Shiny” package. To validate the system that has been made, some experiments have been done using data from a psychiatric hospital in West Java, Indonesia. Accuracy of the result and computation time are 84.85% and 0.0133 seconds, respectively.

Surgical and molecular pathology of pancreatic neoplasms.

PubMed

Hackeng, Wenzel M; Hruban, Ralph H; Offerhaus, G Johan A; Brosens, Lodewijk A A

2016-06-07

Histologic characteristics have proven to be very useful for classifying different types of tumors of the pancreas. As a result, the major tumor types in the pancreas have long been classified based on their microscopic appearance. Recent advances in whole exome sequencing, gene expression profiling, and knowledge of tumorigenic pathways have deepened our understanding of the underlying biology of pancreatic neoplasia. These advances have not only confirmed the traditional histologic classification system, but also opened new doors to early diagnosis and targeted treatment. This review discusses the histopathology, genetic and epigenetic alterations and potential treatment targets of the five major malignant pancreatic tumors - pancreatic ductal adenocarcinoma, pancreatic neuroendocrine tumor, solid-pseudopapillary neoplasm, acinar cell carcinoma and pancreatoblastoma.

Association Between Severity and the Determinant-Based Classification, Atlanta 2012 and Atlanta 1992, in Acute Pancreatitis

PubMed Central

Chen, Yuhui; Ke, Lu; Tong, Zhihui; Li, Weiqin; Li, Jieshou

2015-01-01

Abstract Recently, the determinant-based classification (DBC) and the Atlanta 2012 have been proposed to provide a basis for study and treatment of acute pancreatitis (AP). The present study aimed to evaluate the association between severity and the DBC, the Atlanta 2012 and the Atlanta 1992, in AP. Patients admitted to our center with AP from January 2007 to July 2013 were reviewed retrospectively. Patients were assigned to severity categories for all the 3 classification systems. The primary outcomes include long-term clinical prognosis (mortality and length-of-hospital stay), major complications (intraabdominal hemorrhage, multiple-organ dysfunction, single organ failure [OF], and sepsis) and clinical interventions (surgical drainage, continuous renal replace therapy [CRRT] lasting time, and mechanical ventilation [MV] lasting time). The classification systems were validated and compared in terms of these abovementioned primary outcomes. A total of 395 patients were enrolled in this retrospective study with an overall 8.86% in-hospital mortality. Intraabdominal hemorrhage was present in 27 (6.84%) of the patients, multiple-organ dysfunction in 73(18.48%), single OF in 67 (16.96%), and sepsis in 73(18.48%). For each classification system, different categories regarding severity were associated with statistically different clinical mortality, major complications, and clinical interventions (P < 0.05). However, the Atlanta 2012 and the DBC performed better than the Atlanta 1992, and they were comparable in predicting mortality (area under curve [AUC] 0.899 and 0.955 vs 0.585, P < 0.05); intraabdominal hemorrhage (AUC 0.930 and 0.961 vs 0.583, P < 0.05), multiple-organ dysfunction (AUC 0.858 and 0.881 vs 0.595, P < 0.05), sepsis (AUC 0.826 and 0.879 vs 0.590, P < 0.05), and surgical drainage (AUC 0.900 and 0.847 vs 0.606, P < 0.05). For continuous variables, the Atlanta 2012 and the DBC were also better than the Atlanta 1992, and they were similar in predicting CRRT lasting time (Somer D 0.379 and 0.360 vs 0.210, P < 0.05) and MV lasting time (Somer D 0.344 and 0.336 vs 0.186, P < 0.05). All the 3 classification systems accurately classify the severity of AP. However, the Atlanta 2012 and the DBC performed better than the Atlanta 1992, and they were comparable in predicting long-term clinical prognosis, major complications, and clinical interventions. PMID:25837754

Using Gaussian mixture models to detect and classify dolphin whistles and pulses.

