AutoMap User’s Guide

DTIC Science & Technology

2006-10-01

Hierarchy of Pre-Processing Techniques 3. NLP (Natural Language Processing) Utilities 3.1 Named-Entity Recognition 3.1.1 Example for Named-Entity... Recognition 3.2 Symbol RemovalN-Gram Identification: Bi-Grams 4. Stemming 4.1 Stemming Example 5. Delete List 5.1 Open a Delete List 5.1.1 Small...iterative and involves several key processes: • Named-Entity Recognition Named-Entity Recognition is an Automap feature that allows you to

Segregation of anterior temporal regions critical for retrieving names of unique and nonunique entities reflects underlying long-range connectivity

PubMed Central

Mehta, Sonya; Inoue, Kayo; Rudrauf, David; Damasio, Hanna; Tranel, Daniel; Grabowski, Thomas

2015-01-01

Lesion-deficit studies support the hypothesis that the left anterior temporal lobe (ATL) plays a critical role in retrieving names of concrete entities. They further suggest that different regions of the left ATL process different conceptual categories. Here we test the specificity of these relationships and whether the anatomical segregation is related to the underlying organization of white matter connections. We reanalyzed data from a previous lesion study of naming and recognition across five categories of concrete entities. In voxelwise logistic regressions of lesion-deficit associations, we formally incorporated measures of disconnection of long-range association fiber tracts (FTs) and covaried for recognition and non-category specific naming deficits. We also performed fiber tractwise analyses to assess whether damage to specific FTs was preferentially associated with category-selective naming deficits. Damage to the basolateral ATL was associated with naming deficits for both unique (famous faces) and non-unique entities, whereas the damage to the temporal pole was associated with naming deficits for unique entities only. This segregation pattern remained after accounting for comorbid recognition deficits or naming deficits in other categories. The tractwise analyses showed that damage to the uncinate fasciculus was associated with naming impairments for unique entities, while damage to the inferior longitudinal fasciculus was associated with naming impairments for non-unique entities. Covarying for FT transection in voxelwise analyses rendered the cortical association for unique entities more focal. These results are consistent with the partial segregation of brain system support for name retrieval of unique and non-unique entities at both the level of cortical components and underlying white matter fiber bundles. Our study reconciles theoretic accounts of the functional organization of the left ATL by revealing both category-related processing and semantic hub sectors. PMID:26707082

Designing Rules for Accounting Transaction Identification based on Indonesian NLP

NASA Astrophysics Data System (ADS)

Iswandi, I.; Suwardi, I. S.; Maulidevi, N. U.

2017-03-01

Recording accounting transactions carried out by the evidence of the transactions. It can be invoices, receipts, letters of intent, electricity bill, telephone bill, etc. In this paper, we proposed design of rules to identify the entities located on the sales invoice. There are some entities identified in a sales invoice, namely : invoice date, company name, invoice number, product id, product name, quantity and total price. Identification this entities using named entity recognition method. The entities generated from the rules used as a basis for automation process of data input into the accounting system.

Entity-based Stochastic Analysis of Search Results for Query Expansion and Results Re-Ranking

DTIC Science & Technology

2015-11-20

pages) and struc- tured data (e.g. Linked Open Data ( LOD ) [8]) coexist in var- ious forms. An important observation is that entity names (like names of...the top-L (e.g. L = 1, 000) results are retrieved. Then, Named Entity Recognition (NER) is applied in these results for identifying LOD entities. In...the next (optional) step, more semantic information about the identified entities is retrieved from the LOD (like properties and related entities). A

Causal Claims and the Operational Environment: An Analysis of Conventional and Emergent Causality as Applied to the Systems in 2007-2008 Iraq

DTIC Science & Technology

2012-06-08

Douglas Ollivant, Surge, Iraq, Petraeus, COIN 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT 18 . NUMBER OF PAGES 19a. NAME OF...3See, New York Times, “Iraq 5 Years In,” http://www.nytimes.com/interactive/ 2008/03/ 18 /world...Government Printing Office, 26 September 2011), 5-2. 18 Open-systems or force fields are generally defined as any human or non-human entity that

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

PubMed Central

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

2015-01-01

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

Encoding of Fundamental Chemical Entities of Organic Reactivity Interest using chemical ontology and XML.

PubMed

Durairaj, Vijayasarathi; Punnaivanam, Sankar

2015-09-01

Fundamental chemical entities are identified in the context of organic reactivity and classified as appropriate concept classes namely ElectronEntity, AtomEntity, AtomGroupEntity, FunctionalGroupEntity and MolecularEntity. The entity classes and their subclasses are organized into a chemical ontology named "ChemEnt" for the purpose of assertion, restriction and modification of properties through entity relations. Individual instances of entity classes are defined and encoded as a library of chemical entities in XML. The instances of entity classes are distinguished with a unique notation and identification values in order to map them with the ontology definitions. A model GUI named Entity Table is created to view graphical representations of all the entity instances. The detection of chemical entities in chemical structures is achieved through suitable algorithms. The possibility of asserting properties to the entities at different levels and the mechanism of property flow within the hierarchical entity levels is outlined. Copyright © 2015 Elsevier Inc. All rights reserved.

42 CFR 455.104 - Disclosure by Medicaid providers and fiscal agents: Information on ownership and control.

Code of Federal Regulations, 2013 CFR

2013-10-01

..., fiscal agents, and managed care entities provide the following disclosures: (1)(i) The name and address... entity, fiscal agent, or managed care entity. The address for corporate entities must include as... disclosing entity as a spouse, parent, child, or sibling. (3) The name of any other disclosing entity (or...

Segregation of anterior temporal regions critical for retrieving names of unique and non-unique entities reflects underlying long-range connectivity.

PubMed

Mehta, Sonya; Inoue, Kayo; Rudrauf, David; Damasio, Hanna; Tranel, Daniel; Grabowski, Thomas

2016-02-01

Lesion-deficit studies support the hypothesis that the left anterior temporal lobe (ATL) plays a critical role in retrieving names of concrete entities. They further suggest that different regions of the left ATL process different conceptual categories. Here we test the specificity of these relationships and whether the anatomical segregation is related to the underlying organization of white matter connections. We reanalyzed data from a previous lesion study of naming and recognition across five categories of concrete entities. In voxelwise logistic regressions of lesion-deficit associations, we formally incorporated measures of disconnection of long-range association fiber tracts (FTs) and covaried for recognition and non-category-specific naming deficits. We also performed fiber tractwise analyses to assess whether damage to specific FTs was preferentially associated with category-selective naming deficits. Damage to the basolateral ATL was associated with naming deficits for both unique (famous faces) and non-unique entities, whereas the damage to the temporal pole was associated with naming deficits for unique entities only. This segregation pattern remained after accounting for comorbid recognition deficits or naming deficits in other categories. The tractwise analyses showed that damage to the uncinate fasciculus (UNC) was associated with naming impairments for unique entities, while damage to the inferior longitudinal fasciculus (ILF) was associated with naming impairments for non-unique entities. Covarying for FT transection in voxelwise analyses rendered the cortical association for unique entities more focal. These results are consistent with the partial segregation of brain system support for name retrieval of unique and non-unique entities at both the level of cortical components and underlying white matter fiber bundles. Our study reconciles theoretic accounts of the functional organization of the left ATL by revealing both category-related processing and semantic hub sectors. Copyright © 2015 Elsevier Ltd. All rights reserved.

Naming unique entities in the semantic variant of primary progressive aphasia and Alzheimer's disease: Towards a better understanding of the semantic impairment.

PubMed

Montembeault, M; Brambati, S M; Joubert, S; Boukadi, M; Chapleau, M; Laforce, R Jr; Wilson, M A; Macoir, J; Rouleau, I

2017-01-27

While the semantic variant of primary progressive aphasia (svPPA) is characterized by a predominant semantic memory impairment, episodic memory impairments are the clinical hallmark of Alzheimer's disease (AD). However, AD patients also present with semantic deficits, which are more severe for semantically unique entities (e.g. a famous person) than for common concepts (e.g. a beaver). Previous studies in these patient populations have largely focused on famous-person naming. Therefore, we aimed to evaluate if these impairments also extend to other semantically unique entities such as famous places and famous logos. In this study, 13 AD patients, 9 svPPA patients, and 12 cognitively unimpaired elderly subjects (CTRL) were tested with a picture-naming test of non-unique entities (Boston Naming Test) and three experimental tests of semantically unique entities assessing naming of famous persons, places, and logos. Both clinical groups were overall more impaired at naming semantically unique entities than non-unique entities. Naming impairments in AD and svPPA extended to the other types of semantically unique entities, since a CTRL>AD>svPPA pattern was found on the performance of all naming tests. Naming famous places and famous persons appeared to be most impaired in svPPA, and both specific and general semantic knowledge for these entities were affected in these patients. Although AD patients were most significantly impaired on famous-person naming, only their specific semantic knowledge was impaired, while general knowledge was preserved. Post-hoc neuroimaging analyses also showed that famous-person naming impairments in AD correlated with atrophy in the temporo-parietal junction, a region functionally associated with lexical access. In line with previous studies, svPPA patients' impairment in both naming and semantic knowledge suggest a more profound semantic impairment, while naming impairments in AD may arise to a greater extent from impaired lexical access, even though semantic impairment for specific knowledge is also present. These results highlight the critical importance of developing and using a variety of semantically-unique-entity naming tests in neuropsychological assessments of patients with neurodegenerative diseases, which may unveil different patterns of lexical-semantic deficits. Copyright © 2016 Elsevier Ltd. All rights reserved.

Boosting drug named entity recognition using an aggregate classifier.

PubMed

Korkontzelos, Ioannis; Piliouras, Dimitrios; Dowsey, Andrew W; Ananiadou, Sophia

2015-10-01

Drug named entity recognition (NER) is a critical step for complex biomedical NLP tasks such as the extraction of pharmacogenomic, pharmacodynamic and pharmacokinetic parameters. Large quantities of high quality training data are almost always a prerequisite for employing supervised machine-learning techniques to achieve high classification performance. However, the human labour needed to produce and maintain such resources is a significant limitation. In this study, we improve the performance of drug NER without relying exclusively on manual annotations. We perform drug NER using either a small gold-standard corpus (120 abstracts) or no corpus at all. In our approach, we develop a voting system to combine a number of heterogeneous models, based on dictionary knowledge, gold-standard corpora and silver annotations, to enhance performance. To improve recall, we employed genetic programming to evolve 11 regular-expression patterns that capture common drug suffixes and used them as an extra means for recognition. Our approach uses a dictionary of drug names, i.e. DrugBank, a small manually annotated corpus, i.e. the pharmacokinetic corpus, and a part of the UKPMC database, as raw biomedical text. Gold-standard and silver annotated data are used to train maximum entropy and multinomial logistic regression classifiers. Aggregating drug NER methods, based on gold-standard annotations, dictionary knowledge and patterns, improved the performance on models trained on gold-standard annotations, only, achieving a maximum F-score of 95%. In addition, combining models trained on silver annotations, dictionary knowledge and patterns are shown to achieve comparable performance to models trained exclusively on gold-standard data. The main reason appears to be the morphological similarities shared among drug names. We conclude that gold-standard data are not a hard requirement for drug NER. Combining heterogeneous models build on dictionary knowledge can achieve similar or comparable classification performance with that of the best performing model trained on gold-standard annotations. Copyright © 2015 The Authors. Published by Elsevier B.V. All rights reserved.

Combining Open-domain and Biomedical Knowledge for Topic Recognition in Consumer Health Questions.

PubMed

Mrabet, Yassine; Kilicoglu, Halil; Roberts, Kirk; Demner-Fushman, Dina

2016-01-01

Determining the main topics in consumer health questions is a crucial step in their processing as it allows narrowing the search space to a specific semantic context. In this paper we propose a topic recognition approach based on biomedical and open-domain knowledge bases. In the first step of our method, we recognize named entities in consumer health questions using an unsupervised method that relies on a biomedical knowledge base, UMLS, and an open-domain knowledge base, DBpedia. In the next step, we cast topic recognition as a binary classification problem of deciding whether a named entity is the question topic or not. We evaluated our approach on a dataset from the National Library of Medicine (NLM), introduced in this paper, and another from the Genetic and Rare Disease Information Center (GARD). The combination of knowledge bases outperformed the results obtained by individual knowledge bases by up to 16.5% F1 and achieved state-of-the-art performance. Our results demonstrate that combining open-domain knowledge bases with biomedical knowledge bases can lead to a substantial improvement in understanding user-generated health content.

LispSEI: The Programmer’s Manual

DTIC Science & Technology

1988-01-01

defun print-entities ( str entities etype) (format t str ) (dolist (entity entities) (format t " -A" (entity-name entity *type)))) (detun entity-name...fields are munged only after the filters are executed. This makes things much easier. ;:Algorithm: (1) get initial list. (2) take out those entitles which...don’t meet all the constraints. 1, 3) pass the entities list through all the filters.(4) munge the appropriate fields (5)u return the result. (defn s

A New Replicator: A theoretical framework for analysing replication

PubMed Central

2010-01-01

Background Replicators are the crucial entities in evolution. The notion of a replicator, however, is far less exact than the weight of its importance. Without identifying and classifying multiplying entities exactly, their dynamics cannot be determined appropriately. Therefore, it is importance to decide the nature and characteristics of any multiplying entity, in a detailed and formal way. Results Replication is basically an autocatalytic process which enables us to rest on the notions of formal chemistry. This statement has major implications. Simple autocatalytic cycle intermediates are considered as non-informational replicators. A consequence of which is that any autocatalytically multiplying entity is a replicator, be it simple or overly complex (even nests). A stricter definition refers to entities which can inherit acquired changes (informational replicators). Simple autocatalytic molecules (and nests) are excluded from this group. However, in turn, any entity possessing copiable information is to be named a replicator, even multicellular organisms. In order to deal with the situation, an abstract, formal framework is presented, which allows the proper identification of various types of replicators. This sheds light on the old problem of the units and levels of selection and evolution. A hierarchical classification for the partition of the replicator-continuum is provided where specific replicators are nested within more general ones. The classification should be able to be successfully applied to known replicators and also to future candidates. Conclusion This paper redefines the concept of the replicator from a bottom-up theoretical approach. The formal definition and the abstract models presented can distinguish between among all possible replicator types, based on their quantity of variable and heritable information. This allows for the exact identification of various replicator types and their underlying dynamics. The most important claim is that replication, in general, is basically autocatalysis, with a specific defined environment and selective force. A replicator is not valid unless its working environment, and the selective force to which it is subject, is specified. PMID:20219099

New tumor entities in the 4th edition of the World Health Organization classification of head and neck tumors: Nasal cavity, paranasal sinuses and skull base.

PubMed

Thompson, Lester D R; Franchi, Alessandro

2018-03-01

The World Health Organization recently published the 4th edition of the Classification of Head and Neck Tumors, including several new entities, emerging entities, and significant updates to the classification and characterization of tumor and tumor-like lesions, specifically as it relates to nasal cavity, paranasal sinuses, and skull base in this overview. Of note, three new entities (NUT carcinoma, seromucinous hamartoma, biphenotypic sinonasal sarcoma,) were added to this section, while emerging entities (SMARCB1-deficient carcinoma and HPV-related carcinoma with adenoid cystic-like features) and several tumor-like entities (respiratory epithelial adenomatoid hamartoma, chondromesenchymal hamartoma) were included as provisional diagnoses or discussed in the setting of the differential diagnosis. The sinonasal tract houses a significant diversity of entities, but interestingly, the total number of entities has been significantly reduced by excluding tumor types if they did not occur exclusively or predominantly at this site or if they are discussed in detail elsewhere in the book. Refinements to nomenclature and criteria were provided to sinonasal papilloma, borderline soft tissue tumors, and neuroendocrine neoplasms. Overall, the new WHO classification reflects the state of current understanding for many relatively rare neoplasms, with this article highlighting the most significant changes.

NELasso: Group-Sparse Modeling for Characterizing Relations Among Named Entities in News Articles.

PubMed

Tariq, Amara; Karim, Asim; Foroosh, Hassan

2017-10-01

Named entities such as people, locations, and organizations play a vital role in characterizing online content. They often reflect information of interest and are frequently used in search queries. Although named entities can be detected reliably from textual content, extracting relations among them is more challenging, yet useful in various applications (e.g., news recommending systems). In this paper, we present a novel model and system for learning semantic relations among named entities from collections of news articles. We model each named entity occurrence with sparse structured logistic regression, and consider the words (predictors) to be grouped based on background semantics. This sparse group LASSO approach forces the weights of word groups that do not influence the prediction towards zero. The resulting sparse structure is utilized for defining the type and strength of relations. Our unsupervised system yields a named entities' network where each relation is typed, quantified, and characterized in context. These relations are the key to understanding news material over time and customizing newsfeeds for readers. Extensive evaluation of our system on articles from TIME magazine and BBC News shows that the learned relations correlate with static semantic relatedness measures like WLM, and capture the evolving relationships among named entities over time.

The 2015 World Health Organization Classification of Lung Tumors: Impact of Genetic, Clinical and Radiologic Advances Since the 2004 Classification.

PubMed

Travis, William D; Brambilla, Elisabeth; Nicholson, Andrew G; Yatabe, Yasushi; Austin, John H M; Beasley, Mary Beth; Chirieac, Lucian R; Dacic, Sanja; Duhig, Edwina; Flieder, Douglas B; Geisinger, Kim; Hirsch, Fred R; Ishikawa, Yuichi; Kerr, Keith M; Noguchi, Masayuki; Pelosi, Giuseppe; Powell, Charles A; Tsao, Ming Sound; Wistuba, Ignacio

2015-09-01

The 2015 World Health Organization (WHO) Classification of Tumors of the Lung, Pleura, Thymus and Heart has just been published with numerous important changes from the 2004 WHO classification. The most significant changes in this edition involve (1) use of immunohistochemistry throughout the classification, (2) a new emphasis on genetic studies, in particular, integration of molecular testing to help personalize treatment strategies for advanced lung cancer patients, (3) a new classification for small biopsies and cytology similar to that proposed in the 2011 Association for the Study of Lung Cancer/American Thoracic Society/European Respiratory Society classification, (4) a completely different approach to lung adenocarcinoma as proposed by the 2011 Association for the Study of Lung Cancer/American Thoracic Society/European Respiratory Society classification, (5) restricting the diagnosis of large cell carcinoma only to resected tumors that lack any clear morphologic or immunohistochemical differentiation with reclassification of the remaining former large cell carcinoma subtypes into different categories, (6) reclassifying squamous cell carcinomas into keratinizing, nonkeratinizing, and basaloid subtypes with the nonkeratinizing tumors requiring immunohistochemistry proof of squamous differentiation, (7) grouping of neuroendocrine tumors together in one category, (8) adding NUT carcinoma, (9) changing the term sclerosing hemangioma to sclerosing pneumocytoma, (10) changing the name hamartoma to "pulmonary hamartoma," (11) creating a group of PEComatous tumors that include (a) lymphangioleiomyomatosis, (b) PEComa, benign (with clear cell tumor as a variant) and (c) PEComa, malignant, (12) introducing the entity pulmonary myxoid sarcoma with an EWSR1-CREB1 translocation, (13) adding the entities myoepithelioma and myoepithelial carcinomas, which can show EWSR1 gene rearrangements, (14) recognition of usefulness of WWTR1-CAMTA1 fusions in diagnosis of epithelioid hemangioendotheliomas, (15) adding Erdheim-Chester disease to the lymphoproliferative tumor, and (16) a group of tumors of ectopic origin to include germ cell tumors, intrapulmonary thymoma, melanoma and meningioma.

Department of Defense Data Model, Version 1, Fy 1998, Volume 6.

DTIC Science & Technology

1998-05-31

Definition: A REQUIREMENT TO WITHHOLD PAYMENT ON A SPECIFIC CONTRACT. (5104) (1) (A) 138 Entity Report DOD Data Model VI FY98 Attribute Names...424 Entity Report DOD Data Model VI FY98 Entity Name: PAYMENT -MEANS-FINANCIAL-INSTITUTION-ACCOUNT Definition: THE ASSOCIATION OF A FINANCIAL...A) 453 Entity Report DOD Data Model VI FY98 Definition: PETITION FOR PAYMENT PRIOR TO PERFORMANCE BY A PERSONNEL-RESOURCE. Attribute Names

10 CFR 300.3 - Guidance for defining and naming the reporting entity.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 10 Energy 3 2013-01-01 2013-01-01 false Guidance for defining and naming the reporting entity. 300.3 Section 300.3 Energy DEPARTMENT OF ENERGY CLIMATE CHANGE VOLUNTARY GREENHOUSE GAS REPORTING PROGRAM: GENERAL GUIDELINES § 300.3 Guidance for defining and naming the reporting entity. (a) A reporting...

10 CFR 300.3 - Guidance for defining and naming the reporting entity.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 10 Energy 3 2012-01-01 2012-01-01 false Guidance for defining and naming the reporting entity. 300.3 Section 300.3 Energy DEPARTMENT OF ENERGY CLIMATE CHANGE VOLUNTARY GREENHOUSE GAS REPORTING PROGRAM: GENERAL GUIDELINES § 300.3 Guidance for defining and naming the reporting entity. (a) A reporting...

10 CFR 300.3 - Guidance for defining and naming the reporting entity.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 10 Energy 3 2011-01-01 2011-01-01 false Guidance for defining and naming the reporting entity. 300.3 Section 300.3 Energy DEPARTMENT OF ENERGY CLIMATE CHANGE VOLUNTARY GREENHOUSE GAS REPORTING PROGRAM: GENERAL GUIDELINES § 300.3 Guidance for defining and naming the reporting entity. (a) A reporting...

10 CFR 300.3 - Guidance for defining and naming the reporting entity.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 10 Energy 3 2014-01-01 2014-01-01 false Guidance for defining and naming the reporting entity. 300.3 Section 300.3 Energy DEPARTMENT OF ENERGY CLIMATE CHANGE VOLUNTARY GREENHOUSE GAS REPORTING PROGRAM: GENERAL GUIDELINES § 300.3 Guidance for defining and naming the reporting entity. (a) A reporting...

10 CFR 300.3 - Guidance for defining and naming the reporting entity.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 10 Energy 3 2010-01-01 2010-01-01 false Guidance for defining and naming the reporting entity. 300.3 Section 300.3 Energy DEPARTMENT OF ENERGY CLIMATE CHANGE VOLUNTARY GREENHOUSE GAS REPORTING PROGRAM: GENERAL GUIDELINES § 300.3 Guidance for defining and naming the reporting entity. (a) A reporting...

Detecting experimental techniques and selecting relevant documents for protein-protein interactions from biomedical literature

PubMed Central

2011-01-01

Background The selection of relevant articles for curation, and linking those articles to experimental techniques confirming the findings became one of the primary subjects of the recent BioCreative III contest. The contest’s Protein-Protein Interaction (PPI) task consisted of two sub-tasks: Article Classification Task (ACT) and Interaction Method Task (IMT). ACT aimed to automatically select relevant documents for PPI curation, whereas the goal of IMT was to recognise the methods used in experiments for identifying the interactions in full-text articles. Results We proposed and compared several classification-based methods for both tasks, employing rich contextual features as well as features extracted from external knowledge sources. For IMT, a new method that classifies pair-wise relations between every text phrase and candidate interaction method obtained promising results with an F1 score of 64.49%, as tested on the task’s development dataset. We also explored ways to combine this new approach and more conventional, multi-label document classification methods. For ACT, our classifiers exploited automatically detected named entities and other linguistic information. The evaluation results on the BioCreative III PPI test datasets showed that our systems were very competitive: one of our IMT methods yielded the best performance among all participants, as measured by F1 score, Matthew’s Correlation Coefficient and AUC iP/R; whereas for ACT, our best classifier was ranked second as measured by AUC iP/R, and also competitive according to other metrics. Conclusions Our novel approach that converts the multi-class, multi-label classification problem to a binary classification problem showed much promise in IMT. Nevertheless, on the test dataset the best performance was achieved by taking the union of the output of this method and that of a multi-class, multi-label document classifier, which indicates that the two types of systems complement each other in terms of recall. For ACT, our system exploited a rich set of features and also obtained encouraging results. We examined the features with respect to their contributions to the classification results, and concluded that contextual words surrounding named entities, as well as the MeSH headings associated with the documents were among the main contributors to the performance. PMID:22151769

77 FR 61658 - Designation of Two Entities Pursuant to Executive Orders

Federal Register 2010, 2011, 2012, 2013, 2014

2012-10-10

... DEPARTMENT OF THE TREASURY Office of Foreign Assets Control Designation of Two Entities Pursuant... Treasury Department's Office of Foreign Assets Control (``OFAC'') is publishing the names of two entities....'' DATES: The designation by the Director of OFAC of the two entities named in this notice, pursuant to...

Complex posttraumatic stress disorder: The need to consolidate a distinct clinical syndrome or to reevaluate features of psychiatric disorders following interpersonal trauma?

PubMed

Giourou, Evangelia; Skokou, Maria; Andrew, Stuart P; Alexopoulou, Konstantina; Gourzis, Philippos; Jelastopulu, Eleni

2018-03-22

Complex posttraumatic stress disorder (Complex PTSD) has been recently proposed as a distinct clinical entity in the WHO International Classification of Diseases, 11 th version, due to be published, two decades after its first initiation. It is described as an enhanced version of the current definition of PTSD, with clinical features of PTSD plus three additional clusters of symptoms namely emotional dysregulation, negative self-cognitions and interpersonal hardship, thus resembling the clinical features commonly encountered in borderline personality disorder (BPD). Complex PTSD is related to complex trauma which is defined by its threatening and entrapping context, generally interpersonal in nature. In this manuscript, we review the current findings related to traumatic events predisposing the above-mentioned disorders as well as the biological correlates surrounding them, along with their clinical features. Furthermore, we suggest that besides the present distinct clinical diagnoses (PTSD; Complex PTSD; BPD), there is a cluster of these comorbid disorders, that follow a continuum of trauma and biological severity on a spectrum of common or similar clinical features and should be treated as such. More studies are needed to confirm or reject this hypothesis, particularly in clinical terms and how they correlate to clinical entities' biological background, endorsing a shift from the phenomenologically only classification of psychiatric disorders towards a more biologically validated classification.

Motivation and Organizational Principles for Anatomical Knowledge Representation

PubMed Central

Rosse, Cornelius; Mejino, José L.; Modayur, Bharath R.; Jakobovits, Rex; Hinshaw, Kevin P.; Brinkley, James F.

1998-01-01

Abstract Objective: Conceptualization of the physical objects and spaces that constitute the human body at the macroscopic level of organization, specified as a machine-parseable ontology that, in its human-readable form, is comprehensible to both expert and novice users of anatomical information. Design: Conceived as an anatomical enhancement of the UMLS Semantic Network and Metathesaurus, the anatomical ontology was formulated by specifying defining attributes and differentia for classes and subclasses of physical anatomical entities based on their partitive and spatial relationships. The validity of the classification was assessed by instantiating the ontology for the thorax. Several transitive relationships were used for symbolically modeling aspects of the physical organization of the thorax. Results: By declaring Organ as the macroscopic organizational unit of the body, and defining the entities that constitute organs and higher level entities constituted by organs, all anatomical entities could be assigned to one of three top level classes (Anatomical structure, Anatomical spatial entity and Body substance). The ontology accommodates both the systemic and regional (topographical) views of anatomy, as well as diverse clinical naming conventions of anatomical entities. Conclusions: The ontology formulated for the thorax is extendible to microscopic and cellular levels, as well as to other body parts, in that its classes subsume essentially all anatomical entities that constitute the body. Explicit definitions of these entities and their relationships provide the first requirement for standards in anatomical concept representation. Conceived from an anatomical viewpoint, the ontology can be generalized and mapped to other biomedical domains and problem solving tasks that require anatomical knowledge. PMID:9452983

Noun and knowledge retrieval for biological and non-biological entities following right occipitotemporal lesions.

PubMed

Bruffaerts, Rose; De Weer, An-Sofie; De Grauwe, Sophie; Thys, Miek; Dries, Eva; Thijs, Vincent; Sunaert, Stefan; Vandenbulcke, Mathieu; De Deyne, Simon; Storms, Gerrit; Vandenberghe, Rik

2014-09-01

We investigated the critical contribution of right ventral occipitotemporal cortex to knowledge of visual and functional-associative attributes of biological and non-biological entities and how this relates to category-specificity during confrontation naming. In a consecutive series of 7 patients with lesions confined to right ventral occipitotemporal cortex, we conducted an extensive assessment of oral generation of visual-sensory and functional-associative features in response to the names of biological and nonbiological entities. Subjects also performed a confrontation naming task for these categories. Our main novel finding related to a unique case with a small lesion confined to right medial fusiform gyrus who showed disproportionate naming impairment for nonbiological versus biological entities, specifically for tools. Generation of visual and functional-associative features was preserved for biological and non-biological entities. In two other cases, who had a relatively small posterior lesion restricted to primary visual and posterior fusiform cortex, retrieval of visual attributes was disproportionately impaired compared to functional-associative attributes, in particular for biological entities. However, these cases did not show a category-specific naming deficit. Two final cases with the largest lesions showed a classical dissociation between biological versus nonbiological entities during naming, with normal feature generation performance. This is the first lesion-based evidence of a critical contribution of the right medial fusiform cortex to tool naming. Second, dissociations along the dimension of attribute type during feature generation do not co-occur with category-specificity during naming in the current patient sample. Copyright © 2014 Elsevier Ltd. All rights reserved.

Context and Domain Knowledge Enhanced Entity Spotting in Informal Text

NASA Astrophysics Data System (ADS)

Gruhl, Daniel; Nagarajan, Meena; Pieper, Jan; Robson, Christine; Sheth, Amit

This paper explores the application of restricted relationship graphs (RDF) and statistical NLP techniques to improve named entity annotation in challenging Informal English domains. We validate our approach using on-line forums discussing popular music. Named entity annotation is particularly difficult in this domain because it is characterized by a large number of ambiguous entities, such as the Madonna album "Music" or Lilly Allen's pop hit "Smile".

12 CFR 1010.208 - General information.

Code of Federal Regulations, 2012 CFR

2012-01-01

... owner or developer are corporate entities, name the parent and/or corporate entity and state the... registration or prohibited sales, name the state involved and give the reasons cited by the state for their... made with the SEC, give the SEC identification number; identify the prospectus by name; date of filing...

12 CFR 1010.208 - General information.

Code of Federal Regulations, 2013 CFR

2013-01-01

... owner or developer are corporate entities, name the parent and/or corporate entity and state the... registration or prohibited sales, name the state involved and give the reasons cited by the state for their... made with the SEC, give the SEC identification number; identify the prospectus by name; date of filing...

2 CFR 170.110 - Types of entities to which this part applies.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 2 Grants and Agreements 1 2014-01-01 2014-01-01 false Types of entities to which this part applies... or receive agency awards; or (2) Receive subawards under those awards. (b) Exceptions. (1) None of... her name). (2) None of the requirements regarding reporting names and total compensation of an entity...

2 CFR 170.110 - Types of entities to which this part applies.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 2 Grants and Agreements 1 2011-01-01 2011-01-01 false Types of entities to which this part applies... or receive agency awards; or (2) Receive subawards under those awards. (b) Exceptions. (1) None of... her name). (2) None of the requirements regarding reporting names and total compensation of an entity...

InterLymph hierarchical classification of lymphoid neoplasms for epidemiologic research based on the WHO classification (2008): update and future directions

PubMed Central

Morton, Lindsay M.; Linet, Martha S.; Clarke, Christina A.; Kadin, Marshall E.; Vajdic, Claire M.; Monnereau, Alain; Maynadié, Marc; Chiu, Brian C.-H.; Marcos-Gragera, Rafael; Costantini, Adele Seniori; Cerhan, James R.; Weisenburger, Dennis D.

2010-01-01

After publication of the updated World Health Organization (WHO) classification of tumors of hematopoietic and lymphoid tissues in 2008, the Pathology Working Group of the International Lymphoma Epidemiology Consortium (InterLymph) now presents an update of the hierarchical classification of lymphoid neoplasms for epidemiologic research based on the 2001 WHO classification, which we published in 2007. The updated hierarchical classification incorporates all of the major and provisional entities in the 2008 WHO classification, including newly defined entities based on age, site, certain infections, and molecular characteristics, as well as borderline categories, early and “in situ” lesions, disorders with limited capacity for clinical progression, lesions without current International Classification of Diseases for Oncology, 3rd Edition codes, and immunodeficiency-associated lymphoproliferative disorders. WHO subtypes are defined in hierarchical groupings, with newly defined groups for small B-cell lymphomas with plasmacytic differentiation and for primary cutaneous T-cell lymphomas. We suggest approaches for applying the hierarchical classification in various epidemiologic settings, including strategies for dealing with multiple coexisting lymphoma subtypes in one patient, and cases with incomplete pathologic information. The pathology materials useful for state-of-the-art epidemiology studies are also discussed. We encourage epidemiologists to adopt the updated InterLymph hierarchical classification, which incorporates the most recent WHO entities while demonstrating their relationship to older classifications. PMID:20699439

InterLymph hierarchical classification of lymphoid neoplasms for epidemiologic research based on the WHO classification (2008): update and future directions.

PubMed

Turner, Jennifer J; Morton, Lindsay M; Linet, Martha S; Clarke, Christina A; Kadin, Marshall E; Vajdic, Claire M; Monnereau, Alain; Maynadié, Marc; Chiu, Brian C-H; Marcos-Gragera, Rafael; Costantini, Adele Seniori; Cerhan, James R; Weisenburger, Dennis D

2010-11-18

After publication of the updated World Health Organization (WHO) classification of tumors of hematopoietic and lymphoid tissues in 2008, the Pathology Working Group of the International Lymphoma Epidemiology Consortium (InterLymph) now presents an update of the hierarchical classification of lymphoid neoplasms for epidemiologic research based on the 2001 WHO classification, which we published in 2007. The updated hierarchical classification incorporates all of the major and provisional entities in the 2008 WHO classification, including newly defined entities based on age, site, certain infections, and molecular characteristics, as well as borderline categories, early and "in situ" lesions, disorders with limited capacity for clinical progression, lesions without current International Classification of Diseases for Oncology, 3rd Edition codes, and immunodeficiency-associated lymphoproliferative disorders. WHO subtypes are defined in hierarchical groupings, with newly defined groups for small B-cell lymphomas with plasmacytic differentiation and for primary cutaneous T-cell lymphomas. We suggest approaches for applying the hierarchical classification in various epidemiologic settings, including strategies for dealing with multiple coexisting lymphoma subtypes in one patient, and cases with incomplete pathologic information. The pathology materials useful for state-of-the-art epidemiology studies are also discussed. We encourage epidemiologists to adopt the updated InterLymph hierarchical classification, which incorporates the most recent WHO entities while demonstrating their relationship to older classifications.

26 CFR 301.7701-3 - Classification of certain business entities.

Code of Federal Regulations, 2013 CFR

2013-04-01

... the new target corporation under section 338. (iii) Application to successive elections in tiered... of an entity does not result in the creation of a new entity for purposes of the sixty month... entity separate from A when A becomes the only member of X. X, however, is not treated as a new entity...

26 CFR 301.7701-3 - Classification of certain business entities.

Code of Federal Regulations, 2012 CFR

2012-04-01

... the new target corporation under section 338. (iii) Application to successive elections in tiered... of an entity does not result in the creation of a new entity for purposes of the sixty month... entity separate from A when A becomes the only member of X. X, however, is not treated as a new entity...