PubMed

Peso Parada, Pablo; Cardenal-López, Antonio

2014-06-01

In recent years, a number of automatic detection systems for free-ranging cetaceans have been proposed that aim to detect not just surfaced, but also submerged, individuals. These systems are typically based on pattern-recognition techniques applied to underwater acoustic recordings. Using a Gaussian mixture model, a classification system was developed that detects sounds in recordings and classifies them as one of four types: background noise, whistles, pulses, and combined whistles and pulses. The classifier was tested using a database of underwater recordings made off the Spanish coast during 2011. Using cepstral-coefficient-based parameterization, a sound detection rate of 87.5% was achieved for a 23.6% classification error rate. To improve these results, two parameters computed using the multiple signal classification algorithm and an unpredictability measure were included in the classifier. These parameters, which helped to classify the segments containing whistles, increased the detection rate to 90.3% and reduced the classification error rate to 18.1%. Finally, the potential of the multiple signal classification algorithm and unpredictability measure for estimating whistle contours and classifying cetacean species was also explored, with promising results.

Deep Convolutional Neural Network-Based Early Automated Detection of Diabetic Retinopathy Using Fundus Image.

PubMed

Xu, Kele; Feng, Dawei; Mi, Haibo

2017-11-23

The automatic detection of diabetic retinopathy is of vital importance, as it is the main cause of irreversible vision loss in the working-age population in the developed world. The early detection of diabetic retinopathy occurrence can be very helpful for clinical treatment; although several different feature extraction approaches have been proposed, the classification task for retinal images is still tedious even for those trained clinicians. Recently, deep convolutional neural networks have manifested superior performance in image classification compared to previous handcrafted feature-based image classification methods. Thus, in this paper, we explored the use of deep convolutional neural network methodology for the automatic classification of diabetic retinopathy using color fundus image, and obtained an accuracy of 94.5% on our dataset, outperforming the results obtained by using classical approaches.

The classification of phobic disorders.

PubMed

Sheehan, D V; Sheehan, K H

The history of classification of phobic disorders is reviewed. Problems in the ability of current classification schemes to predict, control and describe the relationship between the symptoms and other phenomena are outlined. A new classification of phobic disorders is proposed based on the presence or absence of an endogenous anxiety syndrome with the phobias. The two categories of phobic disorder have a different clinical presentation and course, a different mean age of onset, distribution of age of onset, sex distribution, response to treatment modalities, GSR testing and habituation response. Empirical evidence supporting this proposal is cited. This classification has heuristic merit in guiding research efforts and discussions and in directing the clinician to a simple and practical solution of his patient's phobic disorder.

Electroconvulsive therapy-induced brain functional connectivity predicts therapeutic efficacy in patients with schizophrenia: a multivariate pattern recognition study.

PubMed

Li, Peng; Jing, Ri-Xing; Zhao, Rong-Jiang; Ding, Zeng-Bo; Shi, Le; Sun, Hong-Qiang; Lin, Xiao; Fan, Teng-Teng; Dong, Wen-Tian; Fan, Yong; Lu, Lin

2017-05-11

Previous studies suggested that electroconvulsive therapy can influence regional metabolism and dopamine signaling, thereby alleviating symptoms of schizophrenia. It remains unclear what patients may benefit more from the treatment. The present study sought to identify biomarkers that predict the electroconvulsive therapy response in individual patients. Thirty-four schizophrenia patients and 34 controls were included in this study. Patients were scanned prior to treatment and after 6 weeks of treatment with antipsychotics only (n = 16) or a combination of antipsychotics and electroconvulsive therapy (n = 13). Subject-specific intrinsic connectivity networks were computed for each subject using a group information-guided independent component analysis technique. Classifiers were built to distinguish patients from controls and quantify brain states based on intrinsic connectivity networks. A general linear model was built on the classification scores of first scan (referred to as baseline classification scores) to predict treatment response. Classifiers built on the default mode network, the temporal lobe network, the language network, the corticostriatal network, the frontal-parietal network, and the cerebellum achieved a cross-validated classification accuracy of 83.82%, with specificity of 91.18% and sensitivity of 76.47%. After the electroconvulsive therapy, psychosis symptoms of the patients were relieved and classification scores of the patients were decreased. Moreover, the baseline classification scores were predictive for the treatment outcome. Schizophrenia patients exhibited functional deviations in multiple intrinsic connectivity networks which were able to distinguish patients from healthy controls at an individual level. Patients with lower classification scores prior to treatment had better treatment outcome, indicating that the baseline classification scores before treatment is a good predictor for treatment outcome. CONNECTIVITY NETWORKS REVEAL GOOD CANDIDATES FOR BRAIN STIMULATION: Connectivity patterns in the brain may help identify patients with schizophrenia most likely to benefit from electroconvulsive therapy. A team led by Lin Lu from Peking University, China, and Yong Fan from the University of Pennsylvania, USA, took functional magnetic resonance imaging (MRI) scans of 34 people with schizophrenia and 34 control individuals without mental illness. Those with schizophrenia were scanned before and after treatment; some received antipsychotics alone, others received medication plus electroconvulsive therapy. The researchers created organizational brain maps known as "intrinsic connectivity networks" for each individual, and showed that the neuroimaging pattern could discriminate between people with and without schizophrenia. For the schizophrenia patients, the connectivity networks taken prior to treatment also helped predict who would benefit from the brain-stimulation procedure. Such a biomarker could prove a useful diagnostic tool for clinicians.

Map Classification: A Comparison of Schemes with Special Reference to the Continent of Africa. Occasional Papers, Number 154.

ERIC Educational Resources Information Center

Merrett, Christopher E.

This guide to the theory and practice of map classification begins with a discussion of the filing of maps and the function of map classification based on area and theme as illustrated by four maps of Africa. The description of the various classification systems which follows is divided into book schemes with provision for maps (including Dewey…

Regression-Based Approach For Feature Selection In Classification Issues. Application To Breast Cancer Detection And Recurrence

NASA Astrophysics Data System (ADS)

Belciug, Smaranda; Serbanescu, Mircea-Sebastian

2015-09-01

Feature selection is considered a key factor in classifications/decision problems. It is currently used in designing intelligent decision systems to choose the best features which allow the best performance. This paper proposes a regression-based approach to select the most important predictors to significantly increase the classification performance. Application to breast cancer detection and recurrence using publically available datasets proved the efficiency of this technique.

A fuzzy hill-climbing algorithm for the development of a compact associative classifier

NASA Astrophysics Data System (ADS)

Mitra, Soumyaroop; Lam, Sarah S.

2012-02-01

Classification, a data mining technique, has widespread applications including medical diagnosis, targeted marketing, and others. Knowledge discovery from databases in the form of association rules is one of the important data mining tasks. An integrated approach, classification based on association rules, has drawn the attention of the data mining community over the last decade. While attention has been mainly focused on increasing classifier accuracies, not much efforts have been devoted towards building interpretable and less complex models. This paper discusses the development of a compact associative classification model using a hill-climbing approach and fuzzy sets. The proposed methodology builds the rule-base by selecting rules which contribute towards increasing training accuracy, thus balancing classification accuracy with the number of classification association rules. The results indicated that the proposed associative classification model can achieve competitive accuracies on benchmark datasets with continuous attributes and lend better interpretability, when compared with other rule-based systems.

[Who benefits from systemic therapy with a reflecting team?].

PubMed

Höger, C; Temme, M; Geiken, G

1994-03-01

In an evaluation study we investigated the effectiveness of the reflecting team approach compared to eclectic child psychiatric treatment in an outpatient setting and the indications for each type of treatment. The relationship between treatment outcome and diagnostic data obtained with the Multi-axial Classification Scheme was examined in 22 families treated with the reflecting team approach and in a second group of families matched on all important sociodemographic and diagnostic variables but receiving eclectic treatment. No difference was found between the two groups regarding symptom improvement or changes in family functioning. Regarding satisfaction with treatment, the reflecting team approach was superior to the eclectic modality. In the reflecting team group parental mental disorder and inadequate intra-familial communication (according to the new fifth axis of the Multi-axial Classification Scheme) had a negative effect on outcome.

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.

Fuzzy logic based on-line fault detection and classification in transmission line.

PubMed

Adhikari, Shuma; Sinha, Nidul; Dorendrajit, Thingam

2016-01-01

This study presents fuzzy logic based online fault detection and classification of transmission line using Programmable Automation and Control technology based National Instrument Compact Reconfigurable i/o (CRIO) devices. The LabVIEW software combined with CRIO can perform real time data acquisition of transmission line. When fault occurs in the system current waveforms are distorted due to transients and their pattern changes according to the type of fault in the system. The three phase alternating current, zero sequence and positive sequence current data generated by LabVIEW through CRIO-9067 are processed directly for relaying. The result shows that proposed technique is capable of right tripping action and classification of type of fault at high speed therefore can be employed in practical application.