26 CFR 301.7701-3 - Classification of certain business entities.

Code of Federal Regulations, 2011 CFR

2011-04-01

... the new target corporation under section 338. (iii) Application to successive elections in tiered... of an entity does not result in the creation of a new entity for purposes of the sixty month... entity separate from A when A becomes the only member of X. X, however, is not treated as a new entity...

26 CFR 301.7701-3 - Classification of certain business entities.

Code of Federal Regulations, 2014 CFR

2014-04-01

... the new target corporation under section 338. (iii) Application to successive elections in tiered... of an entity does not result in the creation of a new entity for purposes of the sixty month... entity separate from A when A becomes the only member of X. X, however, is not treated as a new entity...

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.

Feature generation and representations for protein-protein interaction classification.

PubMed

Lan, Man; Tan, Chew Lim; Su, Jian

2009-10-01

Automatic detecting protein-protein interaction (PPI) relevant articles is a crucial step for large-scale biological database curation. The previous work adopted POS tagging, shallow parsing and sentence splitting techniques, but they achieved worse performance than the simple bag-of-words representation. In this paper, we generated and investigated multiple types of feature representations in order to further improve the performance of PPI text classification task. Besides the traditional domain-independent bag-of-words approach and the term weighting methods, we also explored other domain-dependent features, i.e. protein-protein interaction trigger keywords, protein named entities and the advanced ways of incorporating Natural Language Processing (NLP) output. The integration of these multiple features has been evaluated on the BioCreAtIvE II corpus. The experimental results showed that both the advanced way of using NLP output and the integration of bag-of-words and NLP output improved the performance of text classification. Specifically, in comparison with the best performance achieved in the BioCreAtIvE II IAS, the feature-level and classifier-level integration of multiple features improved the performance of classification 2.71% and 3.95%, respectively.

17 CFR 229.1107 - (Item 1107) Issuing entities.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 17 Commodity and Securities Exchanges 2 2011-04-01 2011-04-01 false (Item 1107) Issuing entities....1107 (Item 1107) Issuing entities. Provide the following information about the issuing entity: (a) State the issuing entity's name and describe the issuing entity's form of organization, including the...

17 CFR 229.1107 - (Item 1107) Issuing entities.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 17 Commodity and Securities Exchanges 2 2010-04-01 2010-04-01 false (Item 1107) Issuing entities....1107 (Item 1107) Issuing entities. Provide the following information about the issuing entity: (a) State the issuing entity's name and describe the issuing entity's form of organization, including the...

Medical Named Entity Recognition for Indonesian Language Using Word Representations

NASA Astrophysics Data System (ADS)

Rahman, Arief

2018-03-01

Nowadays, Named Entity Recognition (NER) system is used in medical texts to obtain important medical information, like diseases, symptoms, and drugs. While most NER systems are applied to formal medical texts, informal ones like those from social media (also called semi-formal texts) are starting to get recognition as a gold mine for medical information. We propose a theoretical Named Entity Recognition (NER) model for semi-formal medical texts in our medical knowledge management system by comparing two kinds of word representations: cluster-based word representation and distributed representation.

The 2016 revision of the World Health Organization classification of lymphoid neoplasms | Center for Cancer Research

Cancer.gov

A revision of the nearly 8-year-old World Health Organization classification of the lymphoid neoplasms and the accompanying monograph is being published. It reflects a consensus among hematopathologists, geneticists, and clinicians regarding both updates to current entities as well as the addition of a limited number of new provisional entities.

A method for named entity normalization in biomedical articles: application to diseases and plants.

PubMed

Cho, Hyejin; Choi, Wonjun; Lee, Hyunju

2017-10-13

In biomedical articles, a named entity recognition (NER) technique that identifies entity names from texts is an important element for extracting biological knowledge from articles. After NER is applied to articles, the next step is to normalize the identified names into standard concepts (i.e., disease names are mapped to the National Library of Medicine's Medical Subject Headings disease terms). In biomedical articles, many entity normalization methods rely on domain-specific dictionaries for resolving synonyms and abbreviations. However, the dictionaries are not comprehensive except for some entities such as genes. In recent years, biomedical articles have accumulated rapidly, and neural network-based algorithms that incorporate a large amount of unlabeled data have shown considerable success in several natural language processing problems. In this study, we propose an approach for normalizing biological entities, such as disease names and plant names, by using word embeddings to represent semantic spaces. For diseases, training data from the National Center for Biotechnology Information (NCBI) disease corpus and unlabeled data from PubMed abstracts were used to construct word representations. For plants, a training corpus that we manually constructed and unlabeled PubMed abstracts were used to represent word vectors. We showed that the proposed approach performed better than the use of only the training corpus or only the unlabeled data and showed that the normalization accuracy was improved by using our model even when the dictionaries were not comprehensive. We obtained F-scores of 0.808 and 0.690 for normalizing the NCBI disease corpus and manually constructed plant corpus, respectively. We further evaluated our approach using a data set in the disease normalization task of the BioCreative V challenge. When only the disease corpus was used as a dictionary, our approach significantly outperformed the best system of the task. The proposed approach shows robust performance for normalizing biological entities. The manually constructed plant corpus and the proposed model are available at http://gcancer.org/plant and http://gcancer.org/normalization , respectively.

Identifying non-elliptical entity mentions in a coordinated NP with ellipses.

PubMed

Chae, Jeongmin; Jung, Younghee; Lee, Taemin; Jung, Soonyoung; Huh, Chan; Kim, Gilhan; Kim, Hyeoncheol; Oh, Heungbum

2014-02-01

Named entities in the biomedical domain are often written using a Noun Phrase (NP) along with a coordinating conjunction such as 'and' and 'or'. In addition, repeated words among named entity mentions are frequently omitted. It is often difficult to identify named entities. Although various Named Entity Recognition (NER) methods have tried to solve this problem, these methods can only deal with relatively simple elliptical patterns in coordinated NPs. We propose a new NER method for identifying non-elliptical entity mentions with simple or complex ellipses using linguistic rules and an entity mention dictionary. The GENIA and CRAFT corpora were used to evaluate the performance of the proposed system. The GENIA corpus was used to evaluate the performance of the system according to the quality of the dictionary. The GENIA corpus comprises 3434 non-elliptical entity mentions in 1585 coordinated NPs with ellipses. The system achieves 92.11% precision, 95.20% recall, and 93.63% F-score in identification of non-elliptical entity mentions in coordinated NPs. The accuracy of the system in resolving simple and complex ellipses is 94.54% and 91.95%, respectively. The CRAFT corpus was used to evaluate the performance of the system under realistic conditions. The system achieved 78.47% precision, 67.10% recall, and 72.34% F-score in coordinated NPs. The performance evaluations of the system show that it efficiently solves the problem caused by ellipses, and improves NER performance. The algorithm is implemented in PHP and the code can be downloaded from https://code.google.com/p/medtextmining/. Copyright © 2013. Published by Elsevier Inc.

Acute bacterial skin and skin structure infections in internal medicine wards: old and new drugs.

PubMed

Falcone, Marco; Concia, Ercole; Giusti, Massimo; Mazzone, Antonino; Santini, Claudio; Stefani, Stefania; Violi, Francesco

2016-08-01

Skin and soft tissue infections (SSTIs) are a common cause of hospital admission among elderly patients, and traditionally have been divided into complicated and uncomplicated SSTIs. In 2010, the FDA provided a new classification of these infections, and a new category of disease, named acute bacterial skin and skin structure infections (ABSSSIs), has been proposed as an independent clinical entity. ABSSSIs include three entities: cellulitis and erysipelas, wound infections, and major cutaneous abscesses This paper revises the epidemiology of SSTIs and ABSSSIs with regard to etiologies, diagnostic techniques, and clinical presentation in the hospital settings. Particular attention is owed to frail patients with multiple comorbidities and underlying significant disease states, hospitalized on internal medicine wards or residing in nursing homes, who appear to be at increased risk of infection due to multi-drug resistant pathogens and treatment failures. Management of ABSSSIs and SSTIs, including evaluation of the hemodynamic state, surgical intervention and treatment with appropriate antibiotic therapy are extensively discussed.

Cross domains Arabic named entity recognition system

NASA Astrophysics Data System (ADS)

Al-Ahmari, S. Saad; Abdullatif Al-Johar, B.

2016-07-01

Named Entity Recognition (NER) plays an important role in many Natural Language Processing (NLP) applications such as; Information Extraction (IE), Question Answering (QA), Text Clustering, Text Summarization and Word Sense Disambiguation. This paper presents the development and implementation of domain independent system to recognize three types of Arabic named entities. The system works based on a set of domain independent grammar-rules along with Arabic part of speech tagger in addition to gazetteers and lists of trigger words. The experimental results shown, that the system performed as good as other systems with better results in some cases of cross-domains corpora.

CheNER: a tool for the identification of chemical entities and their classes in biomedical literature.

PubMed

Usié, Anabel; Cruz, Joaquim; Comas, Jorge; Solsona, Francesc; Alves, Rui

2015-01-01

Small chemical molecules regulate biological processes at the molecular level. Those molecules are often involved in causing or treating pathological states. Automatically identifying such molecules in biomedical text is difficult due to both, the diverse morphology of chemical names and the alternative types of nomenclature that are simultaneously used to describe them. To address these issues, the last BioCreAtIvE challenge proposed a CHEMDNER task, which is a Named Entity Recognition (NER) challenge that aims at labelling different types of chemical names in biomedical text. To address this challenge we tested various approaches to recognizing chemical entities in biomedical documents. These approaches range from linear Conditional Random Fields (CRFs) to a combination of CRFs with regular expression and dictionary matching, followed by a post-processing step to tag those chemical names in a corpus of Medline abstracts. We named our best performing systems CheNER. We evaluate the performance of the various approaches using the F-score statistics. Higher F-scores indicate better performance. The highest F-score we obtain in identifying unique chemical entities is 72.88%. The highest F-score we obtain in identifying all chemical entities is 73.07%. We also evaluate the F-Score of combining our system with ChemSpot, and find an increase from 72.88% to 73.83%. CheNER presents a valid alternative for automated annotation of chemical entities in biomedical documents. In addition, CheNER may be used to derive new features to train newer methods for tagging chemical entities. CheNER can be downloaded from http://metres.udl.cat and included in text annotation pipelines.

Cystic renal tumors: new entities and novel concepts.

PubMed

Moch, Holger

2010-05-01

Cystic renal neoplasms and renal epithelial stromal tumors are diagnostically challenging and represent some novel tumor entities. In this article, clinical and pathologic features of established and novel entities are discussed. Predominantly cystic renal tumors include cystic nephroma/mixed epithelial and stromal tumor, synovial sarcoma, and multilocular cystic renal cell carcinoma. These entities are own tumor entities of the 2004 WHO classification of renal tumors. Tubulocystic carcinoma and acquired cystic disease-associated renal cell carcinoma are neoplasms with an intrinsically cystic growth pattern. Both tumor types should be included in a future WHO classification as novel entities owing to their characteristic features. Cysts and clear cell renal cell carcinoma frequently coexist within the kidneys of patients with von Hippel-Lindau disease. Sporadic clear cell renal cell carcinomas often contain cysts, usually as a minor component. Some clear cell renal cell carcinomas have prominent cysts, and multilocular cystic renal cell carcinoma is composed almost exclusively of cysts. Recent molecular findings suggest that clear cell renal cancer may develop through cyst-dependent and cyst-independent molecular pathways.

Character-level neural network for biomedical named entity recognition.

PubMed

Gridach, Mourad

2017-06-01

Biomedical named entity recognition (BNER), which extracts important named entities such as genes and proteins, is a challenging task in automated systems that mine knowledge in biomedical texts. The previous state-of-the-art systems required large amounts of task-specific knowledge in the form of feature engineering, lexicons and data pre-processing to achieve high performance. In this paper, we introduce a novel neural network architecture that benefits from both word- and character-level representations automatically, by using a combination of bidirectional long short-term memory (LSTM) and conditional random field (CRF) eliminating the need for most feature engineering tasks. We evaluate our system on two datasets: JNLPBA corpus and the BioCreAtIvE II Gene Mention (GM) corpus. We obtained state-of-the-art performance by outperforming the previous systems. To the best of our knowledge, we are the first to investigate the combination of deep neural networks, CRF, word embeddings and character-level representation in recognizing biomedical named entities. Copyright © 2017 Elsevier Inc. All rights reserved.

Active learning for ontological event extraction incorporating named entity recognition and unknown word handling.

PubMed

Han, Xu; Kim, Jung-jae; Kwoh, Chee Keong

2016-01-01

Biomedical text mining may target various kinds of valuable information embedded in the literature, but a critical obstacle to the extension of the mining targets is the cost of manual construction of labeled data, which are required for state-of-the-art supervised learning systems. Active learning is to choose the most informative documents for the supervised learning in order to reduce the amount of required manual annotations. Previous works of active learning, however, focused on the tasks of entity recognition and protein-protein interactions, but not on event extraction tasks for multiple event types. They also did not consider the evidence of event participants, which might be a clue for the presence of events in unlabeled documents. Moreover, the confidence scores of events produced by event extraction systems are not reliable for ranking documents in terms of informativity for supervised learning. We here propose a novel committee-based active learning method that supports multi-event extraction tasks and employs a new statistical method for informativity estimation instead of using the confidence scores from event extraction systems. Our method is based on a committee of two systems as follows: We first employ an event extraction system to filter potential false negatives among unlabeled documents, from which the system does not extract any event. We then develop a statistical method to rank the potential false negatives of unlabeled documents 1) by using a language model that measures the probabilities of the expression of multiple events in documents and 2) by using a named entity recognition system that locates the named entities that can be event arguments (e.g. proteins). The proposed method further deals with unknown words in test data by using word similarity measures. We also apply our active learning method for the task of named entity recognition. We evaluate the proposed method against the BioNLP Shared Tasks datasets, and show that our method can achieve better performance than such previous methods as entropy and Gibbs error based methods and a conventional committee-based method. We also show that the incorporation of named entity recognition into the active learning for event extraction and the unknown word handling further improve the active learning method. In addition, the adaptation of the active learning method into named entity recognition tasks also improves the document selection for manual annotation of named entities.

Chemical named entities recognition: a review on approaches and applications

PubMed Central

2014-01-01

The rapid increase in the flow rate of published digital information in all disciplines has resulted in a pressing need for techniques that can simplify the use of this information. The chemistry literature is very rich with information about chemical entities. Extracting molecules and their related properties and activities from the scientific literature to “text mine” these extracted data and determine contextual relationships helps research scientists, particularly those in drug development. One of the most important challenges in chemical text mining is the recognition of chemical entities mentioned in the texts. In this review, the authors briefly introduce the fundamental concepts of chemical literature mining, the textual contents of chemical documents, and the methods of naming chemicals in documents. We sketch out dictionary-based, rule-based and machine learning, as well as hybrid chemical named entity recognition approaches with their applied solutions. We end with an outlook on the pros and cons of these approaches and the types of chemical entities extracted. PMID:24834132

Chemical named entities recognition: a review on approaches and applications.

PubMed

Eltyeb, Safaa; Salim, Naomie

2014-01-01

The rapid increase in the flow rate of published digital information in all disciplines has resulted in a pressing need for techniques that can simplify the use of this information. The chemistry literature is very rich with information about chemical entities. Extracting molecules and their related properties and activities from the scientific literature to "text mine" these extracted data and determine contextual relationships helps research scientists, particularly those in drug development. One of the most important challenges in chemical text mining is the recognition of chemical entities mentioned in the texts. In this review, the authors briefly introduce the fundamental concepts of chemical literature mining, the textual contents of chemical documents, and the methods of naming chemicals in documents. We sketch out dictionary-based, rule-based and machine learning, as well as hybrid chemical named entity recognition approaches with their applied solutions. We end with an outlook on the pros and cons of these approaches and the types of chemical entities extracted.

76 FR 28503 - Identification of Three Entities as Government of Libya Entities Pursuant to Executive Order 13566

Federal Register 2010, 2011, 2012, 2013, 2014

2011-05-17

... DEPARTMENT OF THE TREASURY Office of Foreign Assets Control Identification of Three Entities as Government of Libya Entities Pursuant to Executive Order 13566 AGENCY: Department of the Treasury. ACTION... names of three entities identified on May 5, 2011 as persons whose property and interests in property...

University of Glasgow at TREC 2009: Experiments with Terrier

DTIC Science & Technology

2009-11-01

identify entities in the category B subset of the corpus, we resort to an efficient dictionary -based named en- tity recognition approach.4 In particular...we build a large dictio- nary of entity names using DBPedia,5 a structured representation of Wikipedia. Dictionary entries comprise all known...aliases for each unique entity, as obtained from DBPedia (e.g., ‘Barack Obama’ is represented by the dictionary entries ‘Barack Obama’ and ‘44th President

14 CFR 1203.701 - Classification.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 14 Aeronautics and Space 5 2013-01-01 2013-01-01 false Classification. 1203.701 Section 1203.701... Government Information § 1203.701 Classification. (a) Foreign government information that is classified by a foreign entity shall either retain its original classification designation or be marked with a United...

14 CFR 1203.701 - Classification.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 14 Aeronautics and Space 5 2012-01-01 2012-01-01 false Classification. 1203.701 Section 1203.701... Government Information § 1203.701 Classification. (a) Foreign government information that is classified by a foreign entity shall either retain its original classification designation or be marked with a United...

14 CFR 1203.701 - Classification.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 14 Aeronautics and Space 5 2011-01-01 2010-01-01 true Classification. 1203.701 Section 1203.701... Government Information § 1203.701 Classification. (a) Foreign government information that is classified by a foreign entity shall either retain its original classification designation or be marked with a United...

50 CFR 679.81 - Rockfish Program annual harvester and processor privileges.

Code of Federal Regulations, 2010 CFR

2010-10-01

... legal name; the type of business entity under which the rockfish cooperative is organized; the state in which the rockfish cooperative is legally registered as a business entity; Tax ID number, date of incorporation, the printed name of the rockfish cooperative's designated representative; the permanent business...

The left temporal pole is a heteromodal hub for retrieving proper names

PubMed Central

Waldron, Eric J.; Manzel, Kenneth; Tranel, Daniel

2015-01-01

The left temporal pole (LTP) has been posited to be a heteromodal hub for retrieving proper names for semantically unique entities. Previous investigations have demonstrated that LTP is important for retrieving names for famous faces and unique landmarks. However, whether such a relationship would hold for unique entities apprehended through stimulus modalities other than vision has not been well established, and such evidence is critical to adjudicate claims about the “heteromodal” nature of the LTP. Here, we tested the hypothesis that the LTP would be important for naming famous voices. Individuals with LTP lesions were asked to recognize and name famous persons speaking in audio clips. Relative to neurologically normal and brain damaged comparison participants, patients with LTP lesions were able to recognize famous persons from their voices normally, but were selectively impaired in naming famous persons from their voices. The current results extend previous research and provide further support for the notion that the LTP is a convergence region serving as a heteromodal hub for retrieving the names of semantically unique entities. PMID:24389260

Current Nomenclature of Pseudohypoparathyroidism: Inactivating Parathyroid Hormone/Parathyroid Hormone-Related Protein Signaling Disorder

PubMed Central

Turan, Serap

2017-01-01

Disorders related to parathyroid hormone (PTH) resistance and PTH signaling pathway impairment are historically classified under the term of pseudohypoparathyroidism (PHP). The disease was first described and named by Fuller Albright and colleagues in 1942. Albright hereditary osteodystrophy (AHO) is described as an associated clinical entity with PHP, characterized by brachydactyly, subcutaneous ossifications, round face, short stature and a stocky build. The classification of PHP is further divided into PHP-Ia, pseudo-PHP (pPHP), PHP-Ib, PHP-Ic and PHP-II according to the presence or absence of AHO, together with an in vivo response to exogenous PTH and the measurement of Gsα protein activity in peripheral erythrocyte membranes in vitro. However, PHP classification fails to differentiate all patients with different clinical and molecular findings for PHP subtypes and classification become more complicated with more recent molecular characterization and new forms having been identified. So far, new classifications have been established by the EuroPHP network to cover all disorders of the PTH receptor and its signaling pathway. Inactivating PTH/PTH-related protein signaling disorder (iPPSD) is the new name proposed for a group of these disorders and which can be further divided into subtypes - iPPSD1 to iPPSD6. These are termed, starting from PTH receptor inactivation mutation (Eiken and Blomstrand dysplasia) as iPPSD1, inactivating Gsα mutations (PHP-Ia, PHP-Ic and pPHP) as iPPSD2, loss of methylation of GNAS DMRs (PHP-Ib) as iPPSD3, PRKAR1A mutations (acrodysostosis type 1) as iPPSD4, PDE4D mutations (acrodysostosis type 2) as iPPSD5 and PDE3A mutations (autosomal dominant hypertension with brachydactyly) as iPPSD6. iPPSDx is reserved for unknown molecular defects and iPPSDn+1 for new molecular defects which are yet to be described. With these new classifications, the aim is to clarify the borders of each different subtype of disease and make the classification according to molecular pathology. The iPPSD group is designed to be expandable and new classifications will readily fit into it as necessary. PMID:29280743

Current Nomenclature of Pseudohypoparathyroidism: Inactivating Parathyroid Hormone/Parathyroid Hormone-Related Protein Signaling Disorder.

PubMed

Turan, Serap

2017-12-30

Disorders related to parathyroid hormone (PTH) resistance and PTH signaling pathway impairment are historically classified under the term of pseudohypoparathyroidism (PHP). The disease was first described and named by Fuller Albright and colleagues in 1942. Albright hereditary osteodystrophy (AHO) is described as an associated clinical entity with PHP, characterized by brachydactyly, subcutaneous ossifications, round face, short stature and a stocky build. The classification of PHP is further divided into PHP-Ia, pseudo-PHP (pPHP), PHP-Ib, PHP-Ic and PHP-II according to the presence or absence of AHO, together with an in vivo response to exogenous PTH and the measurement of Gsα protein activity in peripheral erythrocyte membranes in vitro. However, PHP classification fails to differentiate all patients with different clinical and molecular findings for PHP subtypes and classification become more complicated with more recent molecular characterization and new forms having been identified. So far, new classifications have been established by the EuroPHP network to cover all disorders of the PTH receptor and its signaling pathway. Inactivating PTH/PTH-related protein signaling disorder (iPPSD) is the new name proposed for a group of these disorders and which can be further divided into subtypes - iPPSD1 to iPPSD6. These are termed, starting from PTH receptor inactivation mutation (Eiken and Blomstrand dysplasia) as iPPSD1, inactivating Gsα mutations (PHP-Ia, PHP-Ic and pPHP) as iPPSD2, loss of methylation of GNAS DMRs (PHP-Ib) as iPPSD3, PRKAR1A mutations (acrodysostosis type 1) as iPPSD4, PDE4D mutations (acrodysostosis type 2) as iPPSD5 and PDE3A mutations (autosomal dominant hypertension with brachydactyly) as iPPSD6. iPPSDx is reserved for unknown molecular defects and iPPSDn+1 for new molecular defects which are yet to be described. With these new classifications, the aim is to clarify the borders of each different subtype of disease and make the classification according to molecular pathology. The iPPSD group is designed to be expandable and new classifications will readily fit into it as necessary.

76 FR 52384 - Designation of Additional Entities Pursuant to Executive Order 13405

Federal Register 2010, 2011, 2012, 2013, 2014

2011-08-22

... DEPARTMENT OF THE TREASURY Office of Foreign Assets Control Designation of Additional Entities... Assets Control (``OFAC'') is publishing the names of four newly-designated entities whose property and... the Director of OFAC of the four entities identified in this notice, pursuant to Executive [[Page...

31 CFR 306.88 - Political entities and public corporations.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 31 Money and Finance:Treasury 2 2011-07-01 2011-07-01 false Political entities and public... entities and public corporations. Securities registered in the name of, or assigned to, a State, county, city, town, village, school district or other political entity, public body or corporation, may be...

31 CFR 306.88 - Political entities and public corporations.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 31 Money and Finance: Treasury 2 2010-07-01 2010-07-01 false Political entities and public... entities and public corporations. Securities registered in the name of, or assigned to, a State, county, city, town, village, school district or other political entity, public body or corporation, may be...

A System for Identifying Named Entities in Biomedical Text: how Results From two Evaluations Reflect on Both the System and the Evaluations

PubMed Central

Dingare, Shipra; Nissim, Malvina; Finkel, Jenny; Grover, Claire

2005-01-01

We present a maximum entropy-based system for identifying named entities (NEs) in biomedical abstracts and present its performance in the only two biomedical named entity recognition (NER) comparative evaluations that have been held to date, namely BioCreative and Coling BioNLP. Our system obtained an exact match F-score of 83.2% in the BioCreative evaluation and 70.1% in the BioNLP evaluation. We discuss our system in detail, including its rich use of local features, attention to correct boundary identification, innovative use of external knowledge resources, including parsing and web searches, and rapid adaptation to new NE sets. We also discuss in depth problems with data annotation in the evaluations which caused the final performance to be lower than optimal. PMID:18629295

A Novel Approach towards Medical Entity Recognition in Chinese Clinical Text

PubMed Central

Yu, Jian

2017-01-01

Medical entity recognition, a basic task in the language processing of clinical data, has been extensively studied in analyzing admission notes in alphabetic languages such as English. However, much less work has been done on nonstructural texts that are written in Chinese, or in the setting of differentiation of Chinese drug names between traditional Chinese medicine and Western medicine. Here, we propose a novel cascade-type Chinese medication entity recognition approach that aims at integrating the sentence category classifier from a support vector machine and the conditional random field-based medication entity recognition. We hypothesized that this approach could avoid the side effects of abundant negative samples and improve the performance of the named entity recognition from admission notes written in Chinese. Therefore, we applied this approach to a test set of 324 Chinese-written admission notes with manual annotation by medical experts. Our data demonstrated that this approach had a score of 94.2% in precision, 92.8% in recall, and 93.5% in F-measure for the recognition of traditional Chinese medicine drug names and 91.2% in precision, 92.6% in recall, and 91.7% F-measure for the recognition of Western medicine drug names. The differences in F-measure were significant compared with those in the baseline systems. PMID:29065612

Nom et lumière: enlightenment through nomenclature (the 1996 Kenneth F. Russell Memorial Lecture).

PubMed

Pearn, J

1997-08-01

The classification of living things is both an acknowledgement of biological relationships and an identification of their differences. When Linnaeus, in 1735, published Systema Naturae, he set in place a system of biological classification that saw its apogee in the invention of binomial nomenclature: the description of every living thing being embodied simply in two names, (i.e. a genus and the species within it). Linnaeus built on the work of scientific forebears, of whom Nehemiah Grew (1641-1712) was one of the most influential. Grew was a surgeon-physician whose passionate interest was plant anatomy; his work led to the discovery and documentation of sexual dimorphism in plants. Grew's life and works are a witness to that philosophy which views nature as a continuum, a broad holistic entity in which discoveries in one biological field have ramifications in other areas. Grew allowed his scientific curiosity full rein, manifested the courage to publish his work and possessed the self-discipline to stand by the audit of his peers. Modern biological research and contemporary clinical practice owes much to the enlightenment engendered by the classification and nomenclature that developed from his work.

Cloud Computing in Higher Education Sector for Sustainable Development

ERIC Educational Resources Information Center

Duan, Yuchao

2016-01-01

Cloud computing is considered a new frontier in the field of computing, as this technology comprises three major entities namely: software, hardware and network. The collective nature of all these entities is known as the Cloud. This research aims to examine the impacts of various aspects namely: cloud computing, sustainability, performance…

A transition-based joint model for disease named entity recognition and normalization.

PubMed

Lou, Yinxia; Zhang, Yue; Qian, Tao; Li, Fei; Xiong, Shufeng; Ji, Donghong

2017-08-01

Disease named entities play a central role in many areas of biomedical research, and automatic recognition and normalization of such entities have received increasing attention in biomedical research communities. Existing methods typically used pipeline models with two independent phases: (i) a disease named entity recognition (DER) system is used to find the boundaries of mentions in text and (ii) a disease named entity normalization (DEN) system is used to connect the mentions recognized to concepts in a controlled vocabulary. The main problems of such models are: (i) there is error propagation from DER to DEN and (ii) DEN is useful for DER, but pipeline models cannot utilize this. We propose a transition-based model to jointly perform disease named entity recognition and normalization, casting the output construction process into an incremental state transition process, learning sequences of transition actions globally, which correspond to joint structural outputs. Beam search and online structured learning are used, with learning being designed to guide search. Compared with the only existing method for joint DEN and DER, our method allows non-local features to be used, which significantly improves the accuracies. We evaluate our model on two corpora: the BioCreative V Chemical Disease Relation (CDR) corpus and the NCBI disease corpus. Experiments show that our joint framework achieves significantly higher performances compared to competitive pipeline baselines. Our method compares favourably to other state-of-the-art approaches. Data and code are available at https://github.com/louyinxia/jointRN. dhji@whu.edu.cn. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Prioritizing PubMed articles for the Comparative Toxicogenomic Database utilizing semantic information

PubMed Central

Wilbur, W. John

2012-01-01

The Comparative Toxicogenomics Database (CTD) contains manually curated literature that describes chemical–gene interactions, chemical–disease relationships and gene–disease relationships. Finding articles containing this information is the first and an important step to assist manual curation efficiency. However, the complex nature of named entities and their relationships make it challenging to choose relevant articles. In this article, we introduce a machine learning framework for prioritizing CTD-relevant articles based on our prior system for the protein–protein interaction article classification task in BioCreative III. To address new challenges in the CTD task, we explore a new entity identification method for genes, chemicals and diseases. In addition, latent topics are analyzed and used as a feature type to overcome the small size of the training set. Applied to the BioCreative 2012 Triage dataset, our method achieved 0.8030 mean average precision (MAP) in the official runs, resulting in the top MAP system among participants. Integrated with PubTator, a Web interface for annotating biomedical literature, the proposed system also received a positive review from the CTD curation team. PMID:23160415

Prioritizing PubMed articles for the Comparative Toxicogenomic Database utilizing semantic information.

PubMed

Kim, Sun; Kim, Won; Wei, Chih-Hsuan; Lu, Zhiyong; Wilbur, W John

2012-01-01

The Comparative Toxicogenomics Database (CTD) contains manually curated literature that describes chemical-gene interactions, chemical-disease relationships and gene-disease relationships. Finding articles containing this information is the first and an important step to assist manual curation efficiency. However, the complex nature of named entities and their relationships make it challenging to choose relevant articles. In this article, we introduce a machine learning framework for prioritizing CTD-relevant articles based on our prior system for the protein-protein interaction article classification task in BioCreative III. To address new challenges in the CTD task, we explore a new entity identification method for genes, chemicals and diseases. In addition, latent topics are analyzed and used as a feature type to overcome the small size of the training set. Applied to the BioCreative 2012 Triage dataset, our method achieved 0.8030 mean average precision (MAP) in the official runs, resulting in the top MAP system among participants. Integrated with PubTator, a Web interface for annotating biomedical literature, the proposed system also received a positive review from the CTD curation team.

What is in a name? Is food addiction a misnomer?

PubMed

Vella, Shae-Leigh; Pai, Nagesh

2017-02-01

Recently interest in the phenomenon of food addiction has increased substantially since the inclusion of gambling disorder in the DSM-5. However the phenomenon of food addiction remains controversial and the designation continues to lack clear consideration. Few researchers have offered an explicit theoretical definition of the phenomenon which is fundamental; as it not only pertains to the aetiology it also directs research and management of the phenomenon. Therefore this review explores 'what is in a name'? Specifically possible aetiologies of food addiction, eating addiction and food addiction as an eating disorder are reviewed and the potential DSM-5 classification espoused. It is evident that the phenomenon requires further research and evaluation in order to delineate whether the phenomenon constitutes a disorder and if the phenomenon is found to be a valid entity the most appropriate designation. As it is too early to draw definitive conclusions regarding the concept all plausible designations and the associated aetiologies require further investigation. Copyright © 2016 Elsevier B.V. All rights reserved.

Mayo Clinic/Renal Pathology Society Consensus Report on Pathologic Classification, Diagnosis, and Reporting of GN.

PubMed

Sethi, Sanjeev; Haas, Mark; Markowitz, Glen S; D'Agati, Vivette D; Rennke, Helmut G; Jennette, J Charles; Bajema, Ingeborg M; Alpers, Charles E; Chang, Anthony; Cornell, Lynn D; Cosio, Fernando G; Fogo, Agnes B; Glassock, Richard J; Hariharan, Sundaram; Kambham, Neeraja; Lager, Donna J; Leung, Nelson; Mengel, Michael; Nath, Karl A; Roberts, Ian S; Rovin, Brad H; Seshan, Surya V; Smith, Richard J H; Walker, Patrick D; Winearls, Christopher G; Appel, Gerald B; Alexander, Mariam P; Cattran, Daniel C; Casado, Carmen Avila; Cook, H Terence; De Vriese, An S; Radhakrishnan, Jai; Racusen, Lorraine C; Ronco, Pierre; Fervenza, Fernando C

2016-05-01

Renal pathologists and nephrologists met on February 20, 2015 to establish an etiology/pathogenesis-based system for classification and diagnosis of GN, with a major aim of standardizing the kidney biopsy report of GN. On the basis of etiology/pathogenesis, GN is classified into the following five pathogenic types, each with specific disease entities: immune-complex GN, pauci-immune GN, antiglomerular basement membrane GN, monoclonal Ig GN, and C3 glomerulopathy. The pathogenesis-based classification forms the basis of the kidney biopsy report. To standardize the report, the diagnosis consists of a primary diagnosis and a secondary diagnosis. The primary diagnosis should include the disease entity/pathogenic type (if disease entity is not known) followed in order by pattern of injury (mixed patterns may be present); score/grade/class for disease entities, such as IgA nephropathy, lupus nephritis, and ANCA GN; and additional features as detailed herein. A pattern diagnosis as the sole primary diagnosis is not recommended. Secondary diagnoses should be reported separately and include coexisting lesions that do not form the primary diagnosis. Guidelines for the report format, light microscopy, immunofluorescence microscopy, electron microscopy, and ancillary studies are also provided. In summary, this consensus report emphasizes a pathogenesis-based classification of GN and provides guidelines for the standardized reporting of GN. Copyright © 2016 by the American Society of Nephrology.

77 FR 31806 - Changes to Implement Micro Entity Status for Paying Patent Fees

Federal Register 2010, 2011, 2012, 2013, 2014

2012-05-30

... legislative history of 35 U.S.C. 123 is clear that it is directed to a subset of small entities, namely... history do not, for example, contemplate a for-profit, large entity applicant becoming a ``micro entity... across government agencies and identified goals designed to promote innovation; (8) considered approaches...

Building a protein name dictionary from full text: a machine learning term extraction approach.

PubMed

Shi, Lei; Campagne, Fabien

2005-04-07

The majority of information in the biological literature resides in full text articles, instead of abstracts. Yet, abstracts remain the focus of many publicly available literature data mining tools. Most literature mining tools rely on pre-existing lexicons of biological names, often extracted from curated gene or protein databases. This is a limitation, because such databases have low coverage of the many name variants which are used to refer to biological entities in the literature. We present an approach to recognize named entities in full text. The approach collects high frequency terms in an article, and uses support vector machines (SVM) to identify biological entity names. It is also computationally efficient and robust to noise commonly found in full text material. We use the method to create a protein name dictionary from a set of 80,528 full text articles. Only 8.3% of the names in this dictionary match SwissProt description lines. We assess the quality of the dictionary by studying its protein name recognition performance in full text. This dictionary term lookup method compares favourably to other published methods, supporting the significance of our direct extraction approach. The method is strong in recognizing name variants not found in SwissProt.