Distinct types of primary cutaneous large B-cell lymphoma identified by gene expression profiling.

PubMed

Hoefnagel, Juliette J; Dijkman, Remco; Basso, Katia; Jansen, Patty M; Hallermann, Christian; Willemze, Rein; Tensen, Cornelis P; Vermeer, Maarten H

2005-05-01

In the European Organization for Research and Treatment of Cancer (EORTC) classification 2 types of primary cutaneous large B-cell lymphoma (PCLBCL) are distinguished: primary cutaneous follicle center cell lymphomas (PCFCCL) and PCLBCL of the leg (PCLBCL-leg). Distinction between both groups is considered important because of differences in prognosis (5-year survival > 95% and 52%, respectively) and the first choice of treatment (radiotherapy or systemic chemotherapy, respectively), but is not generally accepted. To establish a molecular basis for this subdivision in the EORTC classification, we investigated the gene expression profiles of 21 PCLBCLs by oligonucleotide microarray analysis. Hierarchical clustering based on a B-cell signature (7450 genes) classified PCLBCL into 2 distinct subgroups consisting of, respectively, 8 PCFCCLs and 13 PCLBCLsleg. PCLBCLs-leg showed increased expression of genes associated with cell proliferation; the proto-oncogenes Pim-1, Pim-2, and c-Myc; and the transcription factors Mum1/IRF4 and Oct-2. In the group of PCFCCL high expression of SPINK2 was observed. Further analysis suggested that PCFCCLs and PCLBCLs-leg have expression profiles similar to that of germinal center B-cell-like and activated B-cell-like diffuse large B-cell lymphoma, respectively. The results of this study suggest that different pathogenetic mechanisms are involved in the development of PCFCCLs and PCLBCLs-leg and provide molecular support for the subdivision used in the EORTC classification.

[Remote sensing monitoring and screening for urban black and odorous water body: A review.

PubMed

Shen, Qian; Zhu, Li; Cao, Hong Ye

2017-10-01

Continuous improvement of urban water environment and overall control of black and odorous water body are not merely national strategic needs with the action plan for prevention and treatment of water pollution, but also the hot issues attracting the attention of people. Most previous researches concentrated on the study of cause, evaluation and treatment measures of this phenomenon, and there are few researches on the monitoring using remote sensing, which is often a strain to meet the national needs of operational monitoring. This paper mainly summarized the urgent research problems, mainly including the identification and classification standard, research on the key technologies, and the frame of remote sensing screening systems for the urban black and odorous water body. The main key technologies were concluded too, including the high spatial resolution image preprocessing and extraction technique for black and odorous water body, the extraction of water information in city zones, the classification of the black and odorous water, and the identification and classification technique based on satellite-sky-ground remote sensing. This paper summarized the research progress and put forward research ideas of monitoring and screening urban black and odorous water body via high spatial resolution remote sensing technology, which would be beneficial to having an overall grasp of spatial distribution and improvement progress of black and odorous water body, and provide strong technical support for controlling urban black and odorous water body.

Pattern Classifications Using Grover's and Ventura's Algorithms in a Two-qubits System

NASA Astrophysics Data System (ADS)

Singh, Manu Pratap; Radhey, Kishori; Rajput, B. S.

2018-03-01

Carrying out the classification of patterns in a two-qubit system by separately using Grover's and Ventura's algorithms on different possible superposition, it has been shown that the exclusion superposition and the phase-invariance superposition are the most suitable search states obtained from two-pattern start-states and one-pattern start-states, respectively, for the simultaneous classifications of patterns. The higher effectiveness of Grover's algorithm for large search states has been verified but the higher effectiveness of Ventura's algorithm for smaller data base has been contradicted in two-qubit systems and it has been demonstrated that the unknown patterns (not present in the concerned data-base) are classified more efficiently than the known ones (present in the data-base) in both the algorithms. It has also been demonstrated that different states of Singh-Rajput MES obtained from the corresponding self-single- pattern start states are the most suitable search states for the classification of patterns |00>,|01 >, |10> and |11> respectively on the second iteration of Grover's method or the first operation of Ventura's algorithm.

Classification of follicular lymphoma images: a holistic approach with symbol-based machine learning methods.

PubMed

Zorman, Milan; Sánchez de la Rosa, José Luis; Dinevski, Dejan

2011-12-01

It is not very often to see a symbol-based machine learning approach to be used for the purpose of image classification and recognition. In this paper we will present such an approach, which we first used on the follicular lymphoma images. Lymphoma is a broad term encompassing a variety of cancers of the lymphatic system. Lymphoma is differentiated by the type of cell that multiplies and how the cancer presents itself. It is very important to get an exact diagnosis regarding lymphoma and to determine the treatments that will be most effective for the patient's condition. Our work was focused on the identification of lymphomas by finding follicles in microscopy images provided by the Laboratory of Pathology in the University Hospital of Tenerife, Spain. We divided our work in two stages: in the first stage we did image pre-processing and feature extraction, and in the second stage we used different symbolic machine learning approaches for pixel classification. Symbolic machine learning approaches are often neglected when looking for image analysis tools. They are not only known for a very appropriate knowledge representation, but also claimed to lack computational power. The results we got are very promising and show that symbolic approaches can be successful in image analysis applications.

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.

Traditional Chinese Medicine and Constitutional Medicine in China, Japan and Korea: A Comparative Study.

PubMed

Yu, Wenjun; Ma, Mingyue; Chen, Xuemei; Min, Jiayu; Li, Lingru; Zheng, Yanfei; Li, Yingshuai; Wang, Ji; Wang, Qi

2017-01-01

Traditional Chinese medicine (TCM), Japanese-Chinese medicine, and Korean Sasang constitutional medicine have common origins. However, the constitutional medicines of China, Japan, and Korea differ because of the influence of geographical culture, social environment, national practices, and other factors. This paper aimed to compare the constitutional medicines of China, Japan, and Korea in terms of theoretical origin, constitutional classification, constitution and pathogenesis, clinical applications and basic studies that were conducted. The constitutional theories of the three countries are all derived from the Canon of Internal Medicine or Treatise on Febrile and Miscellaneous Diseases of Ancient China. However, the three countries have different constitutional classifications and criteria. Medical sciences in the three countries focus on the clinical applications of constitutional theory. They all agree that different pathogenic laws that guide the treatment of diseases govern different constitutions; thus, patients with different constitutions are treated differently. The three countries also differ in terms of drug formulations and medication. Japanese medicine is prescribed only based on constitution. Korean medicine is based on treatment, in which drugs cannot be mixed. TCM synthesize the treatment model of constitution differentiation, disease differentiation and syndrome differentiation with the treatment thought of treating disease according to three categories of etiologic factors, which reflect the constitution as the characteristic of individual precision treatment. In conclusion, constitutional medicines of China, Japan, and Korea have the same theoretical origin, but differ in constitutional classification, clinical application of constitutional theory on the treatment of diseases, drug formulations and medication.

5 CFR 531.203 - Definitions.

Code of Federal Regulations, 2014 CFR

2014-01-01

... Schedule or GS means the classification and pay system established under 5 U.S.C. chapter 51 and subchapter... officers (LEOs) receiving LEO special base rates are covered by the GS classification and pay system but... a break in service of more than 3 days. (See § 531.241.) Any reference to employees, grades...

5 CFR 531.203 - Definitions.

Code of Federal Regulations, 2013 CFR

2013-01-01

... Schedule or GS means the classification and pay system established under 5 U.S.C. chapter 51 and subchapter... officers (LEOs) receiving LEO special base rates are covered by the GS classification and pay system but... a break in service of more than 3 days. (See § 531.241.) Any reference to employees, grades...

5 CFR 531.203 - Definitions.

Code of Federal Regulations, 2012 CFR

2012-01-01

... Schedule or GS means the classification and pay system established under 5 U.S.C. chapter 51 and subchapter... officers (LEOs) receiving LEO special base rates are covered by the GS classification and pay system but... a break in service of more than 3 days. (See § 531.241.) Any reference to employees, grades...

5 CFR 531.203 - Definitions.

Code of Federal Regulations, 2011 CFR

2011-01-01

... Schedule or GS means the classification and pay system established under 5 U.S.C. chapter 51 and subchapter... officers (LEOs) receiving LEO special base rates are covered by the GS classification and pay system but... a break in service of more than 3 days. (See § 531.241.) Any reference to employees, grades...

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.