Building a protein name dictionary from full text: a machine learning term extraction approach

PubMed Central

Shi, Lei; Campagne, Fabien

2005-01-01

Background The majority of information in the biological literature resides in full text articles, instead of abstracts. Yet, abstracts remain the focus of many publicly available literature data mining tools. Most literature mining tools rely on pre-existing lexicons of biological names, often extracted from curated gene or protein databases. This is a limitation, because such databases have low coverage of the many name variants which are used to refer to biological entities in the literature. Results We present an approach to recognize named entities in full text. The approach collects high frequency terms in an article, and uses support vector machines (SVM) to identify biological entity names. It is also computationally efficient and robust to noise commonly found in full text material. We use the method to create a protein name dictionary from a set of 80,528 full text articles. Only 8.3% of the names in this dictionary match SwissProt description lines. We assess the quality of the dictionary by studying its protein name recognition performance in full text. Conclusion This dictionary term lookup method compares favourably to other published methods, supporting the significance of our direct extraction approach. The method is strong in recognizing name variants not found in SwissProt. PMID:15817129

Coping with changing controlled vocabularies.

PubMed Central

Cimino, J. J.; Clayton, P. D.

1994-01-01

For the foreseeable future, controlled medical vocabularies will be in a constant state of development, expansion and refinement. Changes in controlled vocabularies must be reconciled with historical patient information which is coded using those vocabularies and stored in clinical databases. This paper explores the kinds of changes that can occur in controlled vocabularies, including adding terms (simple additions, refinements, redundancy and disambiguation), deleting terms, changing terms (major and minor name changes), and other special situations (obsolescence, discovering redundancy, and precoordination). Examples are drawn from actual changes appearing in the 1993 update to the International Classification of Diseases (ICD9-CM). The methods being used at Columbia-Presbyterian Medical Center to reconcile its Medical Entities Dictionary and its clinical database are discussed. PMID:7949906

26 CFR 301.7701-3 - Classification of certain business entities.

Code of Federal Regulations, 2010 CFR

2010-04-01

... association (S1), which wholly owns another eligible entity classified as an association (S2), which wholly... this section are filed to classify S1, S2, and S3 each as disregarded as an entity separate from its... transaction occurring on the same day immediately after the preceding transaction S1 is treated as liquidating...

2 CFR 170.110 - Types of entities to which this part applies.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 2 Grants and Agreements 1 2013-01-01 2013-01-01 false Types of entities to which this part applies...) Apply for or receive agency awards; or (2) Receive subawards under those awards. (b) Exceptions. (1... his or her name). (2) None of the requirements regarding reporting names and total compensation of an...

2 CFR 170.110 - Types of entities to which this part applies.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 2 Grants and Agreements 1 2012-01-01 2012-01-01 false Types of entities to which this part applies...) Apply for or receive agency awards; or (2) Receive subawards under those awards. (b) Exceptions. (1... his or her name). (2) None of the requirements regarding reporting names and total compensation of an...

Improving Information Extraction and Translation Using Component Interactions

DTIC Science & Technology

2008-01-01

74 7. CASE STUDY ON MONOLINGUAL INTERACTION.....................................................................76 7.1 IMPROVING NAME TAGGING BY...interactions described above focused on the monolingual analysis pipeline. (Huang and Vogel, 2002) presented a cross-lingual joint inference example to...improve the extracted named entity translation dictionary and the entity annotation in a bilingual 22 training corpus. They used a more

Update on the integrated histopathological and genetic classification of medulloblastoma – a practical diagnostic guideline

PubMed Central

Pietsch, Torsten; Haberler, Christine

2016-01-01

The revised WHO classification of tumors of the CNS 2016 has introduced the concept of the integrated diagnosis. The definition of medulloblastoma entities now requires a combination of the traditional histological information with additional molecular/genetic features. For definition of the histopathological component of the medulloblastoma diagnosis, the tumors should be assigned to one of the four entities classic, desmoplastic/nodular (DNMB), extensive nodular (MBEN), or large cell/anaplastic (LC/A) medulloblastoma. The genetically defined component comprises the four entities WNT-activated, SHH-activated and TP53 wildtype, SHH-activated and TP53 mutant, or non-WNT/non-SHH medulloblastoma. Robust and validated methods are available to allow a precise diagnosis of these medulloblastoma entities according to the updated WHO classification, and for differential diagnostic purposes. A combination of immunohistochemical markers including β-catenin, Yap1, p75-NGFR, Otx2, and p53, in combination with targeted sequencing and copy number assessment such as FISH analysis for MYC genes allows a precise assignment of patients for risk-adapted stratification. It also allows comparison to results of study cohorts in the past and provides a robust basis for further treatment refinement. PMID:27781424

Update on the integrated histopathological and genetic classification of medulloblastoma - a practical diagnostic guideline.

PubMed

Pietsch, Torsten; Haberler, Christine

The revised WHO classification of tumors of the CNS 2016 has introduced the concept of the integrated diagnosis. The definition of medulloblastoma entities now requires a combination of the traditional histological information with additional molecular/genetic features. For definition of the histopathological component of the medulloblastoma diagnosis, the tumors should be assigned to one of the four entities classic, desmoplastic/nodular (DNMB), extensive nodular (MBEN), or large cell/anaplastic (LC/A) medulloblastoma. The genetically defined component comprises the four entities WNT-activated, SHH-activated and TP53 wildtype, SHH-activated and TP53 mutant, or non-WNT/non-SHH medulloblastoma. Robust and validated methods are available to allow a precise diagnosis of these medulloblastoma entities according to the updated WHO classification, and for differential diagnostic purposes. A combination of immunohistochemical markers including β-catenin, Yap1, p75-NGFR, Otx2, and p53, in combination with targeted sequencing and copy number assessment such as FISH analysis for MYC genes allows a precise assignment of patients for risk-adapted stratification. It also allows comparison to results of study cohorts in the past and provides a robust basis for further treatment refinement.
.

Finding Related Entities by Retrieving Relations: UIUC at TREC 2009 Entity Track

DTIC Science & Technology

2009-11-01

classes, depending on the categories they belong to. A music album could have any generic name, whereas a laptop model has a more generalizable name. A...names of music albums are simply plain text often capitalized, and so on. Thus, we feel that a better ap- proach would be to first identify the...origin domain of the text to be tagged (e.g., pharmaceutical, music , journal, etc.), and then apply tagging rules that are specific to that domain

BANNER: an executable survey of advances in biomedical named entity recognition.

PubMed

Leaman, Robert; Gonzalez, Graciela

2008-01-01

There has been an increasing amount of research on biomedical named entity recognition, the most basic text extraction problem, resulting in significant progress by different research teams around the world. This has created a need for a freely-available, open source system implementing the advances described in the literature. In this paper we present BANNER, an open-source, executable survey of advances in biomedical named entity recognition, intended to serve as a benchmark for the field. BANNER is implemented in Java as a machine-learning system based on conditional random fields and includes a wide survey of the best techniques recently described in the literature. It is designed to maximize domain independence by not employing brittle semantic features or rule-based processing steps, and achieves significantly better performance than existing baseline systems. It is therefore useful to developers as an extensible NER implementation, to researchers as a standard for comparing innovative techniques, and to biologists requiring the ability to find novel entities in large amounts of text.

31 CFR 598.408 - Alleged change in ownership or control of an entity designated as a specially designated...

Code of Federal Regulations, 2010 CFR

2010-07-01

... of capital; and contracts evidencing the sale of the entity to its new owners. (b) Any continuing... narcotics trafficker could lead to designation of the purchaser. Mere change in name of an entity will not...

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

Discovery of Predicate-Oriented Relations among Named Entities Extracted from Thai Texts

NASA Astrophysics Data System (ADS)

Tongtep, Nattapong; Theeramunkong, Thanaruk

Extracting named entities (NEs) and their relations is more difficult in Thai than in other languages due to several Thai specific characteristics, including no explicit boundaries for words, phrases and sentences; few case markers and modifier clues; high ambiguity in compound words and serial verbs; and flexible word orders. Unlike most previous works which focused on NE relations of specific actions, such as work_for, live_in, located_in, and kill, this paper proposes more general types of NE relations, called predicate-oriented relation (PoR), where an extracted action part (verb) is used as a core component to associate related named entities extracted from Thai Texts. Lacking a practical parser for the Thai language, we present three types of surface features, i.e. punctuation marks (such as token spaces), entity types and the number of entities and then apply five alternative commonly used learning schemes to investigate their performance on predicate-oriented relation extraction. The experimental results show that our approach achieves the F-measure of 97.76%, 99.19%, 95.00% and 93.50% on four different types of predicate-oriented relation (action-location, location-action, action-person and person-action) in crime-related news documents using a data set of 1,736 entity pairs. The effects of NE extraction techniques, feature sets and class unbalance on the performance of relation extraction are explored.

75 FR 9593 - Agency Information Collection Activities; Proposed Renewal of Several Currently Approved...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-03-03

... institutions participating in pesticide, fertilizer, and other agricultural chemical manufacturing [[Page 9595...: Entities potentially affected by this ICR include individuals or entities engaged in pesticide, fertilizer, and other agricultural chemical manufacturing (North American Industrial Classification System (NAICS...

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

PubMed

Dave, Rutwij A; Morris, Marilyn E

2016-09-10

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

31 CFR 306.88 - Political entities and public corporations.

Code of Federal Regulations, 2013 CFR

2013-07-01

... corporations. 306.88 Section 306.88 Money and Finance: Treasury Regulations Relating to Money and Finance... entities and public corporations. Securities registered in the name of, or assigned to, a State, county, city, town, village, school district or other political entity, public body or corporation, may be...

31 CFR 306.88 - Political entities and public corporations.

Code of Federal Regulations, 2014 CFR

2014-07-01

... corporations. 306.88 Section 306.88 Money and Finance: Treasury Regulations Relating to Money and Finance... entities and public corporations. Securities registered in the name of, or assigned to, a State, county, city, town, village, school district or other political entity, public body or corporation, may be...

31 CFR 306.88 - Political entities and public corporations.

Code of Federal Regulations, 2012 CFR

2012-07-01

... corporations. 306.88 Section 306.88 Money and Finance: Treasury Regulations Relating to Money and Finance... entities and public corporations. Securities registered in the name of, or assigned to, a State, county, city, town, village, school district or other political entity, public body or corporation, may be...

Moving Hands, Moving Entities

ERIC Educational Resources Information Center

Setti, Annalisa; Borghi, Anna M.; Tessari, Alessia

2009-01-01

In this study we investigated with a priming paradigm whether uni and bimanual actions presented as primes differently affected language processing. Animals' (self-moving entities) and plants' (not self-moving entities) names were used as targets. As prime we used grasping hands, presented both as static images and videos. The results showed an…

Anatomical Entity Recognition with a Hierarchical Framework Augmented by External Resources

PubMed Central

Xu, Yan; Hua, Ji; Ni, Zhaoheng; Chen, Qinlang; Fan, Yubo; Ananiadou, Sophia; Chang, Eric I-Chao; Tsujii, Junichi

2014-01-01

References to anatomical entities in medical records consist not only of explicit references to anatomical locations, but also other diverse types of expressions, such as specific diseases, clinical tests, clinical treatments, which constitute implicit references to anatomical entities. In order to identify these implicit anatomical entities, we propose a hierarchical framework, in which two layers of named entity recognizers (NERs) work in a cooperative manner. Each of the NERs is implemented using the Conditional Random Fields (CRF) model, which use a range of external resources to generate features. We constructed a dictionary of anatomical entity expressions by exploiting four existing resources, i.e., UMLS, MeSH, RadLex and BodyPart3D, and supplemented information from two external knowledge bases, i.e., Wikipedia and WordNet, to improve inference of anatomical entities from implicit expressions. Experiments conducted on 300 discharge summaries showed a micro-averaged performance of 0.8509 Precision, 0.7796 Recall and 0.8137 F1 for explicit anatomical entity recognition, and 0.8695 Precision, 0.6893 Recall and 0.7690 F1 for implicit anatomical entity recognition. The use of the hierarchical framework, which combines the recognition of named entities of various types (diseases, clinical tests, treatments) with information embedded in external knowledge bases, resulted in a 5.08% increment in F1. The resources constructed for this research will be made publicly available. PMID:25343498

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

PubMed

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

2011-10-01

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

12 CFR 1229.12 - Procedures related to capital classification and other actions.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 12 Banks and Banking 7 2010-01-01 2010-01-01 false Procedures related to capital classification and other actions. 1229.12 Section 1229.12 Banks and Banking FEDERAL HOUSING FINANCE AGENCY ENTITY REGULATIONS CAPITAL CLASSIFICATIONS AND PROMPT CORRECTIVE ACTION Federal Home Loan Banks § 1229.12 Procedures...

75 FR 54697 - Unblocking of Thirteen Specially Designated Nationals Pursuant to Executive Order 13224

Federal Register 2010, 2011, 2012, 2013, 2014

2010-09-08

... removing the names of ten entities and three individuals from the list of Specially Designated Nationals... Commit, Threaten To Commit, or Support Terrorism. DATES: The removal of ten entities and three... Foreign Assets Control has determined that these ten entities and three individuals no longer meet the...

78 FR 59880 - Enhanced Consumer Protections for Charter Air Transportation

Federal Register 2010, 2011, 2012, 2013, 2014

2013-09-30

...) The name of the company in operational control of the aircraft during flight; (2) any other ``doing... disclosure of the entity in operational control of the aircraft during the flight and seven of those comments... different from the entity in operational control of the aircraft, primarily on the basis that these entities...

Moving beyond the Name: Defining Corporate Entities to Support Provenance-Based Access

ERIC Educational Resources Information Center

Light, Michelle

2007-01-01

The second edition of the "International Standard Archival Authority Records for Corporate Bodies, Persons, and Families (ISAAR(CPF)2)" focuses on describing entities as they exist in reality, rather than on establishing authorized terms. This change allows authority records to include multiple authorized terms representing an entity as it changed…

A proposal for classification of entities combining vascular malformations and deregulated growth.

PubMed

Oduber, Charlène E U; van der Horst, Chantal M A M; Sillevis Smitt, J Henk; Smeulders, Mark J C; Mendiratta, Vibhu; Harper, John I; van Steensel, Maurice A M; Hennekam, Raoul C M

2011-01-01

Agreement on terminology and nomenclature is fundamental and essential for effective exchange of information between clinicians and researchers. An adequate terminology to describe all patients showing vascular malformations combined with deregulated growth is at present not available. To propose a classification of patients with vascular malformations, not restricted to the face, and growth disturbances based on simple, clinically visible characteristics, on which clinicians and researchers can comment and which should eventually lead to an internationally accepted classification. Rooted in our joint experience we established a classification of vascular malformation not limited to the face, with growth disturbances. It is based on the nature and localization of the vascular malformations; the nature, localization and timing of growth disturbances; the nature of co-localization of the vascular malformations and growth disturbances; the presence or absence of other features. Subsequently a mixed (experienced and non-experienced) group of observers evaluated 146 patients (106 from the Netherlands; 40 from the UK) with vascular malformations and disturbed growth, using the classification. Inter-observer variability was assessed by estimating the Intra-Class Correlation (ICC) coefficient and its 95% confidence interval. We defined 6 subgroups within the group of entities with vascular malformation-deregulated growth. Scoring the patients using the proposed classification yielded a high inter-observer reproducibility (ICC varying between 0.747 and 0.895 for all levels of flow). The presently proposed classification was found to be reliable and easy to use for patients with vascular malformations with growth disturbances. We invite both clinicians and researchers to comment on the classification, in order to improve it further. This way we may obtain our final aim of an internationally accepted classification of patients, which should facilitate both clinical treatment and care of, as well as research into the molecular background of entities combining vascular malformation and deregulated growth. Copyright © 2011 Elsevier Masson SAS. All rights reserved.

Using Workflows to Explore and Optimise Named Entity Recognition for Chemistry

PubMed Central

Kolluru, BalaKrishna; Hawizy, Lezan; Murray-Rust, Peter; Tsujii, Junichi; Ananiadou, Sophia

2011-01-01

Chemistry text mining tools should be interoperable and adaptable regardless of system-level implementation, installation or even programming issues. We aim to abstract the functionality of these tools from the underlying implementation via reconfigurable workflows for automatically identifying chemical names. To achieve this, we refactored an established named entity recogniser (in the chemistry domain), OSCAR and studied the impact of each component on the net performance. We developed two reconfigurable workflows from OSCAR using an interoperable text mining framework, U-Compare. These workflows can be altered using the drag-&-drop mechanism of the graphical user interface of U-Compare. These workflows also provide a platform to study the relationship between text mining components such as tokenisation and named entity recognition (using maximum entropy Markov model (MEMM) and pattern recognition based classifiers). Results indicate that, for chemistry in particular, eliminating noise generated by tokenisation techniques lead to a slightly better performance than others, in terms of named entity recognition (NER) accuracy. Poor tokenisation translates into poorer input to the classifier components which in turn leads to an increase in Type I or Type II errors, thus, lowering the overall performance. On the Sciborg corpus, the workflow based system, which uses a new tokeniser whilst retaining the same MEMM component, increases the F-score from 82.35% to 84.44%. On the PubMed corpus, it recorded an F-score of 84.84% as against 84.23% by OSCAR. PMID:21633495

Using workflows to explore and optimise named entity recognition for chemistry.

PubMed

Kolluru, Balakrishna; Hawizy, Lezan; Murray-Rust, Peter; Tsujii, Junichi; Ananiadou, Sophia

2011-01-01

Chemistry text mining tools should be interoperable and adaptable regardless of system-level implementation, installation or even programming issues. We aim to abstract the functionality of these tools from the underlying implementation via reconfigurable workflows for automatically identifying chemical names. To achieve this, we refactored an established named entity recogniser (in the chemistry domain), OSCAR and studied the impact of each component on the net performance. We developed two reconfigurable workflows from OSCAR using an interoperable text mining framework, U-Compare. These workflows can be altered using the drag-&-drop mechanism of the graphical user interface of U-Compare. These workflows also provide a platform to study the relationship between text mining components such as tokenisation and named entity recognition (using maximum entropy Markov model (MEMM) and pattern recognition based classifiers). Results indicate that, for chemistry in particular, eliminating noise generated by tokenisation techniques lead to a slightly better performance than others, in terms of named entity recognition (NER) accuracy. Poor tokenisation translates into poorer input to the classifier components which in turn leads to an increase in Type I or Type II errors, thus, lowering the overall performance. On the Sciborg corpus, the workflow based system, which uses a new tokeniser whilst retaining the same MEMM component, increases the F-score from 82.35% to 84.44%. On the PubMed corpus, it recorded an F-score of 84.84% as against 84.23% by OSCAR.

Evaluating Stream Filtering for Entity Profile Updates in TREC 2012, 2013, and 2014 (KBA Track Overview, Notebook Paper)

DTIC Science & Technology

2014-11-01

possible future directions that build on the KBA experience.   Data Assets   In addition to the three hundred run submissions from diverse systems...form name of an entity and assigning a confidence score based on the number of matches of tokens in the name. See code in github [6]. macro-P...131 64 GENDER 4 2 FoundedBy     56 30 NAME 2 2 DateOfDeath     54 12 TOP_MEMBERS_EMPLOYEES 2 1 EmployeeOf     44 19 WON_AWARD 1 1

Handwritten-word spotting using biologically inspired features.

PubMed

van der Zant, Tijn; Schomaker, Lambert; Haak, Koen

2008-11-01

For quick access to new handwritten collections, current handwriting recognition methods are too cumbersome. They cannot deal with the lack of labeled data and would require extensive laboratory training for each individual script, style, language and collection. We propose a biologically inspired whole-word recognition method which is used to incrementally elicit word labels in a live, web-based annotation system, named Monk. Since human labor should be minimized given the massive amount of image data, it becomes important to rely on robust perceptual mechanisms in the machine. Recent computational models of the neuro-physiology of vision are applied to isolated word classification. A primate cortex-like mechanism allows to classify text-images that have a low frequency of occurrence. Typically these images are the most difficult to retrieve and often contain named entities and are regarded as the most important to people. Usually standard pattern-recognition technology cannot deal with these text-images if there are not enough labeled instances. The results of this retrieval system are compared to normalized word-image matching and appear to be very promising.

Automatically Recognizing Medication and Adverse Event Information From Food and Drug Administration’s Adverse Event Reporting System Narratives

PubMed Central

Polepalli Ramesh, Balaji; Belknap, Steven M; Li, Zuofeng; Frid, Nadya; West, Dennis P

2014-01-01

Background The Food and Drug Administration’s (FDA) Adverse Event Reporting System (FAERS) is a repository of spontaneously-reported adverse drug events (ADEs) for FDA-approved prescription drugs. FAERS reports include both structured reports and unstructured narratives. The narratives often include essential information for evaluation of the severity, causality, and description of ADEs that are not present in the structured data. The timely identification of unknown toxicities of prescription drugs is an important, unsolved problem. Objective The objective of this study was to develop an annotated corpus of FAERS narratives and biomedical named entity tagger to automatically identify ADE related information in the FAERS narratives. Methods We developed an annotation guideline and annotate medication information and adverse event related entities on 122 FAERS narratives comprising approximately 23,000 word tokens. A named entity tagger using supervised machine learning approaches was built for detecting medication information and adverse event entities using various categories of features. Results The annotated corpus had an agreement of over .9 Cohen’s kappa for medication and adverse event entities. The best performing tagger achieves an overall performance of 0.73 F1 score for detection of medication, adverse event and other named entities. Conclusions In this study, we developed an annotated corpus of FAERS narratives and machine learning based models for automatically extracting medication and adverse event information from the FAERS narratives. Our study is an important step towards enriching the FAERS data for postmarketing pharmacovigilance. PMID:25600332

76 FR 13449 - Proposed Collection; Comment Request for Revenue Procedure 2009-41 (Rev. Proc. 2002-59 Is...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-03-11

... Classification Elections. DATES: Written comments should be received on or before May 10, 2011 to be assured of... Classification Elections. OMB Number: 1545-1771. Revenue Procedure Number: Revenue Procedure 2009-41. (Rev. Proc... Internal Revenue Code for an eligible entity that requests relief for a late classification election filed...

26 CFR 301.7701(i)-3 - Effective dates and duration of taxable mortgage pool classification.

Code of Federal Regulations, 2011 CFR

2011-04-01

... mortgage pool classification. 301.7701(i)-3 Section 301.7701(i)-3 Internal Revenue INTERNAL REVENUE SERVICE... § 301.7701(i)-3 Effective dates and duration of taxable mortgage pool classification. (a) Effective... connected to the entity's issuance of related debt obligations (as defined in paragraph (b)(3) of this...

Tooth wear: attrition, erosion, and abrasion.

PubMed

Litonjua, Luis A; Andreana, Sebastiano; Bush, Peter J; Cohen, Robert E

2003-06-01

Attrition, erosion, and abrasion result in alterations to the tooth and manifest as tooth wear. Each classification acts through a distinct process that is associated with unique clinical characteristics. Accurate prevalence data for each classification are not available since indices do not necessarily measure one specific etiology, or the study populations may be too diverse in age and characteristics. The treatment of teeth in each classification will depend on identifying the factors associated with each etiology. Some cases may require specific restorative procedures, while others will not require treatment. A review of the literature points to the interaction of the three entities in the initiation and progression of lesions that may act synchronously or sequentially, synergistically or additively, or in conjunction with other entities to mask the true nature of tooth wear, which appears to be multifactorial.

Principles for ecological classification

Treesearch

Dennis H. Grossman; Patrick Bourgeron; Wolf-Dieter N. Busch; David T. Cleland; William Platts; G. Ray; C. Robins; Gary Roloff

1999-01-01

The principal purpose of any classification is to relate common properties among different entities to facilitate understanding of evolutionary and adaptive processes. In the context of this volume, it is to facilitate ecosystem stewardship, i.e., to help support ecosystem conservation and management objectives.

41 CFR 102-173.50 - What is the naming convention for States?

Code of Federal Regulations, 2014 CFR

2014-01-01

...-INTERNET GOV DOMAIN Registration § 102-173.50 What is the naming convention for States? (a) To register any second-level domain within dot-gov, State government entities must register the full State name or clearly indicate the State postal code within the name. Examples of acceptable names include virginia.gov...

41 CFR 102-173.50 - What is the naming convention for States?

Code of Federal Regulations, 2011 CFR

2011-01-01

...-INTERNET GOV DOMAIN Registration § 102-173.50 What is the naming convention for States? (a) To register any second-level domain within dot-gov, State government entities must register the full State name or clearly indicate the State postal code within the name. Examples of acceptable names include virginia.gov...

41 CFR 102-173.50 - What is the naming convention for States?

Code of Federal Regulations, 2010 CFR

2010-07-01

...-INTERNET GOV DOMAIN Registration § 102-173.50 What is the naming convention for States? (a) To register any second-level domain within dot-gov, State government entities must register the full State name or clearly indicate the State postal code within the name. Examples of acceptable names include virginia.gov...

41 CFR 102-173.50 - What is the naming convention for States?

Code of Federal Regulations, 2013 CFR

2013-07-01

...-INTERNET GOV DOMAIN Registration § 102-173.50 What is the naming convention for States? (a) To register any second-level domain within dot-gov, State government entities must register the full State name or clearly indicate the State postal code within the name. Examples of acceptable names include virginia.gov...

41 CFR 102-173.50 - What is the naming convention for States?

Code of Federal Regulations, 2012 CFR

2012-01-01

...-INTERNET GOV DOMAIN Registration § 102-173.50 What is the naming convention for States? (a) To register any second-level domain within dot-gov, State government entities must register the full State name or clearly indicate the State postal code within the name. Examples of acceptable names include virginia.gov...

Schizo-affective psychosis: fact or fiction? A survey of the literature.

PubMed

Procci, W R

1976-10-01

The classification of functional psychoses has traditionally been dichotomous with schizophrenia and manic-depressive disorder, which are considered separate entities. However, the psychiatric literature is replete with descriptions of psychoses with mixed features. A variety of names has been applied to these psychoses, including the term "schizo-affective." Confusion exists regarding the nature of these psychoses, much of it resulting from a tendency to limit investigation to an acute view of symptom complexes. This article examines the schizo-affective states across a variety of dimensions, including the acute symptomatologic picture, response to lithium carbonate therapy, follow-up studies, family history, and genetics. While the term "schizo-affective," as commonly used, probably describes a heterogeneous group of psychoses, considerable evidence supports the hypothesis that at least a subgroup of these psychoses has a definite relationship to the major affective disorders.

Fostering Multilinguality in the UMLS: A Computational Approach to Terminology Expansion for Multiple Languages

PubMed Central

Hellrich, Johannes; Hahn, Udo

2014-01-01

We here report on efforts to computationally support the maintenance and extension of multilingual biomedical terminology resources. Our main idea is to treat term acquisition as a classification problem guided by term alignment in parallel multilingual corpora, using termhood information coming from of a named entity recognition system as a novel feature. We report on experiments for Spanish, French, German and Dutch parts of a multilingual UMLS-derived biomedical terminology. These efforts yielded 19k, 18k, 23k and 12k new terms and synonyms, respectively, from which about half relate to concepts without a previously available term label for these non-English languages. Based on expert assessment of a novel German terminology sample, 80% of the newly acquired terms were judged as reasonable additions to the terminology. PMID:25954371

41 CFR 102-173.25 - What definitions apply to this part?

Code of Federal Regulations, 2014 CFR

2014-01-01

... Management Regulations System (Continued) FEDERAL MANAGEMENT REGULATION TELECOMMUNICATIONS 173-INTERNET GOV... Administration (GSA) is responsible for registrations in the dot-gov domain. Domain name is a name assigned to an... domain name server. A domain name locates the organization or other entity on the Internet. The dot gov...

41 CFR 102-173.25 - What definitions apply to this part?

Code of Federal Regulations, 2013 CFR

2013-07-01

... Management Regulations System (Continued) FEDERAL MANAGEMENT REGULATION TELECOMMUNICATIONS 173-INTERNET GOV... Administration (GSA) is responsible for registrations in the dot-gov domain. Domain name is a name assigned to an... domain name server. A domain name locates the organization or other entity on the Internet. The dot gov...

41 CFR 102-173.25 - What definitions apply to this part?

Code of Federal Regulations, 2012 CFR

2012-01-01

... Management Regulations System (Continued) FEDERAL MANAGEMENT REGULATION TELECOMMUNICATIONS 173-INTERNET GOV... Administration (GSA) is responsible for registrations in the dot-gov domain. Domain name is a name assigned to an... domain name server. A domain name locates the organization or other entity on the Internet. The dot gov...

Translation of the Department of Defense Disease and Injury Codes to the Eighth Revision International Classification of Diseases for use by the Military Services.

DTIC Science & Technology

1976-06-01

with, the DDDIC entity. 3. The ICDA-8 contracts groups of diseases or accidents which had been presented in expanded form in the DDDIC. Example: DDDIC...DDDIC. 4. The ICDA-8 expands groups of entities which had been presented in more condensed folin in the DDDIC. Example: DDDIC ICDA-8 Code Ntmuber Code...rapidly find a disease entity and all closely related entities. At the Naval Health Research Center (N11RC) a new code nunber was given to each

Aggressive B-cell lymphomas in the update of the 4th edition of the World Health Organization classification of haematopoietic and lymphatic tissues: refinements of the classification, new entities and genetic findings.

PubMed

Ott, German

2017-09-01

The update of the 4th edition of the World Health Organization Classification of Haematopoietic and Lymphatic Tissues portends important new findings and concepts in the diagnosis, classification and biology of lymphomas. This review summarizes the basic concepts and cornerstones of the classification of aggressive B-cell lymphomas and details the major changes. Of importance, there is a new concept of High-grade B-cell lymphomas (HGBL), partly replacing the provisional entity of B-cell lymphoma, unclassifiable, with features intermediate between diffuse large B-cell lymphoma (DLBCL) and Burkitt lymphoma, the so-called grey zone lymphomas. They either harbour MYC translocations together with a BCL2 and/or a BCL6 rearrangement (HGBL-Double Hit) or HGBL, not otherwise specified (NOS), lacking a double or triple hit constellation. In addition, the requirement for providing the cell-of-origin classification in the diagnostic work-up of DLBCLs, the role of MYC alterations in DLBCL subtypes, and newer findings in the specific variants/subtypes are highlighted. © 2017 John Wiley & Sons Ltd.

12 CFR 602.24 - Responses to demands served on non-FCA employees or entities.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 12 Banks and Banking 6 2010-01-01 2010-01-01 false Responses to demands served on non-FCA employees or entities. 602.24 Section 602.24 Banks and Banking FARM CREDIT ADMINISTRATION ADMINISTRATIVE... Not a Named Party § 602.24 Responses to demands served on non-FCA employees or entities. If you are...

29 CFR 510.24 - Governmental entities eligible for minimum wage phase-in.

Code of Federal Regulations, 2010 CFR

2010-07-01

.... 510.24 Section 510.24 Labor Regulations Relating to Labor (Continued) WAGE AND HOUR DIVISION... FAIR LABOR STANDARDS ACT IN PUERTO RICO Classification of Industries § 510.24 Governmental entities... engaged in one or more of the “traditional” functions listed in § 510.24 (a) or (b). All other employees...

Evaluation and Cross-Comparison of Lexical Entities of Biological Interest (LexEBI)

PubMed Central

Rebholz-Schuhmann, Dietrich; Kim, Jee-Hyub; Yan, Ying; Dixit, Abhishek; Friteyre, Caroline; Hoehndorf, Robert; Backofen, Rolf; Lewin, Ian

2013-01-01

Motivation Biomedical entities, their identifiers and names, are essential in the representation of biomedical facts and knowledge. In the same way, the complete set of biomedical and chemical terms, i.e. the biomedical “term space” (the “Lexeome”), forms a key resource to achieve the full integration of the scientific literature with biomedical data resources: any identified named entity can immediately be normalized to the correct database entry. This goal does not only require that we are aware of all existing terms, but would also profit from knowing all their senses and their semantic interpretation (ambiguities, nestedness). Result This study compiles a resource for lexical terms of biomedical interest in a standard format (called “LexEBI”), determines the overall number of terms, their reuse in different resources and the nestedness of terms. LexEBI comprises references for protein and gene entries and their term variants and chemical entities amongst other terms. In addition, disease terms have been identified from Medline and PubmedCentral and added to LexEBI. Our analysis demonstrates that the baseforms of terms from the different semantic types show only little polysemous use. Nonetheless, the term variants of protein and gene names (PGNs) frequently contain species mentions, which should have been avoided according to protein annotation guidelines. Furthermore, the protein and gene entities as well as the chemical entities, both do comprise enzymes leading to hierarchical polysemy, and a large portion of PGNs make reference to a chemical entity. Altogether, according to our analysis based on the Medline distribution, 401,869 unique PGNs in the documents contain a reference to 25,022 chemical entities, 3,125 disease terms or 1,576 species mentions. Conclusion LexEBI delivers the complete biomedical and chemical Lexeome in a standardized representation (http://www.ebi.ac.uk/Rebholz-srv/LexEBI/). The resource provides the disease terms as open source content, and fully interlinks terms across resources. PMID:24124474

13 CFR 121.101 - What are SBA size standards?

Code of Federal Regulations, 2011 CFR

2011-01-01

... SBA size standards? (a) SBA's size standards define whether a business entity is small and, thus... Industry Classification System (NAICS). (b) NAICS is described in the North American Industry Classification Manual-United States, which is available from the National Technical Information Service, 5285...

13 CFR 121.101 - What are SBA size standards?

Code of Federal Regulations, 2010 CFR

2010-01-01

... SBA size standards? (a) SBA's size standards define whether a business entity is small and, thus... Industry Classification System (NAICS). (b) NAICS is described in the North American Industry Classification Manual-United States, which is available from the National Technical Information Service, 5285...

[Aggressive B‑cell lymphomas : Recommendations from the German Panel of Reference Pathologists in the Competence Network on Malignant Lymphomas on diagnostic procedures according to the current WHO classification, update 2017].

PubMed

Klapper, W; Fend, F; Feller, A; Hansmann, M L; Möller, P; Stein, H; Rosenwald, A; Ott, G

2018-04-17

The update of the 4th edition of the WHO classification for hematopoietic neoplasms introduces changes in the field of mature aggressive B‑cell lymphomas that are relevant to diagnostic pathologists. In daily practice, the question arises of which analysis should be performed when diagnosing the most common lymphoma entity, diffuse large B‑cell lymphoma. We discuss the importance of the cell of origin, the analysis of MYC translocations, and the delineation of the new WHO entities of high-grade B‑cell lymphomas.

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

PubMed Central

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

2011-01-01

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

78 FR 26244 - Updating of Employer Identification Numbers

Federal Register 2010, 2011, 2012, 2013, 2014

2013-05-06

... (including updated application information regarding the name and taxpayer identifying number of the... require these persons to update application information regarding the name and taxpayer identifying number..., Application for Employer Identification Number, requires entities to disclose the name of the EIN applicant's...

Chemical Entity Recognition and Resolution to ChEBI

PubMed Central

Grego, Tiago; Pesquita, Catia; Bastos, Hugo P.; Couto, Francisco M.

2012-01-01

Chemical entities are ubiquitous through the biomedical literature and the development of text-mining systems that can efficiently identify those entities are required. Due to the lack of available corpora and data resources, the community has focused its efforts in the development of gene and protein named entity recognition systems, but with the release of ChEBI and the availability of an annotated corpus, this task can be addressed. We developed a machine-learning-based method for chemical entity recognition and a lexical-similarity-based method for chemical entity resolution and compared them with Whatizit, a popular-dictionary-based method. Our methods outperformed the dictionary-based method in all tasks, yielding an improvement in F-measure of 20% for the entity recognition task, 2–5% for the entity-resolution task, and 15% for combined entity recognition and resolution tasks. PMID:25937941

WHU at TREC KBA Vital Filtering Track 2014

DTIC Science & Technology

2014-11-01

view the problem as a classification problem and use Stanford NLP Toolkit to extract necessary information. Various kinds of features are leveraged to...profile of an entity. Our approach is to view the problem as a classification problem and use Stanford NLP Toolkit to extract necessary information

Classification of Pinus patula, P. tecunumanii, P. oocarpa, P. caribaea var. hondurensis, and Related Taxonomic Entities

Treesearch

A.E. Squillace; Jesse P. Perry

1992-01-01

Stem xylem terpenes of 75 pine populations were studied to determine relationships among taxonomic entities. Typical Pinus patula populations occurring in areas north and west of Oaxaca, Mexico, had very high proportions of 3-phellandrene and low proportions of other constituents. Terpene compositions of populations of variety longipeduncalatain...

Taxonomic indexing--extending the role of taxonomy.

PubMed

Patterson, David J; Remsen, David; Marino, William A; Norton, Cathy

2006-06-01

Taxonomic indexing refers to a new array of taxonomically intelligent network services that use nomenclatural principles and elements of expert taxonomic knowledge to manage information about organisms. Taxonomic indexing was introduced to help manage the increasing amounts of digital information about biology. It has been designed to form a near basal layer in a layered cyberinfrastructure that deals with biological information. Taxonomic Indexing accommodates the special problems of using names of organisms to index biological material. It links alternative names for the same entity (reconciliation), and distinguishes between uses of the same name for different entities (disambiguation), and names are placed within an indefinite number of hierarchical schemes. In order to access all information on all organisms, Taxonomic indexing must be able to call on a registry of all names in all forms for all organisms. NameBank has been developed to meet that need. Taxonomic indexing is an area of informatics that overlaps with taxonomy, is dependent on the expert input of taxonomists, and reveals the relevance of the discipline to a wide audience.

Deep learning with word embeddings improves biomedical named entity recognition.

PubMed

Habibi, Maryam; Weber, Leon; Neves, Mariana; Wiegandt, David Luis; Leser, Ulf

2017-07-15

Text mining has become an important tool for biomedical research. The most fundamental text-mining task is the recognition of biomedical named entities (NER), such as genes, chemicals and diseases. Current NER methods rely on pre-defined features which try to capture the specific surface properties of entity types, properties of the typical local context, background knowledge, and linguistic information. State-of-the-art tools are entity-specific, as dictionaries and empirically optimal feature sets differ between entity types, which makes their development costly. Furthermore, features are often optimized for a specific gold standard corpus, which makes extrapolation of quality measures difficult. We show that a completely generic method based on deep learning and statistical word embeddings [called long short-term memory network-conditional random field (LSTM-CRF)] outperforms state-of-the-art entity-specific NER tools, and often by a large margin. To this end, we compared the performance of LSTM-CRF on 33 data sets covering five different entity classes with that of best-of-class NER tools and an entity-agnostic CRF implementation. On average, F1-score of LSTM-CRF is 5% above that of the baselines, mostly due to a sharp increase in recall. The source code for LSTM-CRF is available at https://github.com/glample/tagger and the links to the corpora are available at https://corposaurus.github.io/corpora/ . habibima@informatik.hu-berlin.de. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Deep learning with word embeddings improves biomedical named entity recognition

PubMed Central

Habibi, Maryam; Weber, Leon; Neves, Mariana; Wiegandt, David Luis; Leser, Ulf

2017-01-01

Abstract Motivation: Text mining has become an important tool for biomedical research. The most fundamental text-mining task is the recognition of biomedical named entities (NER), such as genes, chemicals and diseases. Current NER methods rely on pre-defined features which try to capture the specific surface properties of entity types, properties of the typical local context, background knowledge, and linguistic information. State-of-the-art tools are entity-specific, as dictionaries and empirically optimal feature sets differ between entity types, which makes their development costly. Furthermore, features are often optimized for a specific gold standard corpus, which makes extrapolation of quality measures difficult. Results: We show that a completely generic method based on deep learning and statistical word embeddings [called long short-term memory network-conditional random field (LSTM-CRF)] outperforms state-of-the-art entity-specific NER tools, and often by a large margin. To this end, we compared the performance of LSTM-CRF on 33 data sets covering five different entity classes with that of best-of-class NER tools and an entity-agnostic CRF implementation. On average, F1-score of LSTM-CRF is 5% above that of the baselines, mostly due to a sharp increase in recall. Availability and implementation: The source code for LSTM-CRF is available at https://github.com/glample/tagger and the links to the corpora are available at https://corposaurus.github.io/corpora/. Contact: habibima@informatik.hu-berlin.de PMID:28881963

LeadMine: a grammar and dictionary driven approach to entity recognition.

PubMed

Lowe, Daniel M; Sayle, Roger A

2015-01-01

Chemical entity recognition has traditionally been performed by machine learning approaches. Here we describe an approach using grammars and dictionaries. This approach has the advantage that the entities found can be directly related to a given grammar or dictionary, which allows the type of an entity to be known and, if an entity is misannotated, indicates which resource should be corrected. As recognition is driven by what is expected, if spelling errors occur, they can be corrected. Correcting such errors is highly useful when attempting to lookup an entity in a database or, in the case of chemical names, converting them to structures. Our system uses a mixture of expertly curated grammars and dictionaries, as well as dictionaries automatically derived from public resources. We show that the heuristics developed to filter our dictionary of trivial chemical names (from PubChem) yields a better performing dictionary than the previously published Jochem dictionary. Our final system performs post-processing steps to modify the boundaries of entities and to detect abbreviations. These steps are shown to significantly improve performance (2.6% and 4.0% F1-score respectively). Our complete system, with incremental post-BioCreative workshop improvements, achieves 89.9% precision and 85.4% recall (87.6% F1-score) on the CHEMDNER test set. Grammar and dictionary approaches can produce results at least as good as the current state of the art in machine learning approaches. While machine learning approaches are commonly thought of as "black box" systems, our approach directly links the output entities to the input dictionaries and grammars. Our approach also allows correction of errors in detected entities, which can assist with entity resolution.

LeadMine: a grammar and dictionary driven approach to entity recognition

PubMed Central

2015-01-01

Background Chemical entity recognition has traditionally been performed by machine learning approaches. Here we describe an approach using grammars and dictionaries. This approach has the advantage that the entities found can be directly related to a given grammar or dictionary, which allows the type of an entity to be known and, if an entity is misannotated, indicates which resource should be corrected. As recognition is driven by what is expected, if spelling errors occur, they can be corrected. Correcting such errors is highly useful when attempting to lookup an entity in a database or, in the case of chemical names, converting them to structures. Results Our system uses a mixture of expertly curated grammars and dictionaries, as well as dictionaries automatically derived from public resources. We show that the heuristics developed to filter our dictionary of trivial chemical names (from PubChem) yields a better performing dictionary than the previously published Jochem dictionary. Our final system performs post-processing steps to modify the boundaries of entities and to detect abbreviations. These steps are shown to significantly improve performance (2.6% and 4.0% F1-score respectively). Our complete system, with incremental post-BioCreative workshop improvements, achieves 89.9% precision and 85.4% recall (87.6% F1-score) on the CHEMDNER test set. Conclusions Grammar and dictionary approaches can produce results at least as good as the current state of the art in machine learning approaches. While machine learning approaches are commonly thought of as "black box" systems, our approach directly links the output entities to the input dictionaries and grammars. Our approach also allows correction of errors in detected entities, which can assist with entity resolution. PMID:25810776

Enterprise Standard Industrial Classification Manual. 1974.

ERIC Educational Resources Information Center

Executive Office of the President, Washington, DC. Statistical Policy Div.

This classification is presented to provide a standard for use with statistics about enterprises (i.e., companies, rather than their individual establishments) by kind of economic activity. The enterprise unit consists of all establishments under common direct or indirect ownership. It is defined to include all entities, including subsidiaries,…

77 FR 38627 - Agency Information Collection Activities; Submission to OMB for Review and Approval; Comment...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-06-28

....regulations.gov . Title: Criteria for Classification of Solid Waste Disposal Facilities and Practices (Renewal... Classification of Solid Waste Disposal Facilities and Practices'' (40 CFR part 257) are self implementing.... Respondents/Affected Entities: Private Solid Waste Disposal Facilities, States. Estimated Number of...

Recognizing the Emotional Valence of Names: An ERP Study

ERIC Educational Resources Information Center

Wang, Lin; Zhu, Zude; Bastiaansen, Marcel; Hagoort, Peter; Yang, Yufang

2013-01-01

Unlike common nouns, person names refer to unique entities and generally have a referring function. We used event-related potentials to investigate the time course of identifying the emotional meaning of nouns and names. The emotional valence of names and nouns were manipulated separately. The results show early N1 effects in response to emotional…

Self-similarity Clustering Event Detection Based on Triggers Guidance

NASA Astrophysics Data System (ADS)

Zhang, Xianfei; Li, Bicheng; Tian, Yuxuan

Traditional method of Event Detection and Characterization (EDC) regards event detection task as classification problem. It makes words as samples to train classifier, which can lead to positive and negative samples of classifier imbalance. Meanwhile, there is data sparseness problem of this method when the corpus is small. This paper doesn't classify event using word as samples, but cluster event in judging event types. It adopts self-similarity to convergence the value of K in K-means algorithm by the guidance of event triggers, and optimizes clustering algorithm. Then, combining with named entity and its comparative position information, the new method further make sure the pinpoint type of event. The new method avoids depending on template of event in tradition methods, and its result of event detection can well be used in automatic text summarization, text retrieval, and topic detection and tracking.

24 CFR 1710.208 - General information.

Code of Federal Regulations, 2010 CFR

2010-04-01

... any of the principals of the owner or developer are corporate entities, name the parent and/or... registration or prohibited sales, name the State involved and give the reasons cited by the State for their... made with the SEC, give the SEC identification number; identify the prospectus by name; date of filing...

24 CFR 1710.208 - General information.

Code of Federal Regulations, 2014 CFR

2014-04-01

... any of the principals of the owner or developer are corporate entities, name the parent and/or... registration or prohibited sales, name the State involved and give the reasons cited by the State for their... made with the SEC, give the SEC identification number; identify the prospectus by name; date of filing...

24 CFR 1710.208 - General information.

Code of Federal Regulations, 2013 CFR

2013-04-01

... any of the principals of the owner or developer are corporate entities, name the parent and/or... registration or prohibited sales, name the State involved and give the reasons cited by the State for their... made with the SEC, give the SEC identification number; identify the prospectus by name; date of filing...

24 CFR 1710.208 - General information.

Code of Federal Regulations, 2011 CFR

2011-04-01

... any of the principals of the owner or developer are corporate entities, name the parent and/or... registration or prohibited sales, name the State involved and give the reasons cited by the State for their... made with the SEC, give the SEC identification number; identify the prospectus by name; date of filing...

24 CFR 1710.208 - General information.

Code of Federal Regulations, 2012 CFR

2012-04-01

... any of the principals of the owner or developer are corporate entities, name the parent and/or... registration or prohibited sales, name the State involved and give the reasons cited by the State for their... made with the SEC, give the SEC identification number; identify the prospectus by name; date of filing...

Deadlock Detection in Computer Networks

DTIC Science & Technology

1977-09-01

it entity class name (ndm-procownerref) = -:"node tab5le" I procnode_name z res-rnode-name call then return; nc ll c eck -for-deadlock(p_obplref...demo12 ~-exlusive sae con Caobridg Fina Sttonaa con0 Official Distribution List Defense Documentation Center New York Area Office Cameron Station 715

Towards a new classification of stable phase schizophrenia into major and simple neuro-cognitive psychosis: Results of unsupervised machine learning analysis.

PubMed

Kanchanatawan, Buranee; Sriswasdi, Sira; Thika, Supaksorn; Stoyanov, Drozdstoy; Sirivichayakul, Sunee; Carvalho, André F; Geffard, Michel; Maes, Michael

2018-05-23

Deficit schizophrenia, as defined by the Schedule for Deficit Syndrome, may represent a distinct diagnostic class defined by neurocognitive impairments coupled with changes in IgA/IgM responses to tryptophan catabolites (TRYCATs). Adequate classifications should be based on supervised and unsupervised learning rather than on consensus criteria. This study used machine learning as means to provide a more accurate classification of patients with stable phase schizophrenia. We found that using negative symptoms as discriminatory variables, schizophrenia patients may be divided into two distinct classes modelled by (A) impairments in IgA/IgM responses to noxious and generally more protective tryptophan catabolites, (B) impairments in episodic and semantic memory, paired associative learning and false memory creation, and (C) psychotic, excitation, hostility, mannerism, negative, and affective symptoms. The first cluster shows increased negative, psychotic, excitation, hostility, mannerism, depression and anxiety symptoms, and more neuroimmune and cognitive disorders and is therefore called "major neurocognitive psychosis" (MNP). The second cluster, called "simple neurocognitive psychosis" (SNP) is discriminated from normal controls by the same features although the impairments are less well developed than in MNP. The latter is additionally externally validated by lowered quality of life, body mass (reflecting a leptosome body type), and education (reflecting lower cognitive reserve). Previous distinctions including "type 1" (positive)/"type 2" (negative) and DSM-IV-TR (eg, paranoid) schizophrenia could not be validated using machine learning techniques. Previous names of the illness, including schizophrenia, are not very adequate because they do not describe the features of the illness, namely, interrelated neuroimmune, cognitive, and clinical features. Stable-phase schizophrenia consists of 2 relevant qualitatively distinct categories or nosological entities with SNP being a less well-developed phenotype, while MNP is the full blown phenotype or core illness. Major neurocognitive psychosis and SNP should be added to the DSM-5 and incorporated into the Research Domain Criteria project. © 2018 John Wiley & Sons, Ltd.

Advances in the understanding and clinical management of mastocytosis and clonal mast cell activation syndromes

PubMed Central

2016-01-01

Clonal mast cell activation syndromes and indolent systemic mastocytosis without skin involvement are two emerging entities that sometimes might be clinically difficult to distinguish, and they involve a great challenge for the physician from both a diagnostic and a therapeutic point of view. Furthermore, final diagnosis of both entities requires a bone marrow study; it is recommended that this be done in reference centers. In this article, we address the current consensus and guidelines for the suspicion, diagnosis, classification, treatment, and management of these two entities. PMID:27909577

Advances in the understanding and clinical management of mastocytosis and clonal mast cell activation syndromes.

PubMed

González-de-Olano, David; Matito, Almudena; Orfao, Alberto; Escribano, Luis

2016-01-01

Clonal mast cell activation syndromes and indolent systemic mastocytosis without skin involvement are two emerging entities that sometimes might be clinically difficult to distinguish, and they involve a great challenge for the physician from both a diagnostic and a therapeutic point of view. Furthermore, final diagnosis of both entities requires a bone marrow study; it is recommended that this be done in reference centers. In this article, we address the current consensus and guidelines for the suspicion, diagnosis, classification, treatment, and management of these two entities.

Anaplastic sarcoma of the kidney.

PubMed

Labanaris, Apostolos; Zugor, Vahudin; Smiszek, Robert; Nützel, Reinhold; Kühn, Reinhard

2009-02-15

Wilms tumor can appear with a wide spectrum of morphologic features and can sometimes cover or delay the recognition of other clinicopathologic entities of the kidney. We present a case of a new tumor entity of the kidney, namely the anaplastic sarcoma of the kidney, a tumor of high malignancy.

Cholangiocarcinoma: classification, diagnosis, staging, imaging features, and management.

PubMed

Oliveira, Irai S; Kilcoyne, Aoife; Everett, Jamie M; Mino-Kenudson, Mari; Harisinghani, Mukesh G; Ganesan, Karthik

2017-06-01

Cholangiocarcinoma is a relatively uncommon malignant neoplasm with poor prognosis. The distinction between extrahepatic and intrahepatic subtypes is important as epidemiological features, biologic and pathologic characteristics, and clinical course are different for both entities. This review study focuses on the role imaging plays in the diagnosis, classification, staging, and post-treatment assessment of cholangiocarcinoma.

12 CFR 1229.2 - Determination of a Bank's capital classification.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 12 Banks and Banking 7 2010-01-01 2010-01-01 false Determination of a Bank's capital classification. 1229.2 Section 1229.2 Banks and Banking FEDERAL HOUSING FINANCE AGENCY ENTITY REGULATIONS CAPITAL... than the minimum required under this paragraph or make a determination for one or more Banks without...

78 FR 60378 - Request for Applications for the IRS Advisory Committee on Tax Exempt and Government Entities

Federal Register 2010, 2011, 2012, 2013, 2014

2013-10-01

... letter with the following information: Name; Other Name(s) Used and Date(s) (required for FBI check); Date of Birth (required for FBI check); City and State of Birth (required for FBI Check); Current..., among other things, pre-appointment and annual tax checks, and an FBI criminal and subversive name check...

Discussion: Imagining the Languaged Worker's Language

ERIC Educational Resources Information Center

Urciuoli, Bonnie

2016-01-01

What people perceive as "a language"--a named entity--is abstracted from practices and notions about those practices. People take for granted that language is somehow a "thing," an objectively distinct and bounded entity. How languages come to be thus imagined indexes the conditions under which they are imagined. The articles…

24 CFR 202.5 - General approval standards.

Code of Federal Regulations, 2011 CFR

2011-04-01

... years from the date that the materials are circulated or used to advertise. (3) Non-FHA-approved entities. A lender or mortgagee that accepts a loan application from a non-FHA-approved entity must confirm..., including, but not limited to, mergers, terminations, name, location, control of ownership, and character of...

24 CFR 202.5 - General approval standards.

Code of Federal Regulations, 2013 CFR

2013-04-01

... years from the date that the materials are circulated or used to advertise. (3) Non-FHA-approved entities. A lender or mortgagee that accepts a loan application from a non-FHA-approved entity must confirm..., including, but not limited to, mergers, terminations, name, location, control of ownership, and character of...

24 CFR 202.5 - General approval standards.

Code of Federal Regulations, 2012 CFR

2012-04-01

... years from the date that the materials are circulated or used to advertise. (3) Non-FHA-approved entities. A lender or mortgagee that accepts a loan application from a non-FHA-approved entity must confirm..., including, but not limited to, mergers, terminations, name, location, control of ownership, and character of...

49 CFR Appendix C to Part 37 - Certifications

Code of Federal Regulations, 2010 CFR

2010-10-01

..., including individuals who use wheelchairs, is equivalent to the level and quality of service offered to... (name of public entity (ies)) has conducted a survey of existing paratransit services as required by 49... is to certify that service provided by other entities but included in the ADA paratransit plan...

Abstracts versus Full Texts and Patents: A Quantitative Analysis of Biomedical Entities

NASA Astrophysics Data System (ADS)

Müller, Bernd; Klinger, Roman; Gurulingappa, Harsha; Mevissen, Heinz-Theodor; Hofmann-Apitius, Martin; Fluck, Juliane; Friedrich, Christoph M.

In information retrieval, named entity recognition gives the opportunity to apply semantic search in domain specific corpora. Recently, more full text patents and journal articles became freely available. As the information distribution amongst the different sections is unknown, an analysis of the diversity is of interest.

77 FR 48609 - Additional Designations, Foreign Narcotics Kingpin Designation Act

Federal Register 2010, 2011, 2012, 2013, 2014

2012-08-14

... the names of three individuals and five entities whose property and interests in property have been... designation by the Director of OFAC of the three individuals and five entities identified in this notice... transactions involving U.S. companies and individuals. The Kingpin Act blocks all property and interests in...

22 CFR 96.32 - Internal structure and oversight.

Code of Federal Regulations, 2011 CFR

2011-04-01

... known, under either its current or any former form of organization, and the addresses and phone numbers used when such names were used; (2) The name, address, and phone number of each current director... number of such other provider; and (3) The name, address, and phone number of any entity it uses or...

22 CFR 96.32 - Internal structure and oversight.

Code of Federal Regulations, 2012 CFR

2012-04-01

... known, under either its current or any former form of organization, and the addresses and phone numbers used when such names were used; (2) The name, address, and phone number of each current director... number of such other provider; and (3) The name, address, and phone number of any entity it uses or...

22 CFR 96.32 - Internal structure and oversight.

Code of Federal Regulations, 2014 CFR

2014-04-01

... known, under either its current or any former form of organization, and the addresses and phone numbers used when such names were used; (2) The name, address, and phone number of each current director... number of such other provider; and (3) The name, address, and phone number of any entity it uses or...

22 CFR 96.32 - Internal structure and oversight.

Code of Federal Regulations, 2013 CFR

2013-04-01

... known, under either its current or any former form of organization, and the addresses and phone numbers used when such names were used; (2) The name, address, and phone number of each current director... number of such other provider; and (3) The name, address, and phone number of any entity it uses or...

30 CFR 1218.540 - How does ONRR serve official correspondence?

Code of Federal Regulations, 2014 CFR

2014-07-01

... reporting entity is responsible for notifying ONRR of any name or address changes on Form ONRR-4444. The... name and address, position title, or department name and address in our database, based on previous... registered agent; (ii) Any corporate officer; or (iii) The addressee of record shown in the files of any...

A Concept Hierarchy Based Ontology Mapping Approach

NASA Astrophysics Data System (ADS)

Wang, Ying; Liu, Weiru; Bell, David

Ontology mapping is one of the most important tasks for ontology interoperability and its main aim is to find semantic relationships between entities (i.e. concept, attribute, and relation) of two ontologies. However, most of the current methods only consider one to one (1:1) mappings. In this paper we propose a new approach (CHM: Concept Hierarchy based Mapping approach) which can find simple (1:1) mappings and complex (m:1 or 1:m) mappings simultaneously. First, we propose a new method to represent the concept names of entities. This method is based on the hierarchical structure of an ontology such that each concept name of entity in the ontology is included in a set. The parent-child relationship in the hierarchical structure of an ontology is then extended as a set-inclusion relationship between the sets for the parent and the child. Second, we compute the similarities between entities based on the new representation of entities in ontologies. Third, after generating the mapping candidates, we select the best mapping result for each source entity. We design a new algorithm based on the Apriori algorithm for selecting the mapping results. Finally, we obtain simple (1:1) and complex (m:1 or 1:m) mappings. Our experimental results and comparisons with related work indicate that utilizing this method in dealing with ontology mapping is a promising way to improve the overall mapping results.

Multi-dimensionality and variability in folk classification of stingless bees (Apidae: Meliponini).

PubMed

Zamudio, Fernando; Hilgert, Norma I

2015-05-23

Not long ago Eugene Hunn suggested using a combination of cognitive, linguistic, ecological and evolutionary theories in order to account for the dynamic character of ethnoecology in the study of folk classification systems. In this way he intended to question certain homogeneity in folk classifications models and deepen in the analysis and interpretation of variability in folk classifications. This paper studies how a rural culturally mixed population of the Atlantic Forest of Misiones (Argentina) classified honey-producing stingless bees according to the linguistic, cognitive and ecological dimensions of folk classification. We also analyze the socio-ecological meaning of binomialization in naming and the meaning of general local variability in the appointment of stingless bees. We used three different approaches: the classical approach developed by Brent Berlin which relies heavily on linguistic criteria, the approach developed by Eleonor Rosch which relies on psychological (cognitive) principles of categorization and finally we have captured the ecological dimension of folk classification in local narratives. For the second approximation, we developed ways of measuring the degree of prototypicality based on a total of 107 comparisons of the type "X is similar to Y" identified in personal narratives. Various logical and grouping strategies coexist and were identified as: graded of lateral linkage, hierarchical and functional. Similarity judgments among folk taxa resulted in an implicit logic of classification graded according to taxa's prototypicality. While there is a high agreement on naming stingless bees with monomial names, a considerable number of underrepresented binomial names and lack of names were observed. Two possible explanations about reported local naming variability are presented. We support the multidimensionality of folk classification systems. This confirms the specificity of local classification systems but also reflects the use of grouping strategies and mechanisms commonly observed in other cultural groups, such as the use of similarity judgments between more or less prototypical organisms. Also we support the idea that alternative naming results from a process of fragmentation of knowledge or incomplete transmission of knowledge. These processes lean on the facts that culturally based knowledge, on the one hand, and biologic knowledge of nature on the other, can be acquired through different learning pathways.

SPECTRa-T: machine-based data extraction and semantic searching of chemistry e-theses.

PubMed

Downing, Jim; Harvey, Matt J; Morgan, Peter B; Murray-Rust, Peter; Rzepa, Henry S; Stewart, Diana C; Tonge, Alan P; Townsend, Joe A

2010-02-22

The SPECTRa-T project has developed text-mining tools to extract named chemical entities (NCEs), such as chemical names and terms, and chemical objects (COs), e.g., experimental spectral assignments and physical chemistry properties, from electronic theses (e-theses). Although NCEs were readily identified within the two major document formats studied, only the use of structured documents enabled identification of chemical objects and their association with the relevant chemical entity (e.g., systematic chemical name). A corpus of theses was analyzed and it is shown that a high degree of semantic information can be extracted from structured documents. This integrated information has been deposited in a persistent Resource Description Framework (RDF) triple-store that allows users to conduct semantic searches. The strength and weaknesses of several document formats are reviewed.

77 FR 44717 - Unblocking of Specially Designated Nationals and Blocked Persons Pursuant to the Foreign...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-07-30

... Foreign Assets Control (``OFAC'') is publishing the names of ten individuals and nine entities whose... ten individuals and nine entities identified in this notice whose property and interests in property... international narcotics trafficking. On July 24, 2012, the Director of OFAC removed from the SDN List the ten...

78 FR 37664 - Identification of Entities Pursuant to the Iranian Transactions and Sanctions Regulations and...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-06-21

... Control (``OFAC'') is publishing the names of 38 entities identified as the Government of Iran under the... Government of Iran and Iranian Financial Institutions'' (the ``Order''). Section 1(a) of the Order blocks, with certain exceptions, all property and interests in property of the Government of Iran, including...

78 FR 78514 - Designation of One Individual and Three Entities Pursuant to Executive Order

Federal Register 2010, 2011, 2012, 2013, 2014

2013-12-26

... DEPARTMENT OF THE TREASURY Office of Foreign Assets Control Designation of One Individual and... publishing the name of one individual and three entities whose property and interests in property are blocked..., Security, or Stability of Burma.'' DATES: The designation by the Director of OFAC of the one individual and...

18 CFR 131.31 - FERC Form No. 561, Annual report of interlocking positions.

Code of Federal Regulations, 2010 CFR

2010-04-01

... supplies electric equipment (ELEQ) named in Column (3) enter the aggregate amount of revenues from... utility ELEQ Entity which produces/supplies electric equipment for the use of any public utility FUEL Entity which produces/supplies coal, natural gas, nuclear fuel, or other fuel for the use of any public...

Named Entity Recognition in Chinese Clinical Text Using Deep Neural Network.

PubMed

Wu, Yonghui; Jiang, Min; Lei, Jianbo; Xu, Hua

2015-01-01

Rapid growth in electronic health records (EHRs) use has led to an unprecedented expansion of available clinical data in electronic formats. However, much of the important healthcare information is locked in the narrative documents. Therefore Natural Language Processing (NLP) technologies, e.g., Named Entity Recognition that identifies boundaries and types of entities, has been extensively studied to unlock important clinical information in free text. In this study, we investigated a novel deep learning method to recognize clinical entities in Chinese clinical documents using the minimal feature engineering approach. We developed a deep neural network (DNN) to generate word embeddings from a large unlabeled corpus through unsupervised learning and another DNN for the NER task. The experiment results showed that the DNN with word embeddings trained from the large unlabeled corpus outperformed the state-of-the-art CRF's model in the minimal feature engineering setting, achieving the highest F1-score of 0.9280. Further analysis showed that word embeddings derived through unsupervised learning from large unlabeled corpus remarkably improved the DNN with randomized embedding, denoting the usefulness of unsupervised feature learning.

Hereditary and non-hereditary microangiopathies in the young. An up-date.

PubMed

Ringelstein, E Bernd; Kleffner, Ilka; Dittrich, Ralf; Kuhlenbäumer, Gregor; Ritter, Martin A

2010-12-15

In recent years, a considerable number of new sporadic or hereditary small artery diseases of the brain have been detected which preferably occur in younger age, below 45 years. Cerebral microangiopathies constitute an appreciable portion of all strokes. In middle aged patients, hereditary cerebral small vessel diseases have to be separated from sporadic degenerative cerebral microangiopathy which is mainly due to a high vascular risk load. Features of the following disorders and details how to differentiate them, are reviewed here, namely CADASIL, MELAS, AD-RVLC, HEMID, CARASIL, PADMAL, FABRY, COL4A1-related cerebral small vessel diseases and a Portuguese type of autosomal dominant cerebral small vessel disease (SVDB). The symptomatic overlap of the cerebral microangiopathies include also other distinctive non-hereditary diseases like posterior (reversible) encephalopathy and Susac's syndrome which are also described. Some of the microangiopathies described here are not only seen in the young but also in the elderly. The precise diagnosis has direct therapeutic implications in several of these entities. Cerebral microangiopathies cause recurring strokes and diffuse white matter lesions leading to a broad spectrum of gait disturbances and in most of these disorders cognitive impairment or even vascular dementia in the long term. Often, they also involve the eye, the inner ear or the kidney. Several typical imaging findings from illustrative cases are presented. The order in which these diseases are presented here is not dictated by an inner logic principle, because a genetically or pathophysiologically based classification system of all these entities does not exist yet. Some entities are well established and not unusual, whereas others have only been described in a few cases in total. Copyright © 2010 Elsevier B.V. All rights reserved.

Classifying Web Pages by Using Knowledge Bases for Entity Retrieval

NASA Astrophysics Data System (ADS)

Kiritani, Yusuke; Ma, Qiang; Yoshikawa, Masatoshi

In this paper, we propose a novel method to classify Web pages by using knowledge bases for entity search, which is a kind of typical Web search for information related to a person, location or organization. First, we map a Web page to entities according to the similarities between the page and the entities. Various methods for computing such similarity are applied. For example, we can compute the similarity between a given page and a Wikipedia article describing a certain entity. The frequency of an entity appearing in the page is another factor used in computing the similarity. Second, we construct a directed acyclic graph, named PEC graph, based on the relations among Web pages, entities, and categories, by referring to YAGO, a knowledge base built on Wikipedia and WordNet. Finally, by analyzing the PEC graph, we classify Web pages into categories. The results of some preliminary experiments validate the methods proposed in this paper.

12 CFR 204.130 - Eligibility for NOW accounts.

Code of Federal Regulations, 2010 CFR

2010-01-01

... clarify the types of entities that may maintain NOW accounts at member banks. (b) Individuals. (1) Any individual may maintain a NOW account regardless of the purposes that the funds will serve. Thus, deposits of... under a trade name is eligible to maintain a NOW account in the individual's name or in the “DBA” name...

30 CFR 1218.540 - How does ONRR serve official correspondence?

Code of Federal Regulations, 2012 CFR

2012-07-01

... correspondence at issue. The company or reporting entity is responsible for notifying ONRR of any name or address changes on Form MMS-4444. The addressee of record in a part 1290, appeal will be the person or...-4444, we may use the individual name and address, position title, or department name and address in our...

30 CFR 1218.540 - How does ONRR serve official correspondence?

Code of Federal Regulations, 2013 CFR

2013-07-01

... correspondence at issue. The company or reporting entity is responsible for notifying ONRR of any name or address changes on Form ONRR-4444. The addressee of record in a part 1290, appeal will be the person or...-4444, we may use the individual name and address, position title, or department name and address in our...

Galeata: chronic migraine independently considered in a medieval headache classification.

PubMed

Guerrero-Peral, Angel Luís; de Frutos González, Virginia; Pedraza-Hueso, María Isabel

2014-03-21

Chronic migraine is a quite recent concept. However, there are descriptions suggestive of episodic migraine since the beginning of scientific medicine. We aim to review main headache classifications during Classical antiquity and compared them with that proposed in the 11th century by Constantine the African in his Liber Pantegni, one of the most influential texts in medieval medicine. We have carried out a descriptive review of Henricum Petrum's Latin edition, year 1539. Headache classifications proposed by Aretaeus of Cappadocia, Galen of Pergamun and Alexander of Tralles, all of them classifying headaches into three main types, considered an entity (called Heterocrania or Hemicrania), comparable to contemporary episodic migraine.In ninth book of Liber Pantegni, headaches were also classified into three types and one of them, Galeata, consisted on a chronic pain of mild intensity with occasional superimposed exacerbations. In Liber Pantegni we have firstly identified, as a separate entity, a headache comparable to that we currently define as chronic migraine: Galeata.

Galeata: chronic migraine independently considered in a medieval headache classification

PubMed Central

2014-01-01

Background Chronic migraine is a quite recent concept. However, there are descriptions suggestive of episodic migraine since the beginning of scientific medicine. We aim to review main headache classifications during Classical antiquity and compared them with that proposed in the 11th century by Constantine the African in his Liber Pantegni, one of the most influential texts in medieval medicine. Method We have carried out a descriptive review of Henricum Petrum's Latin edition, year 1539. Results Headache classifications proposed by Aretaeus of Cappadocia, Galen of Pergamun and Alexander of Tralles, all of them classifying headaches into three main types, considered an entity (called Heterocrania or Hemicrania), comparable to contemporary episodic migraine. In ninth book of Liber Pantegni, headaches were also classified into three types and one of them, Galeata, consisted on a chronic pain of mild intensity with occasional superimposed exacerbations. Conclusion In Liber Pantegni we have firstly identified, as a separate entity, a headache comparable to that we currently define as chronic migraine: Galeata. PMID:24655582

Sieve-based coreference resolution enhances semi-supervised learning model for chemical-induced disease relation extraction.

PubMed

Le, Hoang-Quynh; Tran, Mai-Vu; Dang, Thanh Hai; Ha, Quang-Thuy; Collier, Nigel

2016-07-01

The BioCreative V chemical-disease relation (CDR) track was proposed to accelerate the progress of text mining in facilitating integrative understanding of chemicals, diseases and their relations. In this article, we describe an extension of our system (namely UET-CAM) that participated in the BioCreative V CDR. The original UET-CAM system's performance was ranked fourth among 18 participating systems by the BioCreative CDR track committee. In the Disease Named Entity Recognition and Normalization (DNER) phase, our system employed joint inference (decoding) with a perceptron-based named entity recognizer (NER) and a back-off model with Semantic Supervised Indexing and Skip-gram for named entity normalization. In the chemical-induced disease (CID) relation extraction phase, we proposed a pipeline that includes a coreference resolution module and a Support Vector Machine relation extraction model. The former module utilized a multi-pass sieve to extend entity recall. In this article, the UET-CAM system was improved by adding a 'silver' CID corpus to train the prediction model. This silver standard corpus of more than 50 thousand sentences was automatically built based on the Comparative Toxicogenomics Database (CTD) database. We evaluated our method on the CDR test set. Results showed that our system could reach the state of the art performance with F1 of 82.44 for the DNER task and 58.90 for the CID task. Analysis demonstrated substantial benefits of both the multi-pass sieve coreference resolution method (F1 + 4.13%) and the silver CID corpus (F1 +7.3%).Database URL: SilverCID-The silver-standard corpus for CID relation extraction is freely online available at: https://zenodo.org/record/34530 (doi:10.5281/zenodo.34530). © The Author(s) 2016. Published by Oxford University Press.

Knowledge Management in Taxonomy and Biostratigraphy using TaxonConcept Software

NASA Astrophysics Data System (ADS)

Klump, J.; Huber, R.; Goetz, S.