21 CFR 862.1510 - Nitrite (nonquantitative) test system.

Code of Federal Regulations, 2010 CFR

2010-04-01

... (CONTINUED) MEDICAL DEVICES CLINICAL CHEMISTRY AND CLINICAL TOXICOLOGY DEVICES Clinical Chemistry Test... diagnosis and treatment of uninary tract infection of bacterial origin. (b) Classification. Class I (general...

21 CFR 862.1535 - Ornithine carbamyl transferase test system.

Code of Federal Regulations, 2010 CFR

2010-04-01

... and treatment of liver diseases, such as infectious hepatitis, acute cholecystitis (inflammation of the gall bladder), cirrhosis, and liver metastases. (b) Classification. Class I (general controls...

A canonical correlation analysis based EMG classification algorithm for eliminating electrode shift effect.

PubMed

Zhe Fan; Zhong Wang; Guanglin Li; Ruomei Wang

2016-08-01

Motion classification system based on surface Electromyography (sEMG) pattern recognition has achieved good results in experimental condition. But it is still a challenge for clinical implement and practical application. Many factors contribute to the difficulty of clinical use of the EMG based dexterous control. The most obvious and important is the noise in the EMG signal caused by electrode shift, muscle fatigue, motion artifact, inherent instability of signal and biological signals such as Electrocardiogram. In this paper, a novel method based on Canonical Correlation Analysis (CCA) was developed to eliminate the reduction of classification accuracy caused by electrode shift. The average classification accuracy of our method were above 95% for the healthy subjects. In the process, we validated the influence of electrode shift on motion classification accuracy and discovered the strong correlation with correlation coefficient of >0.9 between shift position data and normal position data.

Classification of driver fatigue in an electroencephalography-based countermeasure system with source separation module.

PubMed

Rifai Chai; Naik, Ganesh R; Tran, Yvonne; Sai Ho Ling; Craig, Ashley; Nguyen, Hung T

2015-08-01

An electroencephalography (EEG)-based counter measure device could be used for fatigue detection during driving. This paper explores the classification of fatigue and alert states using power spectral density (PSD) as a feature extractor and fuzzy swarm based-artificial neural network (ANN) as a classifier. An independent component analysis of entropy rate bound minimization (ICA-ERBM) is investigated as a novel source separation technique for fatigue classification using EEG analysis. A comparison of the classification accuracy of source separator versus no source separator is presented. Classification performance based on 43 participants without the inclusion of the source separator resulted in an overall sensitivity of 71.67%, a specificity of 75.63% and an accuracy of 73.65%. However, these results were improved after the inclusion of a source separator module, resulting in an overall sensitivity of 78.16%, a specificity of 79.60% and an accuracy of 78.88% (p <; 0.05).

Property Specification Patterns for intelligence building software

NASA Astrophysics Data System (ADS)

Chun, Seungsu

2018-03-01

In this paper, through the property specification pattern research for Modal MU(μ) logical aspects present a single framework based on the pattern of intelligence building software. In this study, broken down by state property specification pattern classification of Dwyer (S) and action (A) and was subdivided into it again strong (A) and weaknesses (E). Through these means based on a hierarchical pattern classification of the property specification pattern analysis of logical aspects Mu(μ) was applied to the pattern classification of the examples used in the actual model checker. As a result, not only can a more accurate classification than the existing classification systems were easy to create and understand the attributes specified.

Expert consensus statement to guide the evidence-based classification of Paralympic athletes with vision impairment: a Delphi study.

PubMed

Ravensbergen, H J C Rianne; Mann, D L; Kamper, S J

2016-04-01

Paralympic sports are required to develop evidence-based systems that allocate athletes into 'classes' on the basis of the impact of their impairment on sport performance. However, sports for athletes with vision impairment (VI) classify athletes solely based on the WHO criteria for low vision and blindness. One key barrier to evidence-based classification is the absence of guidance on how to address classification issues unique to VI sport. The aim of this study was to reach expert consensus on how issues specific to VI sport should be addressed in evidence-based classification. A four-round Delphi study was conducted with 25 participants who had expertise as a coach, athlete, classifier and/or administrator in Paralympic sport for VI athletes. The experts agreed that the current method of classification does not fulfil the requirements of Paralympic classification, and that the system should be different for each sport to account for the sports' unique visual demands. Instead of relying only on tests of visual acuity and visual field, the panel agreed that additional tests are required to better account for the impact of impairment on sport performance. There was strong agreement that all athletes should not be required to wear a blindfold as a means of equalising the impairment during competition. There is strong support within the Paralympic movement to change the way that VI athletes are classified. This consensus statement provides clear guidance on how the most important issues specific to VI should be addressed, removing key barriers to the development of evidence-based classification. 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/