2005-12-01

The use of fossils to constrain age models for geological samples is not as straightforward as it might seem. Even though index fossils have been defined as biostratigraphic time markers ambiguity arises from the synonymous use of taxonomic names. Progress in our understanding of the origin of certain species have sometimes lead to substantial changes in the taxonomic classification of these organisms. TaxonConcept was created as part of the Stratigraphy.net initiative as a tool to manage taxonomic information and complex knowledge networks to help resolve taxonomic ambiguities in biostratigraphy. Its workflow is based on the principles of open nomenclature. Open nomenclature allows researchers to comment on the identification of a specimen which cannot exactly be determined and is frequently used in synonymy lists. The use of such synonymy lists in TaxonConcept allows to work with taxonomic classifications that are uncertain, or where several versions exist. Every single taxonomic entity in TaxonConcept is recorded with its relevant citations in the literature. This allows to manage information on taxonomy. The members of working groups using TaxonConcept can record their opinion on the taxonomic classification of each taxon in the framework of open nomenclature and annotate it in free text. This managed and structured collection of taxonomic opinions is an example of knowledge management. Taxonomic opinions are otherwise dispersed throughout the literature, if recorded at all, and are only available to the specialist. Assembled as a collection, they represent our knowledge on the taxonomy of a certain group of organisms. In the terminology of computer science, the semantic relationships between taxonomic terms are an ontology. Open nomenclature offers a formal framework that lends itself very well to describe the nature of the relations between taxonomic terms. The use of such synonymy lists in a taxonomic information system allows interesting search options, ranging from tracking name changes to the investigation of complex taxonomic topologies. In addition to its synonymy and literature management, TaxonConcept allows to store many other information categories such as textual descriptions (e.g. diagnoses and comments), images, bioevents and specimen and collection data. Ecological information is scheduled for a later stage of the project. Already now TaxonConcept is linked to taxon names in paleoenvironmental data of the World Data Center for Marine Environmental Sciences (WDC-MARE), interfaces to other databases are planned. WDC-MARE stores environmental, marine and geological research data and frequently uses taxon names in its parameters. By linking TaxonConcept and WDC-MARE, synonymous names can be included in queries, e.g. when researching for stable isotope data measured on microfossils. TaxonConcept is not a project on authoritative taxonomic information, but is a tool for taxonomic projects to use to find a taxonomic consensus, e.g. to define a taxonomic framework for biostratigraphic studies. Both, the project specific hierarchical classification of selected taxa, as well as a project specific selection of any other information categories is supported by TaxonConcept. The results of such a taxonomic consensus can be used to create Fossilium Catalogus style summaries in various output formats which can later be used to create online or print publications.

A New Classification of the Dictyostelids.

PubMed

Sheikh, Sanea; Thulin, Mats; Cavender, James C; Escalante, Ricardo; Kawakami, Shin-Ichi; Lado, Carlos; Landolt, John C; Nanjundiah, Vidyanand; Queller, David C; Strassmann, Joan E; Spiegel, Frederick W; Stephenson, Steven L; Vadell, Eduardo M; Baldauf, Sandra L

2018-02-01

Traditional morphology-based taxonomy of dictyostelids is rejected by molecular phylogeny. A new classification is presented based on monophyletic entities with consistent and strong molecular phylogenetic support and that are, as far as possible, morphologically recognizable. All newly named clades are diagnosed with small subunit ribosomal RNA (18S rRNA) sequence signatures plus morphological synapomorphies where possible. The two major molecular clades are given the rank of order, as Acytosteliales ord. nov. and Dictyosteliales. The two major clades within each of these orders are recognized and given the rank of family as, respectively, Acytosteliaceae and Cavenderiaceae fam. nov. in Acytosteliales, and Dictyosteliaceae and Raperosteliaceae fam. nov. in Dictyosteliales. Twelve genera are recognized: Cavenderia gen. nov. in Cavenderiaceae, Acytostelium, Rostrostelium gen. nov. and Heterostelium gen. nov. in Acytosteliaceae, Tieghemostelium gen. nov., Hagiwaraea gen. nov., Raperostelium gen. nov. and Speleostelium gen. nov. in Raperosteliaceae, and Dictyostelium and Polysphondylium in Dictyosteliaceae. The "polycephalum" complex is treated as Coremiostelium gen. nov. (not assigned to family) and the "polycarpum" complex as Synstelium gen. nov. (not assigned to order and family). Coenonia, which may not be a dictyostelid, is treated as a genus incertae sedis. Eighty-eight new combinations are made at species and variety level, and Dictyostelium ammophilum is validated. Copyright © 2017 Elsevier GmbH. All rights reserved.

Chemical-induced disease relation extraction with various linguistic features.

PubMed

Gu, Jinghang; Qian, Longhua; Zhou, Guodong

2016-01-01

Understanding the relations between chemicals and diseases is crucial in various biomedical tasks such as new drug discoveries and new therapy developments. While manually mining these relations from the biomedical literature is costly and time-consuming, such a procedure is often difficult to keep up-to-date. To address these issues, the BioCreative-V community proposed a challenging task of automatic extraction of chemical-induced disease (CID) relations in order to benefit biocuration. This article describes our work on the CID relation extraction task on the BioCreative-V tasks. We built a machine learning based system that utilized simple yet effective linguistic features to extract relations with maximum entropy models. In addition to leveraging various features, the hypernym relations between entity concepts derived from the Medical Subject Headings (MeSH)-controlled vocabulary were also employed during both training and testing stages to obtain more accurate classification models and better extraction performance, respectively. We demoted relation extraction between entities in documents to relation extraction between entity mentions. In our system, pairs of chemical and disease mentions at both intra- and inter-sentence levels were first constructed as relation instances for training and testing, then two classification models at both levels were trained from the training examples and applied to the testing examples. Finally, we merged the classification results from mention level to document level to acquire final relations between chemicals and diseases. Our system achieved promisingF-scores of 60.4% on the development dataset and 58.3% on the test dataset using gold-standard entity annotations, respectively. Database URL:https://github.com/JHnlp/BC5CIDTask. © The Author(s) 2016. Published by Oxford University Press.

Spatial distribution and influence factors of interprovincial terrestrial physical geographical names in China

NASA Astrophysics Data System (ADS)

Zhang, S.; Wang, Y.; Ju, H.

2017-12-01

The interprovincial terrestrial physical geographical entities are the key areas of regional integrated management. Based on toponomy dictionaries and different thematic maps, the attributes and the spatial extent of the interprovincial terrestrial physical geographical names (ITPGN, including terrain ITPGN and water ITPGN) were extracted. The coefficient of variation and Moran's I were combined together to measure the spatial variation and spatial association of ITPGN. The influencing factors of the distribution of ITPGN and the implications for the regional management were further discussed. The results showed that 11325 ITPGN were extracted, including 7082 terrain ITPGN and 4243 water ITPGN. Hunan Province had the largest number of ITPGN in China, and Shanghai had the smallest number. The spatial variance of the terrain ITPGN was larger than that of the water ITPGN, and the ITPGN showed a significant agglomeration phenomenon in the southern part of China. Further analysis showed that the number of ITPGN was positively related with the relative elevation and the population where the relative elevation was lower than 2000m and the population was less than 50 million. But the number of ITPGN showed a negative relationship with the two factors when their values became larger, indicating a large number of unnamed entities existed in complex terrain areas and a decreasing number of terrestrial physical geographical entities in densely populated area. Based on these analysis, we suggest the government take the ITPGN as management units to realize a balance development between different parts of the entities and strengthen the geographical names census and the nomination of unnamed interprovincial physical geographical entities. This study also demonstrated that the methods of literature survey, coefficient of variation and Moran's I can be combined to enhance the understanding of the spatial pattern of ITPGN.

Primary Immunodeficiency Diseases: An Update on the Classification from the International Union of Immunological Societies Expert Committee for Primary Immunodeficiency

PubMed Central

Al-Herz, Waleed; Bousfiha, Aziz; Casanova, Jean-Laurent; Chapel, Helen; Conley, Mary Ellen; Cunningham-Rundles, Charlotte; Etzioni, Amos; Fischer, Alain; Franco, Jose Luis; Geha, Raif S.; Hammarström, Lennart; Nonoyama, Shigeaki; Notarangelo, Luigi Daniele; Ochs, Hans Dieter; Puck, Jennifer M.; Roifman, Chaim M.; Seger, Reinhard; Tang, Mimi L. K.

2011-01-01

We report the updated classification of primary immunodeficiency diseases, compiled by the ad hoc Expert Committee of the International Union of Immunological Societies. As compared to the previous edition, more than 15 novel disease entities have been added in the updated version. For each disorders, the key clinical and laboratory features are provided. This updated classification is meant to help in the diagnostic approach to patients with these diseases. PMID:22566844

Soil geomorphic classification, soil taxonomy, and effects on soil richness assessments

Treesearch

Jonathan D. Phillips; Daniel A. Marion

2007-01-01

The study of pedodiversity and soil richness depends on the notion of soils as discrete entities. Soil classifications are often criticized in this regard because they depend in part on arbitrary or subjective criteria. In this study soils were categorized on the basis of the presence or absence of six lithological and morphological characteristics. Richness vs. area...

Demonstration of Advanced EMI Models for Live-Site UXO Discrimination at Former Camp Butner, North Carolina

DTIC Science & Technology

2012-05-01

GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT NUMBER 5e. TASK NUMBER 5f. WORK UNIT NUMBER 7 . PERFORMING ORGANIZATION NAME(S...2.3.3 Classification using template matching ...................................................... 7 2.4 Details of classification schemes... 7 2.4.1 Camp Butner TEMTADS data inversion and classification scheme .......... 9

Enhancing of chemical compound and drug name recognition using representative tag scheme and fine-grained tokenization.

PubMed

Dai, Hong-Jie; Lai, Po-Ting; Chang, Yung-Chun; Tsai, Richard Tzong-Han

2015-01-01

The functions of chemical compounds and drugs that affect biological processes and their particular effect on the onset and treatment of diseases have attracted increasing interest with the advancement of research in the life sciences. To extract knowledge from the extensive literatures on such compounds and drugs, the organizers of BioCreative IV administered the CHEMical Compound and Drug Named Entity Recognition (CHEMDNER) task to establish a standard dataset for evaluating state-of-the-art chemical entity recognition methods. This study introduces the approach of our CHEMDNER system. Instead of emphasizing the development of novel feature sets for machine learning, this study investigates the effect of various tag schemes on the recognition of the names of chemicals and drugs by using conditional random fields. Experiments were conducted using combinations of different tokenization strategies and tag schemes to investigate the effects of tag set selection and tokenization method on the CHEMDNER task. This study presents the performance of CHEMDNER of three more representative tag schemes-IOBE, IOBES, and IOB12E-when applied to a widely utilized IOB tag set and combined with the coarse-/fine-grained tokenization methods. The experimental results thus reveal that the fine-grained tokenization strategy performance best in terms of precision, recall and F-scores when the IOBES tag set was utilized. The IOBES model with fine-grained tokenization yielded the best-F-scores in the six chemical entity categories other than the "Multiple" entity category. Nonetheless, no significant improvement was observed when a more representative tag schemes was used with the coarse or fine-grained tokenization rules. The best F-scores that were achieved using the developed system on the test dataset of the CHEMDNER task were 0.833 and 0.815 for the chemical documents indexing and the chemical entity mention recognition tasks, respectively. The results herein highlight the importance of tag set selection and the use of different tokenization strategies. Fine-grained tokenization combined with the tag set IOBES most effectively recognizes chemical and drug names. To the best of the authors' knowledge, this investigation is the first comprehensive investigation use of various tag set schemes combined with different tokenization strategies for the recognition of chemical entities.

78 FR 39021 - Privacy Act of 1974; Privacy and Civil Liberties Oversight Board; System of Records Notice

Federal Register 2010, 2011, 2012, 2013, 2014

2013-06-28

... requests or appeals on behalf of other persons or entities; individuals who are the subjects of FOIA or PA... number) information, and proof of identification; names and other information about persons who are the... oversight function. E. To appropriate agencies, entities, and persons when: 1. The Board suspects or has...

21 CFR 203.30 - Sample distribution by mail or common carrier.

Code of Federal Regulations, 2011 CFR

2011-04-01

... pharmacy of a hospital or other health care entity, by mail or common carrier, provided that: (1) The... to the pharmacy of a hospital or other health care entity is required to contain, in addition to all of the information in paragraph (b)(l) of this section, the name and address of the pharmacy of the...

21 CFR 203.30 - Sample distribution by mail or common carrier.

Code of Federal Regulations, 2013 CFR

2013-04-01

... pharmacy of a hospital or other health care entity, by mail or common carrier, provided that: (1) The... to the pharmacy of a hospital or other health care entity is required to contain, in addition to all of the information in paragraph (b)(l) of this section, the name and address of the pharmacy of the...

21 CFR 203.30 - Sample distribution by mail or common carrier.

Code of Federal Regulations, 2012 CFR

2012-04-01

... pharmacy of a hospital or other health care entity, by mail or common carrier, provided that: (1) The... to the pharmacy of a hospital or other health care entity is required to contain, in addition to all of the information in paragraph (b)(l) of this section, the name and address of the pharmacy of the...

21 CFR 203.30 - Sample distribution by mail or common carrier.

Code of Federal Regulations, 2014 CFR

2014-04-01

... pharmacy of a hospital or other health care entity, by mail or common carrier, provided that: (1) The... to the pharmacy of a hospital or other health care entity is required to contain, in addition to all of the information in paragraph (b)(l) of this section, the name and address of the pharmacy of the...

78 FR 38537 - Federal Acquisition Regulation; Federal Acquisition Circular 2005-68; Small Entity Compliance Guide

Federal Register 2010, 2011, 2012, 2013, 2014

2013-06-26

... Entity Compliance Guide. SUMMARY: This document is issued under the joint authority of DOD, GSA, and NASA... whose name appears in the table below. Please cite FAC 2005-68 and the FAR case number. For information... Listed in FAC 2005-68 Subject FAR Case Analyst *Expansion of Applicability of the Senior Executive...

[Nonspecific interstitial pneumonitis: a clinicopathologic entity, histologic pattern or unclassified group of heterogeneous interstitial pneumonitis?].

PubMed

Morais, António; Moura, M Conceição Souto; Cruz, M Rosa; Gomes, Isabel

2004-01-01

Nonspecific interstitial pneumonitis (NSIP) initially described by Katzenstein and Fiorelli in 1994, seems to be a distinct clinicopathologic entity among idiopathic interstitial pneumonitis (IIP). Besides different histologic features from other IIP, NSIP is characterized by a better long-term outcome, associated with a better steroids responsiveness than idiopathic pulmonar fibrosis (IPF), where usually were included. Thus, differentiating NSIP from other IIP, namely IPF is very significant, since it has important therapeutic and prognostic implications. NSIP encloses different pathologies, namely those with inflammatory predominance (cellular subtype) or fibrous predominance (fibrosing subtype). NSIP is reviewed and discussed by the authors, after two clinical cases description.

LBMD : a layer-based mesh data structure tailored for generic API infrastructures.

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

Ebeida, Mohamed S.; Knupp, Patrick Michael

2010-11-01

A new mesh data structure is introduced for the purpose of mesh processing in Application Programming Interface (API) infrastructures. This data structure utilizes a reduced mesh representation to increase its ability to handle significantly larger meshes compared to full mesh representation. In spite of the reduced representation, each mesh entity (vertex, edge, face, and region) is represented using a unique handle, with no extra storage cost, which is a crucial requirement in most API libraries. The concept of mesh layers makes the data structure more flexible for mesh generation and mesh modification operations. This flexibility can have a favorable impactmore » in solver based queries of finite volume and multigrid methods. The capabilities of LBMD make it even more attractive for parallel implementations using Message Passing Interface (MPI) or Graphics Processing Units (GPUs). The data structure is associated with a new classification method to relate mesh entities to their corresponding geometrical entities. The classification technique stores the related information at the node level without introducing any ambiguities. Several examples are presented to illustrate the strength of this new data structure.« less

An attention-based BiLSTM-CRF approach to document-level chemical named entity recognition.

PubMed

Luo, Ling; Yang, Zhihao; Yang, Pei; Zhang, Yin; Wang, Lei; Lin, Hongfei; Wang, Jian

2018-04-15

In biomedical research, chemical is an important class of entities, and chemical named entity recognition (NER) is an important task in the field of biomedical information extraction. However, most popular chemical NER methods are based on traditional machine learning and their performances are heavily dependent on the feature engineering. Moreover, these methods are sentence-level ones which have the tagging inconsistency problem. In this paper, we propose a neural network approach, i.e. attention-based bidirectional Long Short-Term Memory with a conditional random field layer (Att-BiLSTM-CRF), to document-level chemical NER. The approach leverages document-level global information obtained by attention mechanism to enforce tagging consistency across multiple instances of the same token in a document. It achieves better performances with little feature engineering than other state-of-the-art methods on the BioCreative IV chemical compound and drug name recognition (CHEMDNER) corpus and the BioCreative V chemical-disease relation (CDR) task corpus (the F-scores of 91.14 and 92.57%, respectively). Data and code are available at https://github.com/lingluodlut/Att-ChemdNER. yangzh@dlut.edu.cn or wangleibihami@gmail.com. Supplementary data are available at Bioinformatics online.

Relationship of Psoriatic Arthritis to Other Spondyloarthritides.

PubMed

Olivieri, Ignazio; D'Angelo, Salvatore; Gilio, Michele; Palazzi, Carlo; Lubrano, Ennio; Padula, Angela

2015-11-01

In the early 1970s, Moll and co-workers formulated the unified concept of spondyloarthritides, a group of conditions sharing similar clinical features. Subsequently, criteria for their classification have been proposed by Amor and coworkers, the European Spondylarthropathy Study Group, and the Assessment in SpondyloArthritis international Society. Opinion, however, is divided between those who believe that the different entities of the complex represent the variable expression of the same disease ("lumpers") and those who think that these should be considered separately but under the same umbrella ("splitters"). Several sets of criteria have been proposed for psoriatic arthritis (PsA), the most recent being the ClASsification for Psoriatic Arthritis (CASPAR) criteria. According to some authors, there are persuasive arguments to support the view of PsA as a distinct entity.

77 FR 63217 - Use of Additional Portable Oxygen Concentrators on Board Aircraft

Federal Register 2010, 2011, 2012, 2013, 2014

2012-10-16

..., organizations, and governmental jurisdictions subject to regulation. To achieve this principle, agencies are... small entities, including small businesses, not-for-profit organizations, and small governmental... manufacturer's names. In this final rule, the FAA will add those previous manufacturer's names (International...

Independent Assessment Plan: LAV-25

DTIC Science & Technology

1989-06-27

Pages. Enter the total Block 7. Performing Organization Name(s) and number of pages. Address(es. Self -explanatory. Block 16. Price Code, Enter...organization Blocks 17. - 19. Security Classifications. performing the report. Self -explanatory. Enter U.S. Security Classification in accordance with U.S...Security Block 9. S oonsorina/Monitoring Acenc Regulations (i.e., UNCLASSIFIED). If form .Names(s) and Address(es). Self -explanatory. contains classified

Identification of Novel Functional Inhibitors of Acid Sphingomyelinase

PubMed Central

Trapp, Stefan; Pechmann, Stefanie; Friedl, Astrid; Reichel, Martin; Mühle, Christiane; Terfloth, Lothar; Groemer, Teja W.; Spitzer, Gudrun M.; Liedl, Klaus R.; Gulbins, Erich; Tripal, Philipp

2011-01-01

We describe a hitherto unknown feature for 27 small drug-like molecules, namely functional inhibition of acid sphingomyelinase (ASM). These entities named FIASMAs (Functional Inhibitors of Acid SphingoMyelinAse), therefore, can be potentially used to treat diseases associated with enhanced activity of ASM, such as Alzheimer's disease, major depression, radiation- and chemotherapy-induced apoptosis and endotoxic shock syndrome. Residual activity of ASM measured in the presence of 10 µM drug concentration shows a bimodal distribution; thus the tested drugs can be classified into two groups with lower and higher inhibitory activity. All FIASMAs share distinct physicochemical properties in showing lipophilic and weakly basic properties. Hierarchical clustering of Tanimoto coefficients revealed that FIASMAs occur among drugs of various chemical scaffolds. Moreover, FIASMAs more frequently violate Lipinski's Rule-of-Five than compounds without effect on ASM. Inhibition of ASM appears to be associated with good permeability across the blood-brain barrier. In the present investigation, we developed a novel structure-property-activity relationship by using a random forest-based binary classification learner. Virtual screening revealed that only six out of 768 (0.78%) compounds of natural products functionally inhibit ASM, whereas this inhibitory activity occurs in 135 out of 2028 (6.66%) drugs licensed for medical use in humans. PMID:21909365

46 CFR 520.3 - Publication responsibilities.

Code of Federal Regulations, 2013 CFR

2013-10-01

... tariff, of its organization name, organization number, home office address, name and telephone number of... tariffs, by electronically submitting Form FMC-1 via the Commission's website at www.fmc.gov. Any changes... unique organization number to new entities operating as common carriers or conferences in the U.S...

46 CFR 520.3 - Publication responsibilities.

Code of Federal Regulations, 2014 CFR

2014-10-01

... tariff, of its organization name, organization number, home office address, name and telephone number of... tariffs, by electronically submitting Form FMC-1 via the Commission's website at www.fmc.gov. Any changes... unique organization number to new entities operating as common carriers or conferences in the U.S...

46 CFR 520.3 - Publication responsibilities.

Code of Federal Regulations, 2011 CFR

2011-10-01

... tariff, of its organization name, organization number, home office address, name and telephone number of... tariffs, by electronically submitting Form FMC-1 via the Commission's website at www.fmc.gov. Any changes... unique organization number to new entities operating as common carriers or conferences in the U.S...

46 CFR 520.3 - Publication responsibilities.

Code of Federal Regulations, 2012 CFR

2012-10-01

... tariff, of its organization name, organization number, home office address, name and telephone number of... tariffs, by electronically submitting Form FMC-1 via the Commission's website at www.fmc.gov. Any changes... unique organization number to new entities operating as common carriers or conferences in the U.S...

75 FR 18887 - FBI Criminal Justice Information Services Division User Fees

Federal Register 2010, 2011, 2012, 2013, 2014

2010-04-13

.... SUMMARY: This notice establishes the user fee schedule for fingerprint- based and name-based criminal... fingerprint-based and other identification services as authorized by federal law. These fees apply to federal, state and any other authorized entities requesting fingerprint identification records and name checks...

Automatic recognition of disorders, findings, pharmaceuticals and body structures from clinical text: an annotation and machine learning study.

PubMed

Skeppstedt, Maria; Kvist, Maria; Nilsson, Gunnar H; Dalianis, Hercules

2014-06-01

Automatic recognition of clinical entities in the narrative text of health records is useful for constructing applications for documentation of patient care, as well as for secondary usage in the form of medical knowledge extraction. There are a number of named entity recognition studies on English clinical text, but less work has been carried out on clinical text in other languages. This study was performed on Swedish health records, and focused on four entities that are highly relevant for constructing a patient overview and for medical hypothesis generation, namely the entities: Disorder, Finding, Pharmaceutical Drug and Body Structure. The study had two aims: to explore how well named entity recognition methods previously applied to English clinical text perform on similar texts written in Swedish; and to evaluate whether it is meaningful to divide the more general category Medical Problem, which has been used in a number of previous studies, into the two more granular entities, Disorder and Finding. Clinical notes from a Swedish internal medicine emergency unit were annotated for the four selected entity categories, and the inter-annotator agreement between two pairs of annotators was measured, resulting in an average F-score of 0.79 for Disorder, 0.66 for Finding, 0.90 for Pharmaceutical Drug and 0.80 for Body Structure. A subset of the developed corpus was thereafter used for finding suitable features for training a conditional random fields model. Finally, a new model was trained on this subset, using the best features and settings, and its ability to generalise to held-out data was evaluated. This final model obtained an F-score of 0.81 for Disorder, 0.69 for Finding, 0.88 for Pharmaceutical Drug, 0.85 for Body Structure and 0.78 for the combined category Disorder+Finding. The obtained results, which are in line with or slightly lower than those for similar studies on English clinical text, many of them conducted using a larger training data set, show that the approaches used for English are also suitable for Swedish clinical text. However, a small proportion of the errors made by the model are less likely to occur in English text, showing that results might be improved by further tailoring the system to clinical Swedish. The entity recognition results for the individual entities Disorder and Finding show that it is meaningful to separate the general category Medical Problem into these two more granular entity types, e.g. for knowledge mining of co-morbidity relations and disorder-finding relations. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.

Cytogenetics in the management of lymphomas and lymphoproliferative disorders in adults and children: an update by the Groupe francophone de cytogénétique hématologique (GFCH).

PubMed

Lefebvre, Christine; Callet-Bauchu, Evelyne; Chapiro, Elise; Nadal, Nathalie; Penther, Dominique; Poirel, Hélène-Antoine

2016-10-01

Non-Hodgkin's lymphomas and lymphoproliferative disorders include a high number of heterogeneous entities, described in the 2008 WHO classification. This classification reflects the crucial role of a multidisciplinary approach which integrates cytogenetic results both for the notion of clonality and for differential diagnosis between these entities. The prognostic impact of some cytogenetic abnormalities or genome complexity is also confirmed for many of these entities. Novel provisional entities have been described, such as BCLU (B-cell lymphoma unclassifiable with features intermediate between diffuse large B-cell lymphoma and Burkitt lymphoma) for which karyotype is critical to distinguish BCLU from Burkitt's lymphoma. The karyotype can be established from any tumour or liquid infiltrated by lymphoma cells. Recent adaptations of technics for cellular cultures according to the subtype of known (or suspected) lymphoma have significantly improved the percentage of informative karyotypes. Conventional karyotypes remain the best technical approach recommended for most of these subtypes. Interphase and/or metaphase FISH also represents a solid and rapid approach, because of the significant number of recurrent (sometimes specific) rearrangements of these entities. Next generation sequencing technologies contribute to enrich genomic data and substantially improve the understanding of oncogenic mechanisms underlying these lymphoid malignancies. Some molecular biomarkers are already part of the diagnostic process (for example, somatic mutation of MYD88 in Waldenström disease) thus reinforcing the essential principle of a multidisciplinary approach for the diagnosis of all the mature lymphoid malignancies.

31 CFR 535.508 - Payments to blocked accounts in domestic banks.

Code of Federal Regulations, 2010 CFR

2010-07-01

... Iran or any Iranian entity is hereby authorized: Provided, Such payment or transfer shall not be made... the interest of Iran or an Iranian entity to any other country or person. (b) This section does not authorize: (1) Any payment or transfer to any blocked account held in a name other than that of Iran or the...

31 CFR 535.508 - Payments to blocked accounts in domestic banks.

Code of Federal Regulations, 2011 CFR

2011-07-01

... Iran or any Iranian entity is hereby authorized: Provided, Such payment or transfer shall not be made... the interest of Iran or an Iranian entity to any other country or person. (b) This section does not authorize: (1) Any payment or transfer to any blocked account held in a name other than that of Iran or the...

78 FR 80381 - Federal Acquisition Regulation; Federal Acquisition Circular 2005-72; Small Entity Compliance Guide

Federal Register 2010, 2011, 2012, 2013, 2014

2013-12-31

...: Small Entity Compliance Guide. SUMMARY: This document is issued under the joint authority of DOD, GSA..., contact the analyst whose name appears in the table below. Please cite FAC 2005-72 and the FAR case number... 202- 501-4755. Rules Listed in FAC 2005-72 Item Subject FAR Case Analyst *I Service 2010-010 Loeb...

A rule-based named-entity recognition method for knowledge extraction of evidence-based dietary recommendations

PubMed Central

2017-01-01

Evidence-based dietary information represented as unstructured text is a crucial information that needs to be accessed in order to help dietitians follow the new knowledge arrives daily with newly published scientific reports. Different named-entity recognition (NER) methods have been introduced previously to extract useful information from the biomedical literature. They are focused on, for example extracting gene mentions, proteins mentions, relationships between genes and proteins, chemical concepts and relationships between drugs and diseases. In this paper, we present a novel NER method, called drNER, for knowledge extraction of evidence-based dietary information. To the best of our knowledge this is the first attempt at extracting dietary concepts. DrNER is a rule-based NER that consists of two phases. The first one involves the detection and determination of the entities mention, and the second one involves the selection and extraction of the entities. We evaluate the method by using text corpora from heterogeneous sources, including text from several scientifically validated web sites and text from scientific publications. Evaluation of the method showed that drNER gives good results and can be used for knowledge extraction of evidence-based dietary recommendations. PMID:28644863

Assessment of disease named entity recognition on a corpus of annotated sentences.

PubMed

Jimeno, Antonio; Jimenez-Ruiz, Ernesto; Lee, Vivian; Gaudan, Sylvain; Berlanga, Rafael; Rebholz-Schuhmann, Dietrich

2008-04-11

In recent years, the recognition of semantic types from the biomedical scientific literature has been focused on named entities like protein and gene names (PGNs) and gene ontology terms (GO terms). Other semantic types like diseases have not received the same level of attention. Different solutions have been proposed to identify disease named entities in the scientific literature. While matching the terminology with language patterns suffers from low recall (e.g., Whatizit) other solutions make use of morpho-syntactic features to better cover the full scope of terminological variability (e.g., MetaMap). Currently, MetaMap that is provided from the National Library of Medicine (NLM) is the state of the art solution for the annotation of concepts from UMLS (Unified Medical Language System) in the literature. Nonetheless, its performance has not yet been assessed on an annotated corpus. In addition, little effort has been invested so far to generate an annotated dataset that links disease entities in text to disease entries in a database, thesaurus or ontology and that could serve as a gold standard to benchmark text mining solutions. As part of our research work, we have taken a corpus that has been delivered in the past for the identification of associations of genes to diseases based on the UMLS Metathesaurus and we have reprocessed and re-annotated the corpus. We have gathered annotations for disease entities from two curators, analyzed their disagreement (0.51 in the kappa-statistic) and composed a single annotated corpus for public use. Thereafter, three solutions for disease named entity recognition including MetaMap have been applied to the corpus to automatically annotate it with UMLS Metathesaurus concepts. The resulting annotations have been benchmarked to compare their performance. The annotated corpus is publicly available at ftp://ftp.ebi.ac.uk/pub/software/textmining/corpora/diseases and can serve as a benchmark to other systems. In addition, we found that dictionary look-up already provides competitive results indicating that the use of disease terminology is highly standardized throughout the terminologies and the literature. MetaMap generates precise results at the expense of insufficient recall while our statistical method obtains better recall at a lower precision rate. Even better results in terms of precision are achieved by combining at least two of the three methods leading, but this approach again lowers recall. Altogether, our analysis gives a better understanding of the complexity of disease annotations in the literature. MetaMap and the dictionary based approach are available through the Whatizit web service infrastructure (Rebholz-Schuhmann D, Arregui M, Gaudan S, Kirsch H, Jimeno A: Text processing through Web services: Calling Whatizit. Bioinformatics 2008, 24:296-298).

Occult Hepatitis B (OBH) in Clinical Settings

PubMed Central

Alavian, Seyed Moayed; Miri, Seyed Mohammad; Hollinger, F. Blaine; Jazayeri, Seyed Mohammad

2012-01-01

Context Occult hepatitis B (OHB), or persistent HBV DNA in patients who are hepatitis B surface antigen (HBsAg) negative, is a recently recognized entity. In an attempt to summarize the issues, this review presents an overview of the current proposed hypothesis on the clinical relevance and also updates the knowledge on the classification of OHB in different clinical settings. Evidence Acquisition OHB could be found in different population and clinical backgrounds including: viral co-infections (with either human immunodeficiency or hepatitis C viruses), HBV chronic carriers, dialysis patients, transplantation settings and certain clinical situations (named in here: special clinical settings) with no apparent distinguishable clinical parameters. Results The exact magnitude, pathogenesis, and clinical relevance of OHB are unclear. Even the possible role exerted by this cryptic infection on liver disease outcome, and hepatocellular carcinoma development remains unknown. Conclusions Monitoring of Individuals with positive anti-HBc, mass immunization programs and improvement in diagnostic tools seem to be important to control the probability of transmission of HBV through cryptic HBV infection. PMID:23087749

[TNM 2010. What's new?].

PubMed

Wittekind, C

2010-10-01

In the seventh edition of the TNM Classification of Malignant Tumours there are several entirely new classifications: upper aerodigestive mucosal melanoma, gastrointestinal stromal tumour, gastrointestinal carcinoid (neuroendocrine tumour), intrahepatic cholangiocarcinoma, Merkel cell carcinoma, uterine sarcomas, and adrenal cortical carcinoma. Significant modifications concern carcinomas of the oesophagus, oesophagogastric junction, stomach, appendix, biliary tract, lung, skin, prostate and ophthalmic tumours, which will be not addressed in this article. For several tumour entities only minor changes were introduced which might be of importance in daily practice. The new classifications and changes will be commented on without going into details.

Towards a new taxonomy of idiopathic orofacial pain.

PubMed

Woda, Alain; Tubert-Jeannin, Stéphanie; Bouhassira, Didier; Attal, Nadine; Fleiter, Bernard; Goulet, Jean-Paul; Gremeau-Richard, Christelle; Navez, Marie Louise; Picard, Pascale; Pionchon, Paul; Albuisson, Eliane

2005-08-01

There is no current consensus on the taxonomy of the different forms of idiopathic orofacial pain (stomatodynia, atypical odontalgia, atypical facial pain, facial arthromyalgia), which are sometimes considered as separate entities and sometimes grouped together. In the present prospective multicentric study, we used a systematic approach to help to place these different painful syndromes in the general classification of chronic facial pain. This multicenter study was carried out on 245 consecutive patients presenting with chronic facial pain (>4 months duration). Each patient was seen by two experts who proposed a diagnosis, administered a 111-item questionnaire and filled out a standardized 68-item examination form. Statistical processing included univariate analysis and several forms of multidimensional analysis. Migraines (n=37), tension-type headache (n=26), post-traumatic neuralgia (n=20) and trigeminal neuralgia (n=13) tended to cluster independently. When signs and symptoms describing topographic features were not included in the list of variables, the idiopathic orofacial pain patients tended to cluster in a single group. Inside this large cluster, only stomatodynia (n=42) emerged as a distinct homogenous subgroup. In contrast, facial arthromyalgia (n=46) and an entity formed with atypical facial pain (n=25) and atypical odontalgia (n=13) could only be individualised by variables reflecting topographical characteristics. These data provide grounds for an evidence-based classification of idiopathic facial pain entities and indicate that the current sub-classification of these syndromes relies primarily on the topography of the symptoms.

Contextually guided very-high-resolution imagery classification with semantic segments

NASA Astrophysics Data System (ADS)

Zhao, Wenzhi; Du, Shihong; Wang, Qiao; Emery, William J.

2017-10-01

Contextual information, revealing relationships and dependencies between image objects, is one of the most important information for the successful interpretation of very-high-resolution (VHR) remote sensing imagery. Over the last decade, geographic object-based image analysis (GEOBIA) technique has been widely used to first divide images into homogeneous parts, and then to assign semantic labels according to the properties of image segments. However, due to the complexity and heterogeneity of VHR images, segments without semantic labels (i.e., semantic-free segments) generated with low-level features often fail to represent geographic entities (such as building roofs usually be partitioned into chimney/antenna/shadow parts). As a result, it is hard to capture contextual information across geographic entities when using semantic-free segments. In contrast to low-level features, "deep" features can be used to build robust segments with accurate labels (i.e., semantic segments) in order to represent geographic entities at higher levels. Based on these semantic segments, semantic graphs can be constructed to capture contextual information in VHR images. In this paper, semantic segments were first explored with convolutional neural networks (CNN) and a conditional random field (CRF) model was then applied to model the contextual information between semantic segments. Experimental results on two challenging VHR datasets (i.e., the Vaihingen and Beijing scenes) indicate that the proposed method is an improvement over existing image classification techniques in classification performance (overall accuracy ranges from 82% to 96%).

Object-Oriented Approach to Integrating Database Semantics. Volume 4.

DTIC Science & Technology

1987-12-01

schemata for; 1. Object Classification Shema -- Entities 2. Object Structure and Relationship Schema -- Relations 3. Operation Classification and... relationships are represented in a database is non- intuitive for naive users. *It is difficult to access and combine information in multiple databases. In this...from the CURRENT-.CLASSES table. Choosing a selected item do-selects it. Choose 0 to exit. 1. STUDENTS 2. CUR~RENT-..CLASSES 3. MANAGMNT -.CLASS

FamPlex: a resource for entity recognition and relationship resolution of human protein families and complexes in biomedical text mining.

PubMed

Bachman, John A; Gyori, Benjamin M; Sorger, Peter K

2018-06-28

For automated reading of scientific publications to extract useful information about molecular mechanisms it is critical that genes, proteins and other entities be correctly associated with uniform identifiers, a process known as named entity linking or "grounding." Correct grounding is essential for resolving relationships among mined information, curated interaction databases, and biological datasets. The accuracy of this process is largely dependent on the availability of machine-readable resources associating synonyms and abbreviations commonly found in biomedical literature with uniform identifiers. In a task involving automated reading of ∼215,000 articles using the REACH event extraction software we found that grounding was disproportionately inaccurate for multi-protein families (e.g., "AKT") and complexes with multiple subunits (e.g."NF- κB"). To address this problem we constructed FamPlex, a manually curated resource defining protein families and complexes as they are commonly encountered in biomedical text. In FamPlex the gene-level constituents of families and complexes are defined in a flexible format allowing for multi-level, hierarchical membership. To create FamPlex, text strings corresponding to entities were identified empirically from literature and linked manually to uniform identifiers; these identifiers were also mapped to equivalent entries in multiple related databases. FamPlex also includes curated prefix and suffix patterns that improve named entity recognition and event extraction. Evaluation of REACH extractions on a test corpus of ∼54,000 articles showed that FamPlex significantly increased grounding accuracy for families and complexes (from 15 to 71%). The hierarchical organization of entities in FamPlex also made it possible to integrate otherwise unconnected mechanistic information across families, subfamilies, and individual proteins. Applications of FamPlex to the TRIPS/DRUM reading system and the Biocreative VI Bioentity Normalization Task dataset demonstrated the utility of FamPlex in other settings. FamPlex is an effective resource for improving named entity recognition, grounding, and relationship resolution in automated reading of biomedical text. The content in FamPlex is available in both tabular and Open Biomedical Ontology formats at https://github.com/sorgerlab/famplex under the Creative Commons CC0 license and has been integrated into the TRIPS/DRUM and REACH reading systems.

Combination of Evidence for Effective Web Search

DTIC Science & Technology

2010-11-01

SPONSORING/MONITORING AGENCY NAME(S) AND ADDRESS(ES) 10. SPONSOR/MONITOR’S ACRONYM(S) 11. SPONSOR/MONITOR’S REPORT NUMBER(S) 12. DISTRIBUTION /AVAILABILITY...STATEMENT Approved for public release; distribution unlimited 13. SUPPLEMENTARY NOTES Presented at the Nineteenth Text REtrieval Conference (TREC...use that page to expand. This happens often with named entity queries (such as ‘the secret garden’ or ‘ starbucks ’). However, when the query is

Clinical Named Entity Recognition Using Deep Learning Models.

PubMed

Wu, Yonghui; Jiang, Min; Xu, Jun; Zhi, Degui; Xu, Hua

2017-01-01

Clinical Named Entity Recognition (NER) is a critical natural language processing (NLP) task to extract important concepts (named entities) from clinical narratives. Researchers have extensively investigated machine learning models for clinical NER. Recently, there have been increasing efforts to apply deep learning models to improve the performance of current clinical NER systems. This study examined two popular deep learning architectures, the Convolutional Neural Network (CNN) and the Recurrent Neural Network (RNN), to extract concepts from clinical texts. We compared the two deep neural network architectures with three baseline Conditional Random Fields (CRFs) models and two state-of-the-art clinical NER systems using the i2b2 2010 clinical concept extraction corpus. The evaluation results showed that the RNN model trained with the word embeddings achieved a new state-of-the- art performance (a strict F1 score of 85.94%) for the defined clinical NER task, outperforming the best-reported system that used both manually defined and unsupervised learning features. This study demonstrates the advantage of using deep neural network architectures for clinical concept extraction, including distributed feature representation, automatic feature learning, and long-term dependencies capture. This is one of the first studies to compare the two widely used deep learning models and demonstrate the superior performance of the RNN model for clinical NER.

Clinical Named Entity Recognition Using Deep Learning Models

PubMed Central

Wu, Yonghui; Jiang, Min; Xu, Jun; Zhi, Degui; Xu, Hua

2017-01-01

Clinical Named Entity Recognition (NER) is a critical natural language processing (NLP) task to extract important concepts (named entities) from clinical narratives. Researchers have extensively investigated machine learning models for clinical NER. Recently, there have been increasing efforts to apply deep learning models to improve the performance of current clinical NER systems. This study examined two popular deep learning architectures, the Convolutional Neural Network (CNN) and the Recurrent Neural Network (RNN), to extract concepts from clinical texts. We compared the two deep neural network architectures with three baseline Conditional Random Fields (CRFs) models and two state-of-the-art clinical NER systems using the i2b2 2010 clinical concept extraction corpus. The evaluation results showed that the RNN model trained with the word embeddings achieved a new state-of-the- art performance (a strict F1 score of 85.94%) for the defined clinical NER task, outperforming the best-reported system that used both manually defined and unsupervised learning features. This study demonstrates the advantage of using deep neural network architectures for clinical concept extraction, including distributed feature representation, automatic feature learning, and long-term dependencies capture. This is one of the first studies to compare the two widely used deep learning models and demonstrate the superior performance of the RNN model for clinical NER. PMID:29854252

Taxonaut: an application software for comparative display of multiple taxonomies with a use case of GBIF Species API.

PubMed

Ytow, Nozomi

2016-01-01

The Species API of the Global Biodiversity Information Facility (GBIF) provides public access to taxonomic data aggregated from multiple data sources. Each data source follows its own classification which can be inconsistent with classifications from other sources. Even with a reference classification e.g. the GBIF Backbone taxonomy, a comprehensive method to compare classifications in the data aggregation is essential, especially for non-expert users. A Java application was developed to compare multiple taxonomies graphically using classification data acquired from GBIF's ChecklistBank via the GBIF Species API. It uses a table to display taxonomies where each column represents a taxonomy under comparison, with an aligner column to organise taxa by name. Each cell contains the name of a taxon if the classification in that column contains the name. Each column also has a cell showing the hierarchy of the taxonomy by a folder metaphor where taxa are aligned and synchronised in the aligner column. A set of those comparative tables shows taxa categorised by relationship between taxonomies. The result set is also available as tables in an Excel format file.

5 CFR 1312.8 - Standard identification and markings.

Code of Federal Regulations, 2014 CFR

2014-01-01

... CLASSIFICATION, DOWNGRADING, DECLASSIFICATION AND SAFEGUARDING OF NATIONAL SECURITY INFORMATION Classification.... (a) Original classification. At the time classified material is produced, the classifier shall apply...: (1) Classification authority. The name/personal identifier, and position title of the original...

5 CFR 1312.8 - Standard identification and markings.

Code of Federal Regulations, 2013 CFR

2013-01-01

... CLASSIFICATION, DOWNGRADING, DECLASSIFICATION AND SAFEGUARDING OF NATIONAL SECURITY INFORMATION Classification.... (a) Original classification. At the time classified material is produced, the classifier shall apply...: (1) Classification authority. The name/personal identifier, and position title of the original...

5 CFR 1312.8 - Standard identification and markings.

Code of Federal Regulations, 2012 CFR

2012-01-01

... CLASSIFICATION, DOWNGRADING, DECLASSIFICATION AND SAFEGUARDING OF NATIONAL SECURITY INFORMATION Classification.... (a) Original classification. At the time classified material is produced, the classifier shall apply...: (1) Classification authority. The name/personal identifier, and position title of the original...

32 CFR 2001.21 - Original classification.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 32 National Defense 6 2010-07-01 2010-07-01 false Original classification. 2001.21 Section 2001.21... Markings § 2001.21 Original classification. (a) Primary markings. At the time of original classification... authority. The name and position, or personal identifier, of the original classification authority shall...

78 FR 79007 - Certain Multiple Mode Outdoor Grills and Parts Thereof; Commission Determination Not To Review an...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-12-27

... Antonio, Texas; Kmart Corporation of Hoffman Estates, Illinois; Sears Brands Management Corporation, Sears... Specialty Brands, LLC, (2) change the name of Respondent Rankam Group to Rankam Metal Products Manufactory... Kamado Joe Company is a trade name for the legal entity Premier Specialty Brands, LLC; Rankam Metal...

49 CFR Appendix E to Part 512 - Consumer Assistance to Recycle and Save (CARS) Class Determinations

Code of Federal Regulations, 2013 CFR

2013-10-01

... of the new vehicle owner's name, home address, telephone number, state identification number and last... harm to the competitive position of the entity submitting the information: (1) Vehicle Manufacturer Issued Dealer Identification Code; (2) Dealer Bank Name, ABA Routing Number and Bank Account Number; and...

77 FR 31356 - Pesticide Products; Receipt of Applications To Register New Uses

Federal Register 2010, 2011, 2012, 2013, 2014

2012-05-25

... Number: EPA-HQ-OPP-2012- 0241. Company name and address: Bayer CropScience LP, 2 T. W. Alexander Drive.... Registration Number: 264-825. Docket Number: EPA-HQ-OPP-2012- 0325. Company name and address: Bayer CropScience... pesticide manufacturer. Potentially affected entities may include, but are not limited to: Crop production...

Mining protein phosphorylation information from biomedical literature using NLP parsing and Support Vector Machines.

PubMed

Raja, Kalpana; Natarajan, Jeyakumar

2018-07-01

Extraction of protein phosphorylation information from biomedical literature has gained much attention because of the importance in numerous biological processes. In this study, we propose a text mining methodology which consists of two phases, NLP parsing and SVM classification to extract phosphorylation information from literature. First, using NLP parsing we divide the data into three base-forms depending on the biomedical entities related to phosphorylation and further classify into ten sub-forms based on their distribution with phosphorylation keyword. Next, we extract the phosphorylation entity singles/pairs/triplets and apply SVM to classify the extracted singles/pairs/triplets using a set of features applicable to each sub-form. The performance of our methodology was evaluated on three corpora namely PLC, iProLink and hPP corpus. We obtained promising results of >85% F-score on ten sub-forms of training datasets on cross validation test. Our system achieved overall F-score of 93.0% on iProLink and 96.3% on hPP corpus test datasets. Furthermore, our proposed system achieved best performance on cross corpus evaluation and outperformed the existing system with recall of 90.1%. The performance analysis of our unique system on three corpora reveals that it extracts protein phosphorylation information efficiently in both non-organism specific general datasets such as PLC and iProLink, and human specific dataset such as hPP corpus. Copyright © 2018 Elsevier B.V. All rights reserved.

The 2017 WHO update on mature T- and natural killer (NK) cell neoplasms.

PubMed

Matutes, E

2018-05-01

Over the last decade, there has been a significant body of information regarding the biology of the lymphoid neoplasms. This clearly supports the need for updating the 2008 WHO (World Health Organization) classification of haematopoietic and lymphoid tumours. The 2017 WHO classification is not a new edition but an update and revision of the 4th edition. New provisional entities but not new definitive entities are included, and novel molecular data in most of the entities and changes in the nomenclature in few of them have been incorporated. In the context of the mature T- and NK-cell neoplasms, the most relevant updates concern to: 1-dysregulation of the JAK/STAT pathway due to gene mutations which are common to various aggressive and indolent neoplasms; 2-incorporation of new molecular players that are relevant to the pathogenesis of these neoplasms and/or have prognostic implications; 3-inclusion of new provisional entities within the subgroups of anaplastic, primarily intestinal and cutaneous lymphomas such as breast implant-associated anaplastic large cell lymphoma, indolent T-cell lymphoproliferative disorder of the gastrointestinal tract and primary cutaneous acral CD8 + T-cell lymphoma; 4-identification of poor prognostic subtypes of peripheral T-cell lymphomas not otherwise specified (PTCL, NOS) characterized by overexpression of certain genes and of a subgroup PTCL, NOS with a T follicular phenotype that now is included together with angioimmunoblastic T-cell lymphoma under the umbrella of lymphomas with a T follicular helper phenotype; and 5-refinement on the designation and definition of already established entities. A review of the major changes will be outlined. © 2018 John Wiley & Sons Ltd.

Overlap in drug-disease associations between clinical practice guidelines and drug structured product label indications.

PubMed

Leung, Tiffany I; Dumontier, Michel

2016-06-08

Clinical practice guidelines (CPGs) recommend pharmacologic treatments for clinical conditions, and drug structured product labels (SPLs) summarize approved treatment indications. Both resources are intended to promote evidence-based medical practices and guide clinicians' prescribing decisions. However, it is unclear how well CPG recommendations about pharmacologic therapies match SPL indications for recommended drugs. In this study, we perform text mining of CPG summaries to examine drug-disease associations in CPG recommendations and in SPL treatment indications for 15 common chronic conditions. We constructed an initial text corpus of guideline summaries from the National Guideline Clearinghouse (NGC) from a set of manually selected ICD-9 codes for each of the 15 conditions. We obtained 377 relevant guideline summaries and their Major Recommendations section, which excludes guidelines for pediatric patients, pregnant or breastfeeding women, or for medical diagnoses not meeting inclusion criteria. A vocabulary of drug terms was derived from five medical taxonomies. We used named entity recognition, in combination with dictionary-based and ontology-based methods, to identify drug term occurrences in the text corpus and construct drug-disease associations. The ATC (Anatomical Therapeutic Chemical Classification) was utilized to perform drug name and drug class matching to construct the drug-disease associations from CPGs. We then obtained drug-disease associations from SPLs using conditions mentioned in their Indications section in SIDER. The primary outcomes were the frequency of drug-disease associations in CPGs and SPLs, and the frequency of overlap between the two sets of drug-disease associations, with and without using taxonomic information from ATC. Without taxonomic information, we identified 1444 drug-disease associations across CPGs and SPLs for 15 common chronic conditions. Of these, 195 drug-disease associations overlapped between CPGs and SPLs, 917 associations occurred in CPGs only and 332 associations occurred in SPLs only. With taxonomic information, 859 unique drug-disease associations were identified, of which 152 of these drug-disease associations overlapped between CPGs and SPLs, 541 associations occurred in CPGs only, and 166 associations occurred in SPLs only. Our results suggest that CPG-recommended pharmacologic therapies and SPL indications do not overlap frequently when identifying drug-disease associations using named entity recognition, although incorporating taxonomic relationships between drug names and drug classes into the approach improves the overlap. This has important implications in practice because conflicting or inconsistent evidence may complicate clinical decision making and implementation or measurement of best practices.

Finding Cervical Cancer Symptoms in Swedish Clinical Text using a Machine Learning Approach and NegEx

PubMed Central

Weegar, Rebecka; Kvist, Maria; Sundström, Karin; Brunak, Søren; Dalianis, Hercules

2015-01-01

Detection of early symptoms in cervical cancer is crucial for early treatment and survival. To find symptoms of cervical cancer in clinical text, Named Entity Recognition is needed. In this paper the Clinical Entity Finder, a machine-learning tool trained on annotated clinical text from a Swedish internal medicine emergency unit, is evaluated on cervical cancer records. The Clinical Entity Finder identifies entities of the types body part, finding and disorder and is extended with negation detection using the rule-based tool NegEx, to distinguish between negated and non-negated entities. To measure the performance of the tools on this new domain, two physicians annotated a set of clinical notes from the health records of cervical cancer patients. The inter-annotator agreement for finding, disorder and body part obtained an average F-score of 0.677 and the Clinical Entity Finder extended with NegEx had an average F-score of 0.667. PMID:26958270

Finding Cervical Cancer Symptoms in Swedish Clinical Text using a Machine Learning Approach and NegEx.

PubMed

Weegar, Rebecka; Kvist, Maria; Sundström, Karin; Brunak, Søren; Dalianis, Hercules

2015-01-01

Detection of early symptoms in cervical cancer is crucial for early treatment and survival. To find symptoms of cervical cancer in clinical text, Named Entity Recognition is needed. In this paper the Clinical Entity Finder, a machine-learning tool trained on annotated clinical text from a Swedish internal medicine emergency unit, is evaluated on cervical cancer records. The Clinical Entity Finder identifies entities of the types body part, finding and disorder and is extended with negation detection using the rule-based tool NegEx, to distinguish between negated and non-negated entities. To measure the performance of the tools on this new domain, two physicians annotated a set of clinical notes from the health records of cervical cancer patients. The inter-annotator agreement for finding, disorder and body part obtained an average F-score of 0.677 and the Clinical Entity Finder extended with NegEx had an average F-score of 0.667.

A Complex Network Perspective on Clinical Science

PubMed Central

Hofmann, Stefan G.; Curtiss, Joshua; McNally, Richard J.

2016-01-01

Contemporary classification systems for mental disorders assume that abnormal behaviors are expressions of latent disease entities. An alternative to the latent disease model is the complex network approach. Instead of assuming that symptoms arise from an underlying disease entity, the complex network approach holds that disorders exist as systems of interrelated elements of a network. This approach also provides a framework for the understanding of therapeutic change. Depending on the structure of the network, change can occur abruptly once the network reaches a critical threshold (the tipping point). Homogeneous and highly connected networks often recover more slowly from local perturbations when the network approaches the tipping point, allowing for the possibility to predict treatment change, relapse, and recovery. In this article we discuss the complex network approach as an alternative to the latent disease model, and we discuss its implications for classification, therapy, relapse, and recovery. PMID:27694457

Extrahepatic portal vein obstruction and portal vein thrombosis in special situations: Need for a new classification.

PubMed

Wani, Zeeshan A; Bhat, Riyaz A; Bhadoria, Ajeet S; Maiwall, Rakhi

2015-01-01

Extrahepatic portal vein obstruction is a vascular disorder of liver, which results in obstruction and cavernomatous transformation of portal vein with or without the involvement of intrahepatic portal vein, splenic vein, or superior mesenteric vein. Portal vein obstruction due to chronic liver disease, neoplasm, or postsurgery is a separate entity and is not the same as extrahepatic portal vein obstruction. Patients with extrahepatic portal vein obstruction are generally young and belong mostly to Asian countries. It is therefore very important to define portal vein thrombosis as acute or chronic from management point of view. Portal vein thrombosis in certain situations such as liver transplant and postsurgical/liver transplant period is an evolving area and needs extensive research. There is a need for a new classification, which includes all areas of the entity. In the current review, the most recent literature of extrahepatic portal vein obstruction is reviewed and summarized.

Extrahepatic Portal Vein Obstruction and Portal Vein Thrombosis in Special Situations: Need for a New Classification

PubMed Central

Wani, Zeeshan A.; Bhat, Riyaz A.; Bhadoria, Ajeet S.; Maiwall, Rakhi

2015-01-01

Extrahepatic portal vein obstruction is a vascular disorder of liver, which results in obstruction and cavernomatous transformation of portal vein with or without the involvement of intrahepatic portal vein, splenic vein, or superior mesenteric vein. Portal vein obstruction due to chronic liver disease, neoplasm, or postsurgery is a separate entity and is not the same as extrahepatic portal vein obstruction. Patients with extrahepatic portal vein obstruction are generally young and belong mostly to Asian countries. It is therefore very important to define portal vein thrombosis as acute or chronic from management point of view. Portal vein thrombosis in certain situations such as liver transplant and postsurgical/liver transplant period is an evolving area and needs extensive research. There is a need for a new classification, which includes all areas of the entity. In the current review, the most recent literature of extrahepatic portal vein obstruction is reviewed and summarized. PMID:26021771

Developing a hybrid dictionary-based bio-entity recognition technique.

PubMed

Song, Min; Yu, Hwanjo; Han, Wook-Shin

2015-01-01

Bio-entity extraction is a pivotal component for information extraction from biomedical literature. The dictionary-based bio-entity extraction is the first generation of Named Entity Recognition (NER) techniques. This paper presents a hybrid dictionary-based bio-entity extraction technique. The approach expands the bio-entity dictionary by combining different data sources and improves the recall rate through the shortest path edit distance algorithm. In addition, the proposed technique adopts text mining techniques in the merging stage of similar entities such as Part of Speech (POS) expansion, stemming, and the exploitation of the contextual cues to further improve the performance. The experimental results show that the proposed technique achieves the best or at least equivalent performance among compared techniques, GENIA, MESH, UMLS, and combinations of these three resources in F-measure. The results imply that the performance of dictionary-based extraction techniques is largely influenced by information resources used to build the dictionary. In addition, the edit distance algorithm shows steady performance with three different dictionaries in precision whereas the context-only technique achieves a high-end performance with three difference dictionaries in recall.

Developing a hybrid dictionary-based bio-entity recognition technique

PubMed Central

2015-01-01

Background Bio-entity extraction is a pivotal component for information extraction from biomedical literature. The dictionary-based bio-entity extraction is the first generation of Named Entity Recognition (NER) techniques. Methods This paper presents a hybrid dictionary-based bio-entity extraction technique. The approach expands the bio-entity dictionary by combining different data sources and improves the recall rate through the shortest path edit distance algorithm. In addition, the proposed technique adopts text mining techniques in the merging stage of similar entities such as Part of Speech (POS) expansion, stemming, and the exploitation of the contextual cues to further improve the performance. Results The experimental results show that the proposed technique achieves the best or at least equivalent performance among compared techniques, GENIA, MESH, UMLS, and combinations of these three resources in F-measure. Conclusions The results imply that the performance of dictionary-based extraction techniques is largely influenced by information resources used to build the dictionary. In addition, the edit distance algorithm shows steady performance with three different dictionaries in precision whereas the context-only technique achieves a high-end performance with three difference dictionaries in recall. PMID:26043907

A Statistical Model for Multilingual Entity Detection and Tracking

DTIC Science & Technology

2004-01-01

tomatic Content Extraction ( ACE ) evaluation achieved top-tier results in all three evaluation languages. 1 Introduction Detecting entities, whether named...of com- bining the detected mentions into groups of references to the same object. The work presented here is motivated by the ACE eval- uation...Entropy (MaxEnt henceforth) (Berger et al., 1996) and Robust Risk Minimization (RRM henceforth) 1For a description of the ACE program see http

Improving the Accuracy of Attribute Extraction using the Relatedness between Attribute Values

NASA Astrophysics Data System (ADS)

Bollegala, Danushka; Tani, Naoki; Ishizuka, Mitsuru

Extracting attribute-values related to entities from web texts is an important step in numerous web related tasks such as information retrieval, information extraction, and entity disambiguation (namesake disambiguation). For example, for a search query that contains a personal name, we can not only return documents that contain that personal name, but if we have attribute-values such as the organization for which that person works, we can also suggest documents that contain information related to that organization, thereby improving the user's search experience. Despite numerous potential applications of attribute extraction, it remains a challenging task due to the inherent noise in web data -- often a single web page contains multiple entities and attributes. We propose a graph-based approach to select the correct attribute-values from a set of candidate attribute-values extracted for a particular entity. First, we build an undirected weighted graph in which, attribute-values are represented by nodes, and the edge that connects two nodes in the graph represents the degree of relatedness between the corresponding attribute-values. Next, we find the maximum spanning tree of this graph that connects exactly one attribute-value for each attribute-type. The proposed method outperforms previously proposed attribute extraction methods on a dataset that contains 5000 web pages.

Network analysis of named entity co-occurrences in written texts

NASA Astrophysics Data System (ADS)

Amancio, Diego Raphael

2016-06-01

The use of methods borrowed from statistics and physics to analyze written texts has allowed the discovery of unprecedent patterns of human behavior and cognition by establishing links between models features and language structure. While current models have been useful to unveil patterns via analysis of syntactical and semantical networks, only a few works have probed the relevance of investigating the structure arising from the relationship between relevant entities such as characters, locations and organizations. In this study, we represent entities appearing in the same context as a co-occurrence network, where links are established according to a null model based on random, shuffled texts. Computational simulations performed in novels revealed that the proposed model displays interesting topological features, such as the small world feature, characterized by high values of clustering coefficient. The effectiveness of our model was verified in a practical pattern recognition task in real networks. When compared with traditional word adjacency networks, our model displayed optimized results in identifying unknown references in texts. Because the proposed representation plays a complementary role in characterizing unstructured documents via topological analysis of named entities, we believe that it could be useful to improve the characterization of written texts (and related systems), specially if combined with traditional approaches based on statistical and deeper paradigms.

NeuroNames: an ontology for the BrainInfo portal to neuroscience on the web.

PubMed

Bowden, Douglas M; Song, Evan; Kosheleva, Julia; Dubach, Mark F

2012-01-01

BrainInfo ( http://braininfo.org ) is a growing portal to neuroscientific information on the Web. It is indexed by NeuroNames, an ontology designed to compensate for ambiguities in neuroanatomical nomenclature. The 20-year old ontology continues to evolve toward the ideal of recognizing all names of neuroanatomical entities and accommodating all structural concepts about which neuroscientists communicate, including multiple concepts of entities for which neuroanatomists have yet to determine the best or 'true' conceptualization. To make the definitions of structural concepts unambiguous and terminologically consistent we created a 'default vocabulary' of unique structure names selected from existing terminology. We selected standard names by criteria designed to maximize practicality for use in verbal communication as well as computerized knowledge management. The ontology of NeuroNames accommodates synonyms and homonyms of the standard terms in many languages. It defines complex structures as models composed of primary structures, which are defined in unambiguous operational terms. NeuroNames currently relates more than 16,000 names in eight languages to some 2,500 neuroanatomical concepts. The ontology is maintained in a relational database with three core tables: Names, Concepts and Models. BrainInfo uses NeuroNames to index information by structure, to interpret users' queries and to clarify terminology on remote web pages. NeuroNames is a resource vocabulary of the NLM's Unified Medical Language System (UMLS, 2011) and the basis for the brain regions component of NIFSTD (NeuroLex, 2011). The current version has been downloaded to hundreds of laboratories for indexing data and linking to BrainInfo, which attracts some 400 visitors/day, downloading 2,000 pages/day.

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

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.

Exploring the Repeated Name Penalty and the Overt Pronoun Penalty in Spanish

ERIC Educational Resources Information Center

Gelormini-Lezama, Carlos

2018-01-01

Anaphoric expressions such as repeated names, overt pronouns, and null pronouns serve a major role in the creation and maintenance of discourse coherence. The felicitous use of an anaphoric expression is highly dependent on the discourse salience of the entity introduced by the antecedent. Gordon et al. ("Cogn Sci" 17:311-347, 1993)…

The 2017 World Health Organization classification of tumors of the pituitary gland: a summary.

PubMed

Lopes, M Beatriz S

2017-10-01

The 4th edition of the World Health Organization (WHO) classification of endocrine tumors has been recently released. In this new edition, major changes are recommended in several areas of the classification of tumors of the anterior pituitary gland (adenophypophysis). The scope of the present manuscript is to summarize these recommended changes, emphasizing a few significant topics. These changes include the following: (1) a novel approach for classifying pituitary neuroendocrine tumors according to pituitary adenohypophyseal cell lineages; (2) changes to the histological grading of pituitary neuroendocrine tumors with the elimination of the term "atypical adenoma;" and (3) introduction of new entities like the pituitary blastoma and re-definition of old entities like the null-cell adenoma. This new classification is very practical and mostly based on immunohistochemistry for pituitary hormones, pituitary-specific transcription factors, and other immunohistochemical markers commonly used in pathology practice, not requiring routine ultrastructural analysis of the tumors. Evaluation of tumor proliferation potential, by mitotic count and Ki-67 labeling index, and tumor invasion is strongly recommended on individual case basis to identify clinically aggressive adenomas. In addition, the classification offers the treating clinical team information on tumor prognosis by identifying specific variants of adenomas associated with an elevated risk for recurrence. Changes in the classification of non-neuroendocrine tumors are also proposed, in particular those tumors arising in the posterior pituitary including pituicytoma, granular cell tumor of the posterior pituitary, and spindle cell oncocytoma. These changes endorse those previously published in the 2016 WHO classification of CNS tumors. Other tumors arising in the sellar region are also reviewed in detail including craniopharyngiomas, mesenchymal and stromal tumors, germ cell tumors, and hematopoietic tumors. It is hoped that the 2017 WHO classification of pituitary tumors will establish more biologically and clinically uniform groups of tumors, make it possible for practicing pathologists to better diagnose these tumors, and contribute to our understanding of clinical outcomes for patients harboring pituitary tumors.

24 CFR 58.36 - Environmental assessments.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 24 Housing and Urban Development 1 2010-04-01 2010-04-01 false Environmental assessments. 58.36... Development ENVIRONMENTAL REVIEW PROCEDURES FOR ENTITIES ASSUMING HUD ENVIRONMENTAL RESPONSIBILITIES Environmental Review Process: Documentation, Range of Activities, Project Aggregation and Classification § 58.36...

24 CFR 58.36 - Environmental assessments.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 24 Housing and Urban Development 1 2011-04-01 2011-04-01 false Environmental assessments. 58.36... Development ENVIRONMENTAL REVIEW PROCEDURES FOR ENTITIES ASSUMING HUD ENVIRONMENTAL RESPONSIBILITIES Environmental Review Process: Documentation, Range of Activities, Project Aggregation and Classification § 58.36...

Elucidation of metabolic pathways from enzyme classification data.

PubMed

McDonald, Andrew G; Tipton, Keith F

2014-01-01

The IUBMB Enzyme List is widely used by other databases as a source for avoiding ambiguity in the recognition of enzymes as catalytic entities. However, it was not designed for metabolic pathway tracing, which has become increasingly important in systems biology. A Reactions Database has been created from the material in the Enzyme List to allow reactions to be searched by substrate/product, and pathways to be traced from any selected starting/seed substrate. An extensive synonym glossary allows searches by many of the alternative names, including accepted abbreviations, by which a chemical compound may be known. This database was necessary for the development of the application Reaction Explorer ( http://www.reaction-explorer.org ), which was written in Real Studio ( http://www.realsoftware.com/realstudio/ ) to search the Reactions Database and draw metabolic pathways from reactions selected by the user. Having input the name of the starting compound (the "seed"), the user is presented with a list of all reactions containing that compound and then selects the product of interest as the next point on the ensuing graph. The pathway diagram is then generated as the process iterates. A contextual menu is provided, which allows the user: (1) to remove a compound from the graph, along with all associated links; (2) to search the reactions database again for additional reactions involving the compound; (3) to search for the compound within the Enzyme List.

Taxonaut: an application software for comparative display of multiple taxonomies with a use case of GBIF Species API

PubMed Central

2016-01-01

Abstract Background The Species API of the Global Biodiversity Information Facility (GBIF) provides public access to taxonomic data aggregated from multiple data sources. Each data source follows its own classification which can be inconsistent with classifications from other sources. Even with a reference classification e.g. the GBIF Backbone taxonomy, a comprehensive method to compare classifications in the data aggregation is essential, especially for non-expert users. New information A Java application was developed to compare multiple taxonomies graphically using classification data acquired from GBIF’s ChecklistBank via the GBIF Species API. It uses a table to display taxonomies where each column represents a taxonomy under comparison, with an aligner column to organise taxa by name. Each cell contains the name of a taxon if the classification in that column contains the name. Each column also has a cell showing the hierarchy of the taxonomy by a folder metaphor where taxa are aligned and synchronised in the aligner column. A set of those comparative tables shows taxa categorised by relationship between taxonomies. The result set is also available as tables in an Excel format file. PMID:27932916

Assessment of Orthographic Similarity of Drugs Names between Iran and Overseas Using the Solar Model

PubMed Central

ABOLHASSANI, Nazanin; AKBARI SARI, Ali; RASHIDIAN, Arash; RASTEGARPANAH, Mansoor

2017-01-01

Background: The recognition of patient safety is now occupying a prominent place on the health policy agenda since medical errors can result in adverse events. The existence of confusing drug names is one of the most common causes of medication errors. In Iran, the General Office of Trademarks Registry (GOTR), for four years (2010–2014) was responsible for approving drug proprietary names. This study aimed to investigate the performance of the GOTR in terms of drug names orthographic similarity using the SOLAR model. Methods: First, 100 names were randomly selected from the GOTR’s database. Then, each name was searched through pharmaceutical websites including Martindale (the Complete Drug Reference published by Pharmaceutical Press), Drugs.com and Medicines Complete. Pair of drugs whose names look orthographically similar with different indications were identified. Then, the SOLAR model was utilized to determine orthographic similarity between all pair of drug names. Results: The mean of match values of these 100 pairs of drug was 77% indicating the high risk of similarity. The match value for most of the reviewed pairs (92%) was high (≥66%). This value was medium (≥ 33% and <66%) just for 8% of the pairs of drug. These results indicate high risk of confusion due to similarity of drug names. Conclusion: The stewardship of the GOTR in patient safety considerations is fundamentally problematic. Thus, as a best practice, we recommend that proprietary names of drugs be evaluated by an entity within the health system. While an entity within the health system should address patient safety considerations, the GOTR is responsible for intellectual property rights. PMID:29259940

Proceedings of Conference on Variable-Resolution Modeling, Washington, DC, 5-6 May 1992

DTIC Science & Technology

1992-05-01

of powerful new computer architectures for supporting object-oriented computing. Objects, as self -contained data-code packages with orderly...another entity structure. For example, (copy-entstr e:sys- tcm ’ new -system) creates an entity structure named c:new-system that has the same structure...324 Parry, S-H. (1984): A Self -contained Hierarchical Model Construct. In: Systems Analysis and Modeling in Defense (R.K. Huber, Ed.), New York

Mining heart disease risk factors in clinical text with named entity recognition and distributional semantic models.

PubMed

Urbain, Jay

2015-12-01

We present the design, and analyze the performance of a multi-stage natural language processing system employing named entity recognition, Bayesian statistics, and rule logic to identify and characterize heart disease risk factor events in diabetic patients over time. The system was originally developed for the 2014 i2b2 Challenges in Natural Language in Clinical Data. The system's strengths included a high level of accuracy for identifying named entities associated with heart disease risk factor events. The system's primary weakness was due to inaccuracies when characterizing the attributes of some events. For example, determining the relative time of an event with respect to the record date, whether an event is attributable to the patient's history or the patient's family history, and differentiating between current and prior smoking status. We believe these inaccuracies were due in large part to the lack of an effective approach for integrating context into our event detection model. To address these inaccuracies, we explore the addition of a distributional semantic model for characterizing contextual evidence of heart disease risk factor events. Using this semantic model, we raise our initial 2014 i2b2 Challenges in Natural Language of Clinical data F1 score of 0.838 to 0.890 and increased precision by 10.3% without use of any lexicons that might bias our results. Copyright © 2015 Elsevier Inc. All rights reserved.