Deep learning application: rubbish classification with aid of an android device

NASA Astrophysics Data System (ADS)

Liu, Sijiang; Jiang, Bo; Zhan, Jie

2017-06-01

Deep learning is a very hot topic currently in pattern recognition and artificial intelligence researches. Aiming at the practical problem that people usually don't know correct classifications some rubbish should belong to, based on the powerful image classification ability of the deep learning method, we have designed a prototype system to help users to classify kinds of rubbish. Firstly the CaffeNet Model was adopted for our classification network training on the ImageNet dataset, and the trained network was deployed on a web server. Secondly an android app was developed for users to capture images of unclassified rubbish, upload images to the web server for analyzing backstage and retrieve the feedback, so that users can obtain the classification guide by an android device conveniently. Tests on our prototype system of rubbish classification show that: an image of one single type of rubbish with origin shape can be better used to judge its classification, while an image containing kinds of rubbish or rubbish with changed shape may fail to help users to decide rubbish's classification. However, the system still shows promising auxiliary function for rubbish classification if the network training strategy can be optimized further.

Classification systems for natural resource management

USGS Publications Warehouse

Kleckner, Richard L.

1981-01-01

Resource managers employ various types of resource classification systems in their management activities such as inventory, mapping, and data analysis. Classification is the ordering or arranging of objects into groups or sets on the basis of their relationships, and as such, provide the resource managers with a structure for organizing their needed information. In addition of conforming to certain logical principles, resource classifications should be flexible, widely applicable to a variety of environmental conditions, and useable with minimal training. The process of classification may be approached from the bottom up (aggregation) or the top down (subdivision) or a combination of both, depending on the purpose of the classification. Most resource classification systems in use today focus on a single resource and are used for a single, limited purpose. However, resource managers now must employ the concept of multiple use in their management activities. What they need is an integrated, ecologically based approach to resource classification which would fulfill multiple-use mandates. In an effort to achieve resource-data compatibility and data sharing among Federal agencies, and interagency agreement has been signed by five Federal agencies to coordinate and cooperate in the area of resource classification and inventory.

On the Implementation of a Land Cover Classification System for SAR Images Using Khoros

NASA Technical Reports Server (NTRS)

Medina Revera, Edwin J.; Espinosa, Ramon Vasquez

1997-01-01

The Synthetic Aperture Radar (SAR) sensor is widely used to record data about the ground under all atmospheric conditions. The SAR acquired images have very good resolution which necessitates the development of a classification system that process the SAR images to extract useful information for different applications. In this work, a complete system for the land cover classification was designed and programmed using the Khoros, a data flow visual language environment, taking full advantages of the polymorphic data services that it provides. Image analysis was applied to SAR images to improve and automate the processes of recognition and classification of the different regions like mountains and lakes. Both unsupervised and supervised classification utilities were used. The unsupervised classification routines included the use of several Classification/Clustering algorithms like the K-means, ISO2, Weighted Minimum Distance, and the Localized Receptive Field (LRF) training/classifier. Different texture analysis approaches such as Invariant Moments, Fractal Dimension and Second Order statistics were implemented for supervised classification of the images. The results and conclusions for SAR image classification using the various unsupervised and supervised procedures are presented based on their accuracy and performance.

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.

Training sample selection based on self-training for liver cirrhosis classification using ultrasound images

NASA Astrophysics Data System (ADS)

Fujita, Yusuke; Mitani, Yoshihiro; Hamamoto, Yoshihiko; Segawa, Makoto; Terai, Shuji; Sakaida, Isao

2017-03-01

Ultrasound imaging is a popular and non-invasive tool used in the diagnoses of liver disease. Cirrhosis is a chronic liver disease and it can advance to liver cancer. Early detection and appropriate treatment are crucial to prevent liver cancer. However, ultrasound image analysis is very challenging, because of the low signal-to-noise ratio of ultrasound images. To achieve the higher classification performance, selection of training regions of interest (ROIs) is very important that effect to classification accuracy. The purpose of our study is cirrhosis detection with high accuracy using liver ultrasound images. In our previous works, training ROI selection by MILBoost and multiple-ROI classification based on the product rule had been proposed, to achieve high classification performance. In this article, we propose self-training method to select training ROIs effectively. Evaluation experiments were performed to evaluate effect of self-training, using manually selected ROIs and also automatically selected ROIs. Experimental results show that self-training for manually selected ROIs achieved higher classification performance than other approaches, including our conventional methods. The manually ROI definition and sample selection are important to improve classification accuracy in cirrhosis detection using ultrasound images.