Automatic recognition of topic-classified relations between prostate cancer and genes using MEDLINE abstracts

PubMed Central

Chun, Hong-Woo; Tsuruoka, Yoshimasa; Kim, Jin-Dong; Shiba, Rie; Nagata, Naoki; Hishiki, Teruyoshi; Tsujii, Jun'ichi

2006-01-01

Background Automatic recognition of relations between a specific disease term and its relevant genes or protein terms is an important practice of bioinformatics. Considering the utility of the results of this approach, we identified prostate cancer and gene terms with the ID tags of public biomedical databases. Moreover, considering that genetics experts will use our results, we classified them based on six topics that can be used to analyze the type of prostate cancers, genes, and their relations. Methods We developed a maximum entropy-based named entity recognizer and a relation recognizer and applied them to a corpus-based approach. We collected prostate cancer-related abstracts from MEDLINE, and constructed an annotated corpus of gene and prostate cancer relations based on six topics by biologists. We used it to train the maximum entropy-based named entity recognizer and relation recognizer. Results Topic-classified relation recognition achieved 92.1% precision for the relation (an increase of 11.0% from that obtained in a baseline experiment). For all topics, the precision was between 67.6 and 88.1%. Conclusion A series of experimental results revealed two important findings: a carefully designed relation recognition system using named entity recognition can improve the performance of relation recognition, and topic-classified relation recognition can be effectively addressed through a corpus-based approach using manual annotation and machine learning techniques. PMID:17134477

Automatic recognition of topic-classified relations between prostate cancer and genes using MEDLINE abstracts.

PubMed

Chun, Hong-Woo; Tsuruoka, Yoshimasa; Kim, Jin-Dong; Shiba, Rie; Nagata, Naoki; Hishiki, Teruyoshi; Tsujii, Jun'ichi

2006-11-24

Automatic recognition of relations between a specific disease term and its relevant genes or protein terms is an important practice of bioinformatics. Considering the utility of the results of this approach, we identified prostate cancer and gene terms with the ID tags of public biomedical databases. Moreover, considering that genetics experts will use our results, we classified them based on six topics that can be used to analyze the type of prostate cancers, genes, and their relations. We developed a maximum entropy-based named entity recognizer and a relation recognizer and applied them to a corpus-based approach. We collected prostate cancer-related abstracts from MEDLINE, and constructed an annotated corpus of gene and prostate cancer relations based on six topics by biologists. We used it to train the maximum entropy-based named entity recognizer and relation recognizer. Topic-classified relation recognition achieved 92.1% precision for the relation (an increase of 11.0% from that obtained in a baseline experiment). For all topics, the precision was between 67.6 and 88.1%. A series of experimental results revealed two important findings: a carefully designed relation recognition system using named entity recognition can improve the performance of relation recognition, and topic-classified relation recognition can be effectively addressed through a corpus-based approach using manual annotation and machine learning techniques.

A New Data Representation Based on Training Data Characteristics to Extract Drug Name Entity in Medical Text

PubMed Central

Basaruddin, T.

2016-01-01

One essential task in information extraction from the medical corpus is drug name recognition. Compared with text sources come from other domains, the medical text mining poses more challenges, for example, more unstructured text, the fast growing of new terms addition, a wide range of name variation for the same drug, the lack of labeled dataset sources and external knowledge, and the multiple token representations for a single drug name. Although many approaches have been proposed to overwhelm the task, some problems remained with poor F-score performance (less than 0.75). This paper presents a new treatment in data representation techniques to overcome some of those challenges. We propose three data representation techniques based on the characteristics of word distribution and word similarities as a result of word embedding training. The first technique is evaluated with the standard NN model, that is, MLP. The second technique involves two deep network classifiers, that is, DBN and SAE. The third technique represents the sentence as a sequence that is evaluated with a recurrent NN model, that is, LSTM. In extracting the drug name entities, the third technique gives the best F-score performance compared to the state of the art, with its average F-score being 0.8645. PMID:27843447

Philadelphia chromosome-positive lymphoblastic lymphoma-Is it rare or underdiagnosed?

PubMed

Alshomar, Ahmad; El Fakih, Riad

2018-06-15

Lymphoblastic lymphomas (LBLs) are neoplasms of precursor B and T cells; they are considered in the same spectrum as precursor B and T cell acute lymphoblastic leukemia (ALL). The World Health Organization classification classifies both LBL and ALL as one disease entity. While chromosome abnormalities are well defined with all of their therapeutic and prognostic implications in ALL, these are not well studied in LBL. Here, we describe a case of Philadelphia chromosome-positive LBL and review the available literature regarding this entity. Copyright © 2018. Published by Elsevier Ltd.

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

ERIC Educational Resources Information Center

Diesendruck, Gil

2003-01-01

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

Traditional knowledge among Zapotecs of Sierra Madre Del Sur, Oaxaca. Does it represent a base for plant resources management and conservation?

PubMed

Luna-José, Azucena de Lourdes; Aguilar, Beatriz Rendón

2012-07-12

Traditional classification systems represent cognitive processes of human cultures in the world. It synthesizes specific conceptions of nature, as well as cumulative learning, beliefs and customs that are part of a particular human community or society. Traditional knowledge has been analyzed from different viewpoints, one of which corresponds to the analysis of ethnoclassifications. In this work, a brief analysis of the botanical traditional knowledge among Zapotecs of the municipality of San Agustin Loxicha, Oaxaca was conducted. The purposes of this study were: a) to analyze the traditional ecological knowledge of local plant resources through the folk classification of both landscapes and plants and b) to determine the role that this knowledge has played in plant resource management and conservation. The study was developed in five communities of San Agustín Loxicha. From field trips, plant specimens were collected and showed to local people in order to get the Spanish or Zapotec names; through interviews with local people, we obtained names and identified classification categories of plants, vegetation units, and soil types. We found a logic structure in Zapotec plant names, based on linguistic terms, as well as morphological and ecological caracteristics. We followed the classification principles proposed by Berlin [6] in order to build a hierarchical structure of life forms, names and other characteristics mentioned by people. We recorded 757 plant names. Most of them (67%) have an equivalent Zapotec name and the remaining 33% had mixed names with Zapotec and Spanish terms. Plants were categorized as native plants, plants introduced in pre-Hispanic times, or plants introduced later. All of them are grouped in a hierarchical classification, which include life form, generic, specific, and varietal categories. Monotypic and polytypic names are used to further classify plants. This holistic classification system plays an important role for local people in many aspects: it helps to organize and make sense of the diversity, to understand the interrelation among plants-soil-vegetation and to classify their physical space since they relate plants with a particular vegetation unit and a kind of soil. The locals also make a rational use of these elements, because they know which crops can grow in any vegetation unit, or which places are indicated to recollect plants. These aspects are interconnected and could be fundamental for a rational use and management of plant resources.

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EPA Pesticide Factsheets

2018-05-18

The Integrated Grants Management System (IGMS) is a web-based system that contains information on the recipient of the grant, fellowship, cooperative agreement and interagency agreement, including the name of the entity accepting the award.

7 CFR 1466.3 - Definitions.

Code of Federal Regulations, 2012 CFR

2012-01-01

...) means an individual, private-sector entity, or public agency certified by NRCS to provide technical...,” “land conservation committee,” “natural resource district,” or similar name. Conservation Innovation...

7 CFR 1466.3 - Definitions.

Code of Federal Regulations, 2013 CFR

2013-01-01

...) means an individual, private-sector entity, or public agency certified by NRCS to provide technical...,” “land conservation committee,” “natural resource district,” or similar name. Conservation Innovation...

7 CFR 1466.3 - Definitions.

Code of Federal Regulations, 2014 CFR

2014-01-01

...) means an individual, private-sector entity, or public agency certified by NRCS to provide technical...,” “land conservation committee,” “natural resource district,” or similar name. Conservation Innovation...

47 CFR 13.7 - Classification of operator licenses and endorsements.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 47 Telecommunication 1 2011-10-01 2011-10-01 false Classification of operator licenses and... OPERATORS General § 13.7 Classification of operator licenses and endorsements. (a) Commercial radio operator... license's ITU classification, if different from its name, is given in parentheses. (1) First Class...

A System to Automatically Classify and Name Any Individual Genome-Sequenced Organism Independently of Current Biological Classification and Nomenclature

PubMed Central

Song, Yuhyun; Leman, Scotland; Monteil, Caroline L.; Heath, Lenwood S.; Vinatzer, Boris A.

2014-01-01

A broadly accepted and stable biological classification system is a prerequisite for biological sciences. It provides the means to describe and communicate about life without ambiguity. Current biological classification and nomenclature use the species as the basic unit and require lengthy and laborious species descriptions before newly discovered organisms can be assigned to a species and be named. The current system is thus inadequate to classify and name the immense genetic diversity within species that is now being revealed by genome sequencing on a daily basis. To address this lack of a general intra-species classification and naming system adequate for today’s speed of discovery of new diversity, we propose a classification and naming system that is exclusively based on genome similarity and that is suitable for automatic assignment of codes to any genome-sequenced organism without requiring any phenotypic or phylogenetic analysis. We provide examples demonstrating that genome similarity-based codes largely align with current taxonomic groups at many different levels in bacteria, animals, humans, plants, and viruses. Importantly, the proposed approach is only slightly affected by the order of code assignment and can thus provide codes that reflect similarity between organisms and that do not need to be revised upon discovery of new diversity. We envision genome similarity-based codes to complement current biological nomenclature and to provide a universal means to communicate unambiguously about any genome-sequenced organism in fields as diverse as biodiversity research, infectious disease control, human and microbial forensics, animal breed and plant cultivar certification, and human ancestry research. PMID:24586551

Apocrine hidradenocarcinoma of the scalp: a classification conundrum.

PubMed

Cohen, Marc; Cassarino, David S; Shih, Hubert B; Abemayor, Elliot; St John, Maie

2009-03-01

The classification of malignant sweat gland lesions is complex. Traditionally, cutaneous sweat gland tumors have been classified by either eccrine or apocrine features. A case report of a 33-year-old Hispanic man with a left scalp mass diagnosed as a malignancy of adnexal origin preoperatively is discussed. After presentation at our multidisciplinary tumor board, excision with ipsilateral neck dissection was undertaken. Final pathology revealed an apocrine hidradenocarcinoma. The classification and behavior of this entity are discussed in this report. Apocrine hidradenocarcinoma can be viewed as an aggressive malignant lesion of cutaneous sweat glands on a spectrum that involves both eccrine and apoeccrine lesions.

Apocrine Hidradenocarcinoma of the Scalp: A Classification Conundrum

PubMed Central

Cassarino, David S.; Shih, Hubert B.; Abemayor, Elliot; John, Maie St.

2008-01-01

Introduction The classification of malignant sweat gland lesions is complex. Traditionally, cutaneous sweat gland tumors have been classified by either eccrine or apocrine features. Methods A case report of a 33-year-old Hispanic man with a left scalp mass diagnosed as a malignancy of adnexal origin preoperatively is discussed. After presentation at our multidisciplinary tumor board, excision with ipsilateral neck dissection was undertaken. Results Final pathology revealed an apocrine hidradenocarcinoma. The classification and behavior of this entity are discussed in this report. Conclusion Apocrine hidradenocarcinoma can be viewed as an aggressive malignant lesion of cutaneous sweat glands on a spectrum that involves both eccrine and apoeccrine lesions. PMID:20596988

[WHO classification of head and neck tumours 2017: Main novelties and update of diagnostic methods].

PubMed

Sarradin, Victor; Siegfried, Aurore; Uro-Coste, Emmanuelle; Delord, Jean-Pierre

2018-06-01

The publication of the new WHO classification of head and neck tumours in 2017 brought major modifications. Especially, a new chapter is dedicated to the oropharynx, focusing on the description of squamous cell carcinoma induced by the virus Human Papilloma Virus (HPV), and new entities of tumors are described in nasal cavities and sinuses. In this article are presented the novelties and main changes of this new classification, as well as the updates of the diagnostic methods (immunohistochemistry, cytogenetics or molecular biology). Copyright © 2018 Société Française du Cancer. Published by Elsevier Masson SAS. All rights reserved.

IGMS Overview

EPA Pesticide Factsheets

The Integrated Grants Management System (IGMS) is a web-based system that contains information on the recipient of the grant, fellowship, cooperative agreement and interagency agreement, including the name of the entity accepting the award.

IGMS Model

EPA Pesticide Factsheets

The Integrated Grants Management System (IGMS) is a web-based system that contains information on the recipient of the grant, fellowship, cooperative agreement and interagency agreement, including the name of the entity accepting the award.

Entity recognition in the biomedical domain using a hybrid approach.

PubMed

Basaldella, Marco; Furrer, Lenz; Tasso, Carlo; Rinaldi, Fabio

2017-11-09

This article describes a high-recall, high-precision approach for the extraction of biomedical entities from scientific articles. The approach uses a two-stage pipeline, combining a dictionary-based entity recognizer with a machine-learning classifier. First, the OGER entity recognizer, which has a bias towards high recall, annotates the terms that appear in selected domain ontologies. Subsequently, the Distiller framework uses this information as a feature for a machine learning algorithm to select the relevant entities only. For this step, we compare two different supervised machine-learning algorithms: Conditional Random Fields and Neural Networks. In an in-domain evaluation using the CRAFT corpus, we test the performance of the combined systems when recognizing chemicals, cell types, cellular components, biological processes, molecular functions, organisms, proteins, and biological sequences. Our best system combines dictionary-based candidate generation with Neural-Network-based filtering. It achieves an overall precision of 86% at a recall of 60% on the named entity recognition task, and a precision of 51% at a recall of 49% on the concept recognition task. These results are to our knowledge the best reported so far in this particular task.

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

A database of natural products and chemical entities from marine habitat

PubMed Central

Babu, Padavala Ajay; Puppala, Suma Sree; Aswini, Satyavarapu Lakshmi; Vani, Metta Ramya; Kumar, Chinta Narasimha; Prasanna, Tallapragada

2008-01-01

Marine compound database consists of marine natural products and chemical entities, collected from various literature sources, which are known to possess bioactivity against human diseases. The database is constructed using html code. The 12 categories of 182 compounds are provided with the source, compound name, 2-dimensional structure, bioactivity and clinical trial information. The database is freely available online and can be accessed at http://www.progenebio.in/mcdb/index.htm PMID:19238254

New daily persistent headache: An evolving entity.

PubMed

Uniyal, Ravi; Paliwal, Vimal Kumar; Anand, Sucharita; Ambesh, Paurush

2018-01-01

New daily persistent headache (NDPH) is characterized by an abrupt onset of headache that becomes a daily entity, is unremitting and continuous from the onset, and lasts for more than 3 months. Dr Walter Vanast first described NDPH in the year 1986. Originally, it was proposed as a chronic daily headache but it was placed under "other primary headaches" in the International Classification of Headache Disorder Second Edition (ICHD 2nd edition). However, with evolving literature and better understanding of its clinical characteristics, it was classified as a "chronic daily headache" in the ICHD 3 rd edition beta. There are still many knowledge-gaps regarding the underlying cause, pathophysiology, natural history and treatment of NDPH. This review tries to revisit the entity and discusses the current status of understanding regarding NDPH.

12 CFR 1229.1 - Definitions.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 12 Banks and Banking 7 2010-01-01 2010-01-01 false Definitions. 1229.1 Section 1229.1 Banks and Banking FEDERAL HOUSING FINANCE AGENCY ENTITY REGULATIONS CAPITAL CLASSIFICATIONS AND PROMPT CORRECTIVE...; (viii) Strategic Planning officer or an equivalent employee; (ix) Internal Audit officer or an...

15 CFR 4a.8 - Access to classified information by individuals outside the Government.

Code of Federal Regulations, 2010 CFR

2010-01-01

... Commerce CLASSIFICATION, DECLASSIFICATION, AND PUBLIC AVAILABILITY OF NATIONAL SECURITY INFORMATION § 4a.8 Access to classified information by individuals outside the Government. (a) Industrial, Educational, and Commercial Entities. Certain bidders, contractors, grantees, educational, scientific, or industrial...

EPA Grants Information

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The Integrated Grants Management System (IGMS) is a web-based system that contains information on the recipient of the grant, fellowship, cooperative agreement and interagency agreement, including the name of the entity accepting the award.

GENE-07. MOLECULAR NEUROPATHOLOGY 2.0 - INCREASING DIAGNOSTIC ACCURACY IN PEDIATRIC NEUROONCOLOGY

PubMed Central

Sturm, Dominik; Jones, David T.W.; Capper, David; Sahm, Felix; von Deimling, Andreas; Rutkoswki, Stefan; Warmuth-Metz, Monika; Bison, Brigitte; Gessi, Marco; Pietsch, Torsten; Pfister, Stefan M.

2017-01-01

Abstract The classification of central nervous system (CNS) tumors into clinically and biologically distinct entities and subgroups is challenging. Children and adolescents can be affected by >100 histological variants with very variable outcomes, some of which are exceedingly rare. The current WHO classification has introduced a number of novel molecular markers to aid routine neuropathological diagnostics, and DNA methylation profiling is emerging as a powerful tool to distinguish CNS tumor classes. The Molecular Neuropathology 2.0 study aims to integrate genome wide (epi-)genetic diagnostics with reference neuropathological assessment for all newly-diagnosed pediatric brain tumors in Germany. To date, >350 patients have been enrolled. A molecular diagnosis is established by epigenetic tumor classification through DNA methylation profiling and targeted panel sequencing of >130 genes to detect diagnostically and/or therapeutically useful DNA mutations, structural alterations, and fusion events. Results are aligned with the reference neuropathological diagnosis, and discrepant findings are discussed in a multi-disciplinary tumor board including reference neuroradiological evaluation. Ten FFPE sections as input material are sufficient to establish a molecular diagnosis in >95% of tumors. Alignment with reference pathology results in four broad categories: a) concordant classification (~77%), b) discrepant classification resolvable by tumor board discussion and/or additional data (~5%), c) discrepant classification without currently available options to resolve (~8%), and d) cases currently unclassifiable by molecular diagnostics (~10%). Discrepancies are enriched in certain histopathological entities, such as histological high grade gliomas with a molecularly low grade profile. Gene panel sequencing reveals predisposing germline events in ~10% of patients. Genome wide (epi-)genetic analyses add a valuable layer of information to routine neuropathological diagnostics. Our study provides insight into CNS tumors with divergent histopathological and molecular classification, opening new avenues for research discoveries and facilitating optimization of clinical management for affected patients in the future.

New Brain Tumor Entities Emerge from Molecular Classification of CNS-PNETs.

PubMed

Sturm, Dominik; Orr, Brent A; Toprak, Umut H; Hovestadt, Volker; Jones, David T W; Capper, David; Sill, Martin; Buchhalter, Ivo; Northcott, Paul A; Leis, Irina; Ryzhova, Marina; Koelsche, Christian; Pfaff, Elke; Allen, Sariah J; Balasubramanian, Gnanaprakash; Worst, Barbara C; Pajtler, Kristian W; Brabetz, Sebastian; Johann, Pascal D; Sahm, Felix; Reimand, Jüri; Mackay, Alan; Carvalho, Diana M; Remke, Marc; Phillips, Joanna J; Perry, Arie; Cowdrey, Cynthia; Drissi, Rachid; Fouladi, Maryam; Giangaspero, Felice; Łastowska, Maria; Grajkowska, Wiesława; Scheurlen, Wolfram; Pietsch, Torsten; Hagel, Christian; Gojo, Johannes; Lötsch, Daniela; Berger, Walter; Slavc, Irene; Haberler, Christine; Jouvet, Anne; Holm, Stefan; Hofer, Silvia; Prinz, Marco; Keohane, Catherine; Fried, Iris; Mawrin, Christian; Scheie, David; Mobley, Bret C; Schniederjan, Matthew J; Santi, Mariarita; Buccoliero, Anna M; Dahiya, Sonika; Kramm, Christof M; von Bueren, André O; von Hoff, Katja; Rutkowski, Stefan; Herold-Mende, Christel; Frühwald, Michael C; Milde, Till; Hasselblatt, Martin; Wesseling, Pieter; Rößler, Jochen; Schüller, Ulrich; Ebinger, Martin; Schittenhelm, Jens; Frank, Stephan; Grobholz, Rainer; Vajtai, Istvan; Hans, Volkmar; Schneppenheim, Reinhard; Zitterbart, Karel; Collins, V Peter; Aronica, Eleonora; Varlet, Pascale; Puget, Stephanie; Dufour, Christelle; Grill, Jacques; Figarella-Branger, Dominique; Wolter, Marietta; Schuhmann, Martin U; Shalaby, Tarek; Grotzer, Michael; van Meter, Timothy; Monoranu, Camelia-Maria; Felsberg, Jörg; Reifenberger, Guido; Snuderl, Matija; Forrester, Lynn Ann; Koster, Jan; Versteeg, Rogier; Volckmann, Richard; van Sluis, Peter; Wolf, Stephan; Mikkelsen, Tom; Gajjar, Amar; Aldape, Kenneth; Moore, Andrew S; Taylor, Michael D; Jones, Chris; Jabado, Nada; Karajannis, Matthias A; Eils, Roland; Schlesner, Matthias; Lichter, Peter; von Deimling, Andreas; Pfister, Stefan M; Ellison, David W; Korshunov, Andrey; Kool, Marcel

2016-02-25

Primitive neuroectodermal tumors of the central nervous system (CNS-PNETs) are highly aggressive, poorly differentiated embryonal tumors occurring predominantly in young children but also affecting adolescents and adults. Herein, we demonstrate that a significant proportion of institutionally diagnosed CNS-PNETs display molecular profiles indistinguishable from those of various other well-defined CNS tumor entities, facilitating diagnosis and appropriate therapy for patients with these tumors. From the remaining fraction of CNS-PNETs, we identify four new CNS tumor entities, each associated with a recurrent genetic alteration and distinct histopathological and clinical features. These new molecular entities, designated "CNS neuroblastoma with FOXR2 activation (CNS NB-FOXR2)," "CNS Ewing sarcoma family tumor with CIC alteration (CNS EFT-CIC)," "CNS high-grade neuroepithelial tumor with MN1 alteration (CNS HGNET-MN1)," and "CNS high-grade neuroepithelial tumor with BCOR alteration (CNS HGNET-BCOR)," will enable meaningful clinical trials and the development of therapeutic strategies for patients affected by poorly differentiated CNS tumors. Copyright © 2016 Elsevier Inc. All rights reserved.

IGMS Construction Grants Overview

EPA Pesticide Factsheets

The Integrated Grants Management System (IGMS) is a web-based system that contains information on the recipient of the grant, fellowship, cooperative agreement and interagency agreement, including the name of the entity accepting the award.

IGMS Search User Guide

EPA Pesticide Factsheets

The Integrated Grants Management System (IGMS) is a web-based system that contains information on the recipient of the grant, fellowship, cooperative agreement and interagency agreement, including the name of the entity accepting the award.

77 FR 9021 - Regulations Relating to Information Reporting by Foreign Financial Institutions and Withholding...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-02-15

..., address, and taxpayer identifying number (TIN) of each account holder who is a specified U.S. person (or, in the case of an account holder that is a U.S. owned foreign entity, the name, address, and TIN of... that such beneficial owner does not have any substantial U.S. owners, or the name, address, and TIN of...

Rendering of Names of Corporate Bodies. Subject Analysis, With Special Reference to Social Sciences. Documentation Systems for Industry (8th Annual Seminar). Part 1: Papers.

ERIC Educational Resources Information Center

Documentation Research and Training Centre, Bangalore (India).

The four sections of the report cover the topics of cataloging, subject analysis, documentation systems for industry and the Documentation Research and Training Centre (DRTC) research report for 1970. The cataloging section covers the conflicts of cataloging, recall, corporate bodies, titles, publishers series and the entity name. The subject…

76 FR 38160 - Pesticide Products; Registration Applications

Federal Register 2010, 2011, 2012, 2013, 2014

2011-06-29

.... Potentially affected entities may include, but are not limited to: Crop production (NAICS code 111). Animal production (NAICS code 112). Food manufacturing (NAICS code 311). Pesticide manufacturing (NAICS code 32532... classification/Use: For control of certain diseases in almond, grape (small fruit vine climbing group, except...

24 CFR 58.37 - Environmental impact statement determinations.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 24 Housing and Urban Development 1 2010-04-01 2010-04-01 false Environmental impact statement... Classification § 58.37 Environmental impact statement determinations. (a) An EIS is required when the project is... and Urban Development ENVIRONMENTAL REVIEW PROCEDURES FOR ENTITIES ASSUMING HUD ENVIRONMENTAL...

Malunion after midshaft clavicle fractures in adults

PubMed Central

Burger, Bart J; Pöll, Rudolf G; de Gast, Arthur; Robinson, C Michael

2010-01-01

This is an overview of the current literature on malunion after midshaft clavicle fracture. Anatomy, trauma mechanism, classification, incidence, symptoms, prevention, and treatment options are all discussed. The conclusion is that clavicle malunion is a distinct clinical entity that can be treated successfully. PMID:20367423

The conundrum of juvenile psoriatic arthritis.

PubMed

Ravelli, Angelo; Consolaro, Alessandro; Schiappapietra, Benedetta; Martini, Alberto

2015-01-01

Juvenile psoriatic arthritis (JPsA) has provided paediatric rheumatologists with a controversial topic for many years. The principal area of contention centres on the discordance between its treatment as a single diagnostic category in current classification schemes and the demonstration of its heterogeneous nature. A further point of debate is the distinctiveness of JPsA as an entity. Owing to these uncertainties, the concept of JPsA has evolved over the years and there have been several changes in its definition and diagnostic criteria. Recently, strong evidence has been provided that the spectrum of JPsA include at least two distinct subgroups, one that has the same characteristics as early-onset ANA-positive JIA, and another that is part of the spectrum of spondyloarthropathies and resembles the forms of psoriatic arthritis in adults that belong to the same disease family. These findings call for a revision of the classification of childhood arthritis, that refutes the assumptions that children with JPsA constitute a single homogeneous population and that JPsA should be considered an individual disease entity.

A statistical approach to combining multisource information in one-class classifiers

DOE PAGES

Simonson, Katherine M.; Derek West, R.; Hansen, Ross L.; ...

2017-06-08

A new method is introduced in this paper for combining information from multiple sources to support one-class classification. The contributing sources may represent measurements taken by different sensors of the same physical entity, repeated measurements by a single sensor, or numerous features computed from a single measured image or signal. The approach utilizes the theory of statistical hypothesis testing, and applies Fisher's technique for combining p-values, modified to handle nonindependent sources. Classifier outputs take the form of fused p-values, which may be used to gauge the consistency of unknown entities with one or more class hypotheses. The approach enables rigorousmore » assessment of classification uncertainties, and allows for traceability of classifier decisions back to the constituent sources, both of which are important for high-consequence decision support. Application of the technique is illustrated in two challenge problems, one for skin segmentation and the other for terrain labeling. Finally, the method is seen to be particularly effective for relatively small training samples.« less

A statistical approach to combining multisource information in one-class classifiers

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

Simonson, Katherine M.; Derek West, R.; Hansen, Ross L.

A new method is introduced in this paper for combining information from multiple sources to support one-class classification. The contributing sources may represent measurements taken by different sensors of the same physical entity, repeated measurements by a single sensor, or numerous features computed from a single measured image or signal. The approach utilizes the theory of statistical hypothesis testing, and applies Fisher's technique for combining p-values, modified to handle nonindependent sources. Classifier outputs take the form of fused p-values, which may be used to gauge the consistency of unknown entities with one or more class hypotheses. The approach enables rigorousmore » assessment of classification uncertainties, and allows for traceability of classifier decisions back to the constituent sources, both of which are important for high-consequence decision support. Application of the technique is illustrated in two challenge problems, one for skin segmentation and the other for terrain labeling. Finally, the method is seen to be particularly effective for relatively small training samples.« less

DNA methylation-based classification of central nervous system tumours.

PubMed

Capper, David; Jones, David T W; Sill, Martin; Hovestadt, Volker; Schrimpf, Daniel; Sturm, Dominik; Koelsche, Christian; Sahm, Felix; Chavez, Lukas; Reuss, David E; Kratz, Annekathrin; Wefers, Annika K; Huang, Kristin; Pajtler, Kristian W; Schweizer, Leonille; Stichel, Damian; Olar, Adriana; Engel, Nils W; Lindenberg, Kerstin; Harter, Patrick N; Braczynski, Anne K; Plate, Karl H; Dohmen, Hildegard; Garvalov, Boyan K; Coras, Roland; Hölsken, Annett; Hewer, Ekkehard; Bewerunge-Hudler, Melanie; Schick, Matthias; Fischer, Roger; Beschorner, Rudi; Schittenhelm, Jens; Staszewski, Ori; Wani, Khalida; Varlet, Pascale; Pages, Melanie; Temming, Petra; Lohmann, Dietmar; Selt, Florian; Witt, Hendrik; Milde, Till; Witt, Olaf; Aronica, Eleonora; Giangaspero, Felice; Rushing, Elisabeth; Scheurlen, Wolfram; Geisenberger, Christoph; Rodriguez, Fausto J; Becker, Albert; Preusser, Matthias; Haberler, Christine; Bjerkvig, Rolf; Cryan, Jane; Farrell, Michael; Deckert, Martina; Hench, Jürgen; Frank, Stephan; Serrano, Jonathan; Kannan, Kasthuri; Tsirigos, Aristotelis; Brück, Wolfgang; Hofer, Silvia; Brehmer, Stefanie; Seiz-Rosenhagen, Marcel; Hänggi, Daniel; Hans, Volkmar; Rozsnoki, Stephanie; Hansford, Jordan R; Kohlhof, Patricia; Kristensen, Bjarne W; Lechner, Matt; Lopes, Beatriz; Mawrin, Christian; Ketter, Ralf; Kulozik, Andreas; Khatib, Ziad; Heppner, Frank; Koch, Arend; Jouvet, Anne; Keohane, Catherine; Mühleisen, Helmut; Mueller, Wolf; Pohl, Ute; Prinz, Marco; Benner, Axel; Zapatka, Marc; Gottardo, Nicholas G; Driever, Pablo Hernáiz; Kramm, Christof M; Müller, Hermann L; Rutkowski, Stefan; von Hoff, Katja; Frühwald, Michael C; Gnekow, Astrid; Fleischhack, Gudrun; Tippelt, Stephan; Calaminus, Gabriele; Monoranu, Camelia-Maria; Perry, Arie; Jones, Chris; Jacques, Thomas S; Radlwimmer, Bernhard; Gessi, Marco; Pietsch, Torsten; Schramm, Johannes; Schackert, Gabriele; Westphal, Manfred; Reifenberger, Guido; Wesseling, Pieter; Weller, Michael; Collins, Vincent Peter; Blümcke, Ingmar; Bendszus, Martin; Debus, Jürgen; Huang, Annie; Jabado, Nada; Northcott, Paul A; Paulus, Werner; Gajjar, Amar; Robinson, Giles W; Taylor, Michael D; Jaunmuktane, Zane; Ryzhova, Marina; Platten, Michael; Unterberg, Andreas; Wick, Wolfgang; Karajannis, Matthias A; Mittelbronn, Michel; Acker, Till; Hartmann, Christian; Aldape, Kenneth; Schüller, Ulrich; Buslei, Rolf; Lichter, Peter; Kool, Marcel; Herold-Mende, Christel; Ellison, David W; Hasselblatt, Martin; Snuderl, Matija; Brandner, Sebastian; Korshunov, Andrey; von Deimling, Andreas; Pfister, Stefan M

2018-03-22

Accurate pathological diagnosis is crucial for optimal management of patients with cancer. For the approximately 100 known tumour types of the central nervous system, standardization of the diagnostic process has been shown to be particularly challenging-with substantial inter-observer variability in the histopathological diagnosis of many tumour types. Here we present a comprehensive approach for the DNA methylation-based classification of central nervous system tumours across all entities and age groups, and demonstrate its application in a routine diagnostic setting. We show that the availability of this method may have a substantial impact on diagnostic precision compared to standard methods, resulting in a change of diagnosis in up to 12% of prospective cases. For broader accessibility, we have designed a free online classifier tool, the use of which does not require any additional onsite data processing. Our results provide a blueprint for the generation of machine-learning-based tumour classifiers across other cancer entities, with the potential to fundamentally transform tumour pathology.

46 CFR 515.34 - Regulated Persons Index.

Code of Federal Regulations, 2010 CFR

2010-10-01

... Commission § 515.34 Regulated Persons Index. The Regulated Persons Index is a database containing the names...-regulated entities. The database may be purchased for $108 by contacting the Bureau of Certification and...

46 CFR 515.34 - Regulated Persons Index.

Code of Federal Regulations, 2013 CFR

2013-10-01

... Commission § 515.34 Regulated Persons Index. The Regulated Persons Index is a database containing the names...-regulated entities. The database may be purchased for $108 by contacting the Bureau of Certification and...

46 CFR 515.34 - Regulated Persons Index.

Code of Federal Regulations, 2014 CFR

2014-10-01

... Commission § 515.34 Regulated Persons Index. The Regulated Persons Index is a database containing the names...-regulated entities. The database may be purchased for $108 by contacting the Bureau of Certification and...

46 CFR 515.34 - Regulated Persons Index.

Code of Federal Regulations, 2012 CFR

2012-10-01

... Commission § 515.34 Regulated Persons Index. The Regulated Persons Index is a database containing the names...-regulated entities. The database may be purchased for $108 by contacting the Bureau of Certification and...

46 CFR 515.34 - Regulated Persons Index.

Code of Federal Regulations, 2011 CFR

2011-10-01

... Commission § 515.34 Regulated Persons Index. The Regulated Persons Index is a database containing the names...-regulated entities. The database may be purchased for $108 by contacting the Bureau of Certification and...

Search | IGMS | Envirofacts | US EPA

EPA Pesticide Factsheets

2016-02-23

The Integrated Grants Management System (IGMS) is a web-based system that contains information on the recipient of the grant, fellowship, cooperative agreement and interagency agreement, including the name of the entity accepting the award.

[Chronic transplant nephropathy].

PubMed

Campistol Plana, J M

2008-01-01

In 2007 there were important scientific contributions in the field of kidney transplant and specifically in chronic transplant nephropathy (interstitial fibrosis and tubular atrophy). A new nomenclature and classification of chronic kidney disease was probably the most important contribution in this entity. Use of the C4d stain has allowed the concepts of glomerulopathy to be updated and to reveal the frequency of this entity and its impact in kidney transplant. Finally, two experimental studies provide new perspectives on the treatment of chronic kidney disease such as the use of statins or the use of pyridoxamine to block glycation end products.

Breast cancer - one term, many entities?

PubMed

Bertos, Nicholas R; Park, Morag

2011-10-01

Breast cancer, rather than constituting a monolithic entity, comprises heterogeneous tumors with different clinical characteristics, disease courses, and responses to specific treatments. Tumor-intrinsic features, including classical histological and immunopathological classifications as well as more recently described molecular subtypes, separate breast tumors into multiple groups. Tumor-extrinsic features, including microenvironmental configuration, also have prognostic significance and further expand the list of tumor-defining variables. A better understanding of the features underlying heterogeneity, as well as of the mechanisms and consequences of their interactions, is essential to improve targeting of existing therapies and to develop novel agents addressing specific combinations of features.

Searching for the elusive neural substrates of body part terms: a neuropsychological study.