New insights into the classification and nomenclature of cortical GABAergic interneurons.

PubMed

DeFelipe, Javier; López-Cruz, Pedro L; Benavides-Piccione, Ruth; Bielza, Concha; Larrañaga, Pedro; Anderson, Stewart; Burkhalter, Andreas; Cauli, Bruno; Fairén, Alfonso; Feldmeyer, Dirk; Fishell, Gord; Fitzpatrick, David; Freund, Tamás F; González-Burgos, Guillermo; Hestrin, Shaul; Hill, Sean; Hof, Patrick R; Huang, Josh; Jones, Edward G; Kawaguchi, Yasuo; Kisvárday, Zoltán; Kubota, Yoshiyuki; Lewis, David A; Marín, Oscar; Markram, Henry; McBain, Chris J; Meyer, Hanno S; Monyer, Hannah; Nelson, Sacha B; Rockland, Kathleen; Rossier, Jean; Rubenstein, John L R; Rudy, Bernardo; Scanziani, Massimo; Shepherd, Gordon M; Sherwood, Chet C; Staiger, Jochen F; Tamás, Gábor; Thomson, Alex; Wang, Yun; Yuste, Rafael; Ascoli, Giorgio A

2013-03-01

A systematic classification and accepted nomenclature of neuron types is much needed but is currently lacking. This article describes a possible taxonomical solution for classifying GABAergic interneurons of the cerebral cortex based on a novel, web-based interactive system that allows experts to classify neurons with pre-determined criteria. Using Bayesian analysis and clustering algorithms on the resulting data, we investigated the suitability of several anatomical terms and neuron names for cortical GABAergic interneurons. Moreover, we show that supervised classification models could automatically categorize interneurons in agreement with experts' assignments. These results demonstrate a practical and objective approach to the naming, characterization and classification of neurons based on community consensus.

New insights into the classification and nomenclature of cortical GABAergic interneurons

PubMed Central

DeFelipe, Javier; López-Cruz, Pedro L.; Benavides-Piccione, Ruth; Bielza, Concha; Larrañaga, Pedro; Anderson, Stewart; Burkhalter, Andreas; Cauli, Bruno; Fairén, Alfonso; Feldmeyer, Dirk; Fishell, Gord; Fitzpatrick, David; Freund, Tamás F.; González-Burgos, Guillermo; Hestrin, Shaul; Hill, Sean; Hof, Patrick R.; Huang, Josh; Jones, Edward G.; Kawaguchi, Yasuo; Kisvárday, Zoltán; Kubota, Yoshiyuki; Lewis, David A.; Marín, Oscar; Markram, Henry; McBain, Chris J.; Meyer, Hanno S.; Monyer, Hannah; Nelson, Sacha B.; Rockland, Kathleen; Rossier, Jean; Rubenstein, John L. R.; Rudy, Bernardo; Scanziani, Massimo; Shepherd, Gordon M.; Sherwood, Chet C.; Staiger, Jochen F.; Tamás, Gábor; Thomson, Alex; Wang, Yun; Yuste, Rafael; Ascoli, Giorgio A.

2013-01-01

A systematic classification and accepted nomenclature of neuron types is much needed but is currently lacking. This article describes a possible taxonomical solution for classifying GABAergic interneurons of the cerebral cortex based on a novel, web-based interactive system that allows experts to classify neurons with pre-determined criteria. Using Bayesian analysis and clustering algorithms on the resulting data, we investigated the suitability of several anatomical terms and neuron names for cortical GABAergic interneurons. Moreover, we show that supervised classification models could automatically categorize interneurons in agreement with experts’ assignments. These results demonstrate a practical and objective approach to the naming, characterization and classification of neurons based on community consensus. PMID:23385869