PubMed

Kemmerer, David; Tranel, Daniel

2008-06-01

Previous neuropsychological studies suggest that, compared to other categories of concrete entities, lexical and conceptual aspects of body part knowledge are frequently spared in brain-damaged patients. To further investigate this issue, we administered a battery of 12 tests assessing lexical and conceptual aspects of body part knowledge to 104 brain-damaged patients with lesions distributed throughout the telencephalon. There were two main outcomes. First, impaired oral naming of body parts, attributable to a disturbance of the mapping between lexical-semantic and lexical-phonological structures, was most reliably and specifically associated with lesions in the left frontal opercular and anterior/inferior parietal opercular cortices and in the white matter underlying these regions (8 patients). Also, 1 patient with body part anomia had a left occipital lesion that included the "extrastriate body area" (EBA). Second, knowledge of the meanings of body part terms was remarkably resistant to impairment, regardless of lesion site; in fact, we did not uncover a single patient who exhibited significantly impaired understanding of the meanings of these terms. In the 9 patients with body part anomia, oral naming of concrete entities was evaluated, and this revealed that 4 patients had disproportionately worse naming of body parts relative to other types of concrete entities. Taken together, these findings extend previous neuropsychological and functional neuroimaging studies of body part knowledge and add to our growing understanding of the nuances of how different linguistic and conceptual categories are operated by left frontal and parietal structures.

Searching for the Elusive Neural Substrates of Body Part Terms: A Neuropsychological Study

PubMed Central

Kemmerer, David; Tranel, Daniel

2010-01-01

Previous neuropsychological studies suggest that, compared to other categories of concrete entities, lexical and conceptual aspects of body part knowledge are frequently spared in brain-damaged patients. To further investigate this issue, we administered a battery of 12 tests assessing lexical and conceptual aspects of body part knowledge to 104 brain-damaged patients with lesions distributed throughout the telencephalon. There were two main outcomes. First, impaired oral naming of body parts, attributable to a disturbance of the mapping between lexical-semantic and lexical-phonological structures, was most reliably and specifically associated with lesions in the left frontal opercular and anterior/inferior parietal opercular cortices, and in the white matter underlying these regions (8 patients). Also, one patient with body part anomia had a left occipital lesion that included the “extrastriate body area” (EBA). Second, knowledge of the meanings of body part terms was remarkably resistant to impairment, regardless of lesion site; in fact, we did not uncover a single patient who exhibited significantly impaired understanding of the meanings of these terms. In the 9 patients with body part anomia, oral naming of concrete entities was evaluated, and this revealed that 4 patients had disproportionately worse naming of body parts relative to other types of concrete entities. Taken together, these findings extend previous neuropsychological and functional neuroimaging studies of body part knowledge, and add to our growing understanding of the nuances of how different linguistic and conceptual categories are operated by left frontal and parietal structures. PMID:18608319

[Definition and classification of pulmonary arterial hypertension].

PubMed

Nakanishi, Norifumi

2008-11-01

Pulmonary hypertension(PH) is a disorder that may occur either in the setting of a variety of underlying medical conditions or as a disease that uniquely affects the pulmonary vasculature. Because an accurate diagnosis of PH in a patient is essential to establish an effective treatment, a classification of PH has been helpful. The first classification, established at WHO Symposium in 1973, classified PH into groups based on the known cause and defined primary pulmonary hypertension (PPH) as a separate entity of unknown cause. In 1998, the second World Symposium on PPH was held in Evian. Evian classification introduced the concept of conditions that directly affected the pulmonary vasculature (i.e., PAH), which included PPH. In 2003, the third World Symposium on PAH convened in Venice. In Venice classification, the term 'PPH' was abandoned in favor of 'idiopathic' within the group of disease known as 'PAH'.

Traditional knowledge among Zapotecs of Sierra Madre Del Sur, Oaxaca. Does it represent a base for plant resources management and conservation?

PubMed Central

2012-01-01

Traditional classification systems represent cognitive processes of human cultures in the world. It synthesizes specific conceptions of nature, as well as cumulative learning, beliefs and customs that are part of a particular human community or society. Traditional knowledge has been analyzed from different viewpoints, one of which corresponds to the analysis of ethnoclassifications. In this work, a brief analysis of the botanical traditional knowledge among Zapotecs of the municipality of San Agustin Loxicha, Oaxaca was conducted. The purposes of this study were: a) to analyze the traditional ecological knowledge of local plant resources through the folk classification of both landscapes and plants and b) to determine the role that this knowledge has played in plant resource management and conservation. The study was developed in five communities of San Agustín Loxicha. From field trips, plant specimens were collected and showed to local people in order to get the Spanish or Zapotec names; through interviews with local people, we obtained names and identified classification categories of plants, vegetation units, and soil types. We found a logic structure in Zapotec plant names, based on linguistic terms, as well as morphological and ecological caracteristics. We followed the classification principles proposed by Berlin [6] in order to build a hierarchical structure of life forms, names and other characteristics mentioned by people. We recorded 757 plant names. Most of them (67%) have an equivalent Zapotec name and the remaining 33% had mixed names with Zapotec and Spanish terms. Plants were categorized as native plants, plants introduced in pre-Hispanic times, or plants introduced later. All of them are grouped in a hierarchical classification, which include life form, generic, specific, and varietal categories. Monotypic and polytypic names are used to further classify plants. This holistic classification system plays an important role for local people in many aspects: it helps to organize and make sense of the diversity, to understand the interrelation among plants–soil–vegetation and to classify their physical space since they relate plants with a particular vegetation unit and a kind of soil. The locals also make a rational use of these elements, because they know which crops can grow in any vegetation unit, or which places are indicated to recollect plants. These aspects are interconnected and could be fundamental for a rational use and management of plant resources. PMID:22789155

TaggerOne: joint named entity recognition and normalization with semi-Markov Models

PubMed Central

Leaman, Robert; Lu, Zhiyong

2016-01-01

Motivation: Text mining is increasingly used to manage the accelerating pace of the biomedical literature. Many text mining applications depend on accurate named entity recognition (NER) and normalization (grounding). While high performing machine learning methods trainable for many entity types exist for NER, normalization methods are usually specialized to a single entity type. NER and normalization systems are also typically used in a serial pipeline, causing cascading errors and limiting the ability of the NER system to directly exploit the lexical information provided by the normalization. Methods: We propose the first machine learning model for joint NER and normalization during both training and prediction. The model is trainable for arbitrary entity types and consists of a semi-Markov structured linear classifier, with a rich feature approach for NER and supervised semantic indexing for normalization. We also introduce TaggerOne, a Java implementation of our model as a general toolkit for joint NER and normalization. TaggerOne is not specific to any entity type, requiring only annotated training data and a corresponding lexicon, and has been optimized for high throughput. Results: We validated TaggerOne with multiple gold-standard corpora containing both mention- and concept-level annotations. Benchmarking results show that TaggerOne achieves high performance on diseases (NCBI Disease corpus, NER f-score: 0.829, normalization f-score: 0.807) and chemicals (BioCreative 5 CDR corpus, NER f-score: 0.914, normalization f-score 0.895). These results compare favorably to the previous state of the art, notwithstanding the greater flexibility of the model. We conclude that jointly modeling NER and normalization greatly improves performance. Availability and Implementation: The TaggerOne source code and an online demonstration are available at: http://www.ncbi.nlm.nih.gov/bionlp/taggerone Contact: zhiyong.lu@nih.gov Supplementary information: Supplementary data are available at Bioinformatics online. PMID:27283952

TaggerOne: joint named entity recognition and normalization with semi-Markov Models.

PubMed

Leaman, Robert; Lu, Zhiyong

2016-09-15

Text mining is increasingly used to manage the accelerating pace of the biomedical literature. Many text mining applications depend on accurate named entity recognition (NER) and normalization (grounding). While high performing machine learning methods trainable for many entity types exist for NER, normalization methods are usually specialized to a single entity type. NER and normalization systems are also typically used in a serial pipeline, causing cascading errors and limiting the ability of the NER system to directly exploit the lexical information provided by the normalization. We propose the first machine learning model for joint NER and normalization during both training and prediction. The model is trainable for arbitrary entity types and consists of a semi-Markov structured linear classifier, with a rich feature approach for NER and supervised semantic indexing for normalization. We also introduce TaggerOne, a Java implementation of our model as a general toolkit for joint NER and normalization. TaggerOne is not specific to any entity type, requiring only annotated training data and a corresponding lexicon, and has been optimized for high throughput. We validated TaggerOne with multiple gold-standard corpora containing both mention- and concept-level annotations. Benchmarking results show that TaggerOne achieves high performance on diseases (NCBI Disease corpus, NER f-score: 0.829, normalization f-score: 0.807) and chemicals (BioCreative 5 CDR corpus, NER f-score: 0.914, normalization f-score 0.895). These results compare favorably to the previous state of the art, notwithstanding the greater flexibility of the model. We conclude that jointly modeling NER and normalization greatly improves performance. The TaggerOne source code and an online demonstration are available at: http://www.ncbi.nlm.nih.gov/bionlp/taggerone zhiyong.lu@nih.gov Supplementary data are available at Bioinformatics online. Published by Oxford University Press 2016. This work is written by US Government employees and is in the public domain in the US.

Transfer learning for biomedical named entity recognition with neural networks.

PubMed

Giorgi, John M; Bader, Gary D

2018-06-01

The explosive increase of biomedical literature has made information extraction an increasingly important tool for biomedical research. A fundamental task is the recognition of biomedical named entities in text (BNER) such as genes/proteins, diseases, and species. Recently, a domain-independent method based on deep learning and statistical word embeddings, called long short-term memory network-conditional random field (LSTM-CRF), has been shown to outperform state-of-the-art entity-specific BNER tools. However, this method is dependent on gold-standard corpora (GSCs) consisting of hand-labeled entities, which tend to be small but highly reliable. An alternative to GSCs are silver-standard corpora (SSCs), which are generated by harmonizing the annotations made by several automatic annotation systems. SSCs typically contain more noise than GSCs but have the advantage of containing many more training examples. Ideally, these corpora could be combined to achieve the benefits of both, which is an opportunity for transfer learning. In this work, we analyze to what extent transfer learning improves upon state-of-the-art results for BNER. We demonstrate that transferring a deep neural network (DNN) trained on a large, noisy SSC to a smaller, but more reliable GSC significantly improves upon state-of-the-art results for BNER. Compared to a state-of-the-art baseline evaluated on 23 GSCs covering four different entity classes, transfer learning results in an average reduction in error of approximately 11%. We found transfer learning to be especially beneficial for target data sets with a small number of labels (approximately 6000 or less). Source code for the LSTM-CRF is available athttps://github.com/Franck-Dernoncourt/NeuroNER/ and links to the corpora are available athttps://github.com/BaderLab/Transfer-Learning-BNER-Bioinformatics-2018/. john.giorgi@utoronto.ca. Supplementary data are available at Bioinformatics online.

Tremor entities and their classification: an update.

PubMed

Gövert, Felix; Deuschl, Günther

2015-08-01

This review focuses on important new findings in the field of tremor and illustrates the consequences for the current definition and classification of tremor. Since 1998 when the consensus criteria for tremor were proposed, new variants of tremors and new diagnostic methods were discovered that have changed particularly the concepts of essential tremor and dystonic tremor. Accumulating evidence exists that essential tremor is not a single entity rather different conditions that share the common symptom action tremor without other major abnormalities. Tremor is a common feature in patients with adult-onset focal dystonia and may involve several different body parts and forms of tremor. Recent advances, in particular, in the field of genetics, suggest that dystonic tremor may even be present without overt dystonia. Monosymptomatic asymmetric rest and postural tremor has been further delineated, and apart from tremor-dominant Parkinson's disease, there are several rare conditions including rest and action tremor with normal dopamine transporter imaging (scans without evidence of dopaminergic deficit) and essential tremor with tremor at rest. Increasing knowledge in the last decades changed the view on tremors and highlights several caveats in the current tremor classification. Given the ambiguous assignment between tremor phenomenology and tremor etiology, a more cautious definition of tremors on the basis of clinical assessment data is needed.

The ChEBI reference database and ontology for biologically relevant chemistry: enhancements for 2013.

PubMed

Hastings, Janna; de Matos, Paula; Dekker, Adriano; Ennis, Marcus; Harsha, Bhavana; Kale, Namrata; Muthukrishnan, Venkatesh; Owen, Gareth; Turner, Steve; Williams, Mark; Steinbeck, Christoph

2013-01-01

ChEBI (http://www.ebi.ac.uk/chebi) is a database and ontology of chemical entities of biological interest. Over the past few years, ChEBI has continued to grow steadily in content, and has added several new features. In addition to incorporating all user-requested compounds, our annotation efforts have emphasized immunology, natural products and metabolites in many species. All database entries are now 'is_a' classified within the ontology, meaning that all of the chemicals are available to semantic reasoning tools that harness the classification hierarchy. We have completely aligned the ontology with the Open Biomedical Ontologies (OBO) Foundry-recommended upper level Basic Formal Ontology. Furthermore, we have aligned our chemical classification with the classification of chemical-involving processes in the Gene Ontology (GO), and as a result of this effort, the majority of chemical-involving processes in GO are now defined in terms of the ChEBI entities that participate in them. This effort necessitated incorporating many additional biologically relevant compounds. We have incorporated additional data types including reference citations, and the species and component for metabolites. Finally, our website and web services have had several enhancements, most notably the provision of a dynamic new interactive graph-based ontology visualization.

24 CFR 58.32 - Project aggregation.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 24 Housing and Urban Development 1 2010-04-01 2010-04-01 false Project aggregation. 58.32 Section... Environmental Review Process: Documentation, Range of Activities, Project Aggregation and Classification § 58.32 Project aggregation. (a) A responsible entity must group together and evaluate as a single project all...

24 CFR 58.32 - Project aggregation.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 24 Housing and Urban Development 1 2011-04-01 2011-04-01 false Project aggregation. 58.32 Section... Environmental Review Process: Documentation, Range of Activities, Project Aggregation and Classification § 58.32 Project aggregation. (a) A responsible entity must group together and evaluate as a single project all...

24 CFR 58.32 - Project aggregation.

Code of Federal Regulations, 2014 CFR

2014-04-01

... 24 Housing and Urban Development 1 2014-04-01 2014-04-01 false Project aggregation. 58.32 Section... Environmental Review Process: Documentation, Range of Activities, Project Aggregation and Classification § 58.32 Project aggregation. (a) A responsible entity must group together and evaluate as a single project all...

24 CFR 58.32 - Project aggregation.

Code of Federal Regulations, 2012 CFR

2012-04-01

... 24 Housing and Urban Development 1 2012-04-01 2012-04-01 false Project aggregation. 58.32 Section... Environmental Review Process: Documentation, Range of Activities, Project Aggregation and Classification § 58.32 Project aggregation. (a) A responsible entity must group together and evaluate as a single project all...

New clinical practice guidelines on the classification, evaluation and management of childhood interstitial lung disease in infants: what do they mean?

PubMed

Wambach, Jennifer A; Young, Lisa R

2014-12-01

The American Thoracic Society (ATS) recently published a clinical practice guideline regarding the classification, evaluation, and management of childhood interstitial lung disease in infancy (chILD). As disease entities among infants with ILD are often distinct from forms seen in older children and adults, the guideline encourages an age-based classification system and focuses on the diagnostic approach to neonates and infants <2 years of age. The guideline reviews current evidence and recommendations for the evaluation, relevant genetic studies, and management of symptomatic infants. Here, we summarize the ATS guideline, highlight the major concepts, and discuss future strategies aimed at addressing current gaps in knowledge.

21 CFR 810.10 - Cease distribution and notification order.

Code of Federal Regulations, 2013 CFR

2013-04-01

..., including, where known: (i) The brand name of the device; (ii) The common name, classification name, or...) A copy of any written communication used by the person named in the order to notify health professionals and device user facilities; (7) A proposed strategy for complying with the cease distribution and...

21 CFR 810.10 - Cease distribution and notification order.

Code of Federal Regulations, 2012 CFR

2012-04-01

..., including, where known: (i) The brand name of the device; (ii) The common name, classification name, or...) A copy of any written communication used by the person named in the order to notify health professionals and device user facilities; (7) A proposed strategy for complying with the cease distribution and...

21 CFR 810.10 - Cease distribution and notification order.

Code of Federal Regulations, 2014 CFR

2014-04-01

..., including, where known: (i) The brand name of the device; (ii) The common name, classification name, or...) A copy of any written communication used by the person named in the order to notify health professionals and device user facilities; (7) A proposed strategy for complying with the cease distribution and...

Scientific names of organisms: attribution, rights, and licensing

PubMed Central

2014-01-01

Background As biological disciplines extend into the ‘big data’ world, they will need a names-based infrastructure to index and interconnect distributed data. The infrastructure must have access to all names of all organisms if it is to manage all information. Those who compile lists of species hold different views as to the intellectual property rights that apply to the lists. This creates uncertainty that impedes the development of a much-needed infrastructure for sharing biological data in the digital world. Findings The laws in the United States of America and European Union are consistent with the position that scientific names of organisms and their compilation in checklists, classifications or taxonomic revisions are not subject to copyright. Compilations of names, such as classifications or checklists, are not creative in the sense of copyright law. Many content providers desire credit for their efforts. Conclusions A ‘blue list’ identifies elements of checklists, classifications and monographs to which intellectual property rights do not apply. To promote sharing, authors of taxonomic content, compilers, intermediaries, and aggregators should receive citable recognition for their contributions, with the greatest recognition being given to the originating authors. Mechanisms for achieving this are discussed. PMID:24495358

41 CFR 105-62.101 - Security classification categories.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 41 Public Contracts and Property Management 3 2013-07-01 2013-07-01 false Security classification... classification categories. As set forth in Executive Order 12065, official information or material which requires... three categories: Namely, Top Secret, Secret, or Confidential, depending on its degree of significance...

41 CFR 105-62.101 - Security classification categories.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 41 Public Contracts and Property Management 3 2012-01-01 2012-01-01 false Security classification... classification categories. As set forth in Executive Order 12065, official information or material which requires... three categories: Namely, Top Secret, Secret, or Confidential, depending on its degree of significance...

41 CFR 105-62.101 - Security classification categories.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 41 Public Contracts and Property Management 3 2014-01-01 2014-01-01 false Security classification... classification categories. As set forth in Executive Order 12065, official information or material which requires... three categories: Namely, Top Secret, Secret, or Confidential, depending on its degree of significance...

Neural systems underlying lexical retrieval for sign language.

PubMed

Emmorey, Karen; Grabowski, Thomas; McCullough, Stephen; Damasio, Hanna; Ponto, Laura L B; Hichwa, Richard D; Bellugi, Ursula

2003-01-01

Positron emission tomography was used to investigate whether signed languages exhibit the same neural organization for lexical retrieval within classical and non-classical language areas as has been described for spoken English. Ten deaf native American sign language (ASL) signers were shown pictures of unique entities (famous persons) and non-unique entities (animals) and were asked to name each stimulus with an overt signed response. Proper name signed responses to famous people were fingerspelled, and common noun responses to animals were both fingerspelled and signed with native ASL signs. In general, retrieving ASL signs activated neural sites similar to those activated by hearing subjects retrieving English words. Naming famous persons activated the left temporal pole (TP), whereas naming animals (whether fingerspelled or signed) activated left inferotemporal (IT) cortex. The retrieval of fingerspelled and native signs generally engaged the same cortical regions, but fingerspelled signs in addition activated a premotor region, perhaps due to the increased motor planning and sequencing demanded by fingerspelling. Native signs activated portions of the left supramarginal gyrus (SMG), an area previously implicated in the retrieval of phonological features of ASL signs. Overall, the findings indicate that similar neuroanatomical areas are involved in lexical retrieval for both signs and words. Copyright 2003 Elsevier Science Ltd.

Identifying interactions between chemical entities in biomedical text.

PubMed

Lamurias, Andre; Ferreira, João D; Couto, Francisco M

2014-10-23

Interactions between chemical compounds described in biomedical text can be of great importance to drug discovery and design, as well as pharmacovigilance. We developed a novel system, \\"Identifying Interactions between Chemical Entities\\" (IICE), to identify chemical interactions described in text. Kernel-based Support Vector Machines first identify the interactions and then an ensemble classifier validates and classifies the type of each interaction. This relation extraction module was evaluated with the corpus released for the DDI Extraction task of SemEval 2013, obtaining results comparable to state-of-the-art methods for this type of task. We integrated this module with our chemical named entity recognition module and made the whole system available as a web tool at www.lasige.di.fc.ul.pt/webtools/iice.

Identifying interactions between chemical entities in biomedical text.

PubMed

Lamurias, Andre; Ferreira, João D; Couto, Francisco M

2014-12-01

Interactions between chemical compounds described in biomedical text can be of great importance to drug discovery and design, as well as pharmacovigilance. We developed a novel system, "Identifying Interactions between Chemical Entities" (IICE), to identify chemical interactions described in text. Kernel-based Support Vector Machines first identify the interactions and then an ensemble classifier validates and classifies the type of each interaction. This relation extraction module was evaluated with the corpus released for the DDI Extraction task of SemEval 2013, obtaining results comparable to stateof- the-art methods for this type of task. We integrated this module with our chemical named entity recognition module and made the whole system available as a web tool at www.lasige.di.fc.ul.pt/webtools/iice.

Structured prediction models for RNN based sequence labeling in clinical text.

PubMed

Jagannatha, Abhyuday N; Yu, Hong

2016-11-01

Sequence labeling is a widely used method for named entity recognition and information extraction from unstructured natural language data. In clinical domain one major application of sequence labeling involves extraction of medical entities such as medication, indication, and side-effects from Electronic Health Record narratives. Sequence labeling in this domain, presents its own set of challenges and objectives. In this work we experimented with various CRF based structured learning models with Recurrent Neural Networks. We extend the previously studied LSTM-CRF models with explicit modeling of pairwise potentials. We also propose an approximate version of skip-chain CRF inference with RNN potentials. We use these methodologies for structured prediction in order to improve the exact phrase detection of various medical entities.

Structured prediction models for RNN based sequence labeling in clinical text

PubMed Central

Jagannatha, Abhyuday N; Yu, Hong

2016-01-01

Sequence labeling is a widely used method for named entity recognition and information extraction from unstructured natural language data. In clinical domain one major application of sequence labeling involves extraction of medical entities such as medication, indication, and side-effects from Electronic Health Record narratives. Sequence labeling in this domain, presents its own set of challenges and objectives. In this work we experimented with various CRF based structured learning models with Recurrent Neural Networks. We extend the previously studied LSTM-CRF models with explicit modeling of pairwise potentials. We also propose an approximate version of skip-chain CRF inference with RNN potentials. We use these methodologies1 for structured prediction in order to improve the exact phrase detection of various medical entities. PMID:28004040

12 CFR 1229.10 - Actions applicable to critically undercapitalized Banks.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 12 Banks and Banking 7 2010-01-01 2010-01-01 false Actions applicable to critically undercapitalized Banks. 1229.10 Section 1229.10 Banks and Banking FEDERAL HOUSING FINANCE AGENCY ENTITY REGULATIONS CAPITAL CLASSIFICATIONS AND PROMPT CORRECTIVE ACTION Federal Home Loan Banks § 1229.10 Actions applicable...

12 CFR 1206.4 - Increased costs of regulation.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 12 Banks and Banking 7 2010-01-01 2010-01-01 false Increased costs of regulation. 1206.4 Section 1206.4 Banks and Banking FEDERAL HOUSING FINANCE AGENCY ORGANIZATION AND OPERATIONS ASSESSMENTS § 1206... regulation of a Regulated Entity due to its classification as other than adequately capitalized, or as a...

12 CFR 1229.8 - Mandatory actions applicable to significantly undercapitalized Banks.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 12 Banks and Banking 7 2010-01-01 2010-01-01 false Mandatory actions applicable to significantly undercapitalized Banks. 1229.8 Section 1229.8 Banks and Banking FEDERAL HOUSING FINANCE AGENCY ENTITY REGULATIONS CAPITAL CLASSIFICATIONS AND PROMPT CORRECTIVE ACTION Federal Home Loan Banks § 1229.8 Mandatory actions...

12 CFR 1229.7 - Discretionary actions applicable to undercapitalized Banks.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 12 Banks and Banking 7 2010-01-01 2010-01-01 false Discretionary actions applicable to undercapitalized Banks. 1229.7 Section 1229.7 Banks and Banking FEDERAL HOUSING FINANCE AGENCY ENTITY REGULATIONS CAPITAL CLASSIFICATIONS AND PROMPT CORRECTIVE ACTION Federal Home Loan Banks § 1229.7 Discretionary...

12 CFR 1229.6 - Mandatory actions applicable to undercapitalized Banks.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 12 Banks and Banking 7 2010-01-01 2010-01-01 false Mandatory actions applicable to undercapitalized Banks. 1229.6 Section 1229.6 Banks and Banking FEDERAL HOUSING FINANCE AGENCY ENTITY REGULATIONS CAPITAL CLASSIFICATIONS AND PROMPT CORRECTIVE ACTION Federal Home Loan Banks § 1229.6 Mandatory actions...

15 CFR Supplement No. 4 to Part 744 - Entity List

Code of Federal Regulations, 2010 CFR

2010-01-01

... Ninth Academy, including the Southwest Institutes of: Applied Electronics, Chemical Materials... Institute of Electronics Technology, Chengdu For all items subject to the EAR having a classification other.../22/08. Creative Electronics, Room 2202c, 22/F, Nan Fung Centre, 264-298 Castle Peak Road, Hong Kong...

Disrupting Power/Entrenching Sovereignty: The Paradox of Human Rights Education

ERIC Educational Resources Information Center

Ahmed, A. Kayum

2017-01-01

While human rights education (HRE) provides the tools for emancipation, it remains susceptible to appropriation by authoritarian regimes who seek to entrench state power. Classification scholars who typologize approaches to HRE fail to acknowledge that state entities could employ human rights discourse to reinforce state sovereignty. Consequently,…

A new landscape classification system for monitoring and assessment of pastures

USDA-ARS?s Scientific Manuscript database

Pasturelands in the United States span a broad range of climate, soils, physical sites, and management. Rather than treat each site as a unique entity, this diversity must be classified into basic units for research and management purposes. A similar system based on ecological principles is needed f...

12 CFR 1207.23 - Annual reports-format and contents.

Code of Federal Regulations, 2011 CFR

2011-01-01

... and gender the number of individuals applying for employment with the regulated entity or the Office... year; (4) Data showing by minority and gender the number of individuals hired for employment with the... during the reporting year; (5) Data showing by minority, gender and disability classification, and...

33 CFR 160.206 - Information required in an NOA.

Code of Federal Regulations, 2010 CFR

2010-07-01

... CDC (1) Vessel Information: (i) Name; X X X (ii) Name of the registered owner; X X X (iii) Country of registry; X X X (iv) Call sign; X X X (v) International Maritime Organization (IMO) international number or... (vi) Name of the operator; X X X (vii) Name of the charterer; and X X X (viii) Name of classification...

Classification of chemical substances, reactions, and interactions: The effect of expertise

NASA Astrophysics Data System (ADS)

Stains, Marilyne Nicole Olivia

2007-12-01

This project explored the strategies that undergraduate and graduate chemistry students engaged in when solving classification tasks involving microscopic (particulate) representations of chemical substances and microscopic and symbolic representations of different chemical reactions. We were specifically interested in characterizing the basic features to which students pay attention while classifying, identifying the patterns of reasoning that they follow, and comparing the performance of students with different levels of preparation in the discipline. In general, our results suggest that advanced levels of expertise in chemical classification do not necessarily evolve in a linear and continuous way with academic training. Novice students had a tendency to reduce the cognitive demand of the task and rely on common-sense reasoning; they had difficulties differentiating concepts (conceptual undifferentiation) and based their classification decisions on only one variable (reduction). These ways of thinking lead them to consider extraneous features, pay more attention to explicit or surface features than implicit features and to overlook important and relevant features. However, unfamiliar levels of representations (microscopic level) seemed to trigger deeper and more meaningful thinking processes. On the other hand, expert students classified entities using a specific set of rules that they applied throughout the classification tasks. They considered a larger variety of implicit features and the unfamiliarity with the microscopic level of representation did not affect their reasoning processes. Consequently, novices created numerous small groups, few of them being chemically meaningful, while experts created few but large chemically meaningful groups. Novices also had difficulties correctly classifying entities in chemically meaningful groups. Finally, expert chemists in our study used classification schemes that are not necessarily traditionally taught in classroom chemistry (e.g. the structure of substances is more relevant to them than their composition when classifying substances as compounds or elements). This result suggests that practice in the field may develop different types of knowledge framework than those usually presented in chemistry textbooks.

Self-organizing ontology of biochemically relevant small molecules

PubMed Central

2012-01-01

Background The advent of high-throughput experimentation in biochemistry has led to the generation of vast amounts of chemical data, necessitating the development of novel analysis, characterization, and cataloguing techniques and tools. Recently, a movement to publically release such data has advanced biochemical structure-activity relationship research, while providing new challenges, the biggest being the curation, annotation, and classification of this information to facilitate useful biochemical pattern analysis. Unfortunately, the human resources currently employed by the organizations supporting these efforts (e.g. ChEBI) are expanding linearly, while new useful scientific information is being released in a seemingly exponential fashion. Compounding this, currently existing chemical classification and annotation systems are not amenable to automated classification, formal and transparent chemical class definition axiomatization, facile class redefinition, or novel class integration, thus further limiting chemical ontology growth by necessitating human involvement in curation. Clearly, there is a need for the automation of this process, especially for novel chemical entities of biological interest. Results To address this, we present a formal framework based on Semantic Web technologies for the automatic design of chemical ontology which can be used for automated classification of novel entities. We demonstrate the automatic self-assembly of a structure-based chemical ontology based on 60 MeSH and 40 ChEBI chemical classes. This ontology is then used to classify 200 compounds with an accuracy of 92.7%. We extend these structure-based classes with molecular feature information and demonstrate the utility of our framework for classification of functionally relevant chemicals. Finally, we discuss an iterative approach that we envision for future biochemical ontology development. Conclusions We conclude that the proposed methodology can ease the burden of chemical data annotators and dramatically increase their productivity. We anticipate that the use of formal logic in our proposed framework will make chemical classification criteria more transparent to humans and machines alike and will thus facilitate predictive and integrative bioactivity model development. PMID:22221313

Glossary: Defense Acquisition Acronyms and Terms. Revision 2

DTIC Science & Technology

1987-07-01

Approved REPORT DOCUMENTATION PAGE OMBNo. 070-O 18 la. REPORT SECURITY CLASSIFICATION lb. RESTRICTIVE MARKINGS % unclassified 2a. SECURITY CLASSIFICATION ...WORK UNIT Fort Belvoir, VA 22060-5426 ELEMENT NO. NO. NO. ACCESSION NO. 11. TITLE (Include Security Classification ) Glossary Defense Acquisition...DISTRIBUTION/AVAILABILITY OF ABSTRACT 21 ABSTRACT SECURITY CLASSIFICATION [RUNCLASSIFIED/UNLIMITED 0 SAME AS RPT 0 DTIC USERS unclassified 22a. NAME OF

Information extraction system

DOEpatents

Lemmond, Tracy D; Hanley, William G; Guensche, Joseph Wendell; Perry, Nathan C; Nitao, John J; Kidwell, Paul Brandon; Boakye, Kofi Agyeman; Glaser, Ron E; Prenger, Ryan James

2014-05-13

An information extraction system and methods of operating the system are provided. In particular, an information extraction system for performing meta-extraction of named entities of people, organizations, and locations as well as relationships and events from text documents are described herein.

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

A user-friendly tool for medical-related patent retrieval.

PubMed

Pasche, Emilie; Gobeill, Julien; Teodoro, Douglas; Gaudinat, Arnaud; Vishnyakova, Dina; Lovis, Christian; Ruch, Patrick

2012-01-01

Health-related information retrieval is complicated by the variety of nomenclatures available to name entities, since different communities of users will use different ways to name a same entity. We present in this report the development and evaluation of a user-friendly interactive Web application aiming at facilitating health-related patent search. Our tool, called TWINC, relies on a search engine tuned during several patent retrieval competitions, enhanced with intelligent interaction modules, such as chemical query, normalization and expansion. While the functionality of related article search showed promising performances, the ad hoc search results in fairly contrasted results. Nonetheless, TWINC performed well during the PatOlympics competition and was appreciated by intellectual property experts. This result should be balanced by the limited evaluation sample. We can also assume that it can be customized to be applied in corporate search environments to process domain and company-specific vocabularies, including non-English literature and patents reports.

PKDE4J: Entity and relation extraction for public knowledge discovery.

PubMed

Song, Min; Kim, Won Chul; Lee, Dahee; Heo, Go Eun; Kang, Keun Young

2015-10-01

Due to an enormous number of scientific publications that cannot be handled manually, there is a rising interest in text-mining techniques for automated information extraction, especially in the biomedical field. Such techniques provide effective means of information search, knowledge discovery, and hypothesis generation. Most previous studies have primarily focused on the design and performance improvement of either named entity recognition or relation extraction. In this paper, we present PKDE4J, a comprehensive text-mining system that integrates dictionary-based entity extraction and rule-based relation extraction in a highly flexible and extensible framework. Starting with the Stanford CoreNLP, we developed the system to cope with multiple types of entities and relations. The system also has fairly good performance in terms of accuracy as well as the ability to configure text-processing components. We demonstrate its competitive performance by evaluating it on many corpora and found that it surpasses existing systems with average F-measures of 85% for entity extraction and 81% for relation extraction. Copyright © 2015 Elsevier Inc. All rights reserved.

Identification of related gene/protein names based on an HMM of name variations.

PubMed

Yeganova, L; Smith, L; Wilbur, W J

2004-04-01

Gene and protein names follow few, if any, true naming conventions and are subject to great variation in different occurrences of the same name. This gives rise to two important problems in natural language processing. First, can one locate the names of genes or proteins in free text, and second, can one determine when two names denote the same gene or protein? The first of these problems is a special case of the problem of named entity recognition, while the second is a special case of the problem of automatic term recognition (ATR). We study the second problem, that of gene or protein name variation. Here we describe a system which, given a query gene or protein name, identifies related gene or protein names in a large list. The system is based on a dynamic programming algorithm for sequence alignment in which the mutation matrix is allowed to vary under the control of a fully trainable hidden Markov model.

Stochastic Process Creation

NASA Astrophysics Data System (ADS)

Esparza, Javier

In many areas of computer science entities can “reproduce”, “replicate”, or “create new instances”. Paramount examples are threads in multithreaded programs, processes in operating systems, and computer viruses, but many others exist: procedure calls create new incarnations of the callees, web crawlers discover new pages to be explored (and so “create” new tasks), divide-and-conquer procedures split a problem into subproblems, and leaves of tree-based data structures become internal nodes with children. For lack of a better name, I use the generic term systems with process creation to refer to all these entities.

Named Entity Recognition in a Hungarian NL Based QA System

NASA Astrophysics Data System (ADS)

Tikkl, Domonkos; Szidarovszky, P. Ferenc; Kardkovacs, Zsolt T.; Magyar, Gábor

In WoW project our purpose is to create a complex search interface with the following features: search in the deep web content of contracted partners' databases, processing Hungarian natural language (NL) questions and transforming them to SQL queries for database access, image search supported by a visual thesaurus that describes in a structural form the visual content of images (also in Hungarian). This paper primarily focuses on a particular problem of question processing task: the entity recognition. Before going into details we give a short overview of the project's aims.

Exploring Contextual Models in Chemical Patent Search

NASA Astrophysics Data System (ADS)

Urbain, Jay; Frieder, Ophir

We explore the development of probabilistic retrieval models for integrating term statistics with entity search using multiple levels of document context to improve the performance of chemical patent search. A distributed indexing model was developed to enable efficient named entity search and aggregation of term statistics at multiple levels of patent structure including individual words, sentences, claims, descriptions, abstracts, and titles. The system can be scaled to an arbitrary number of compute instances in a cloud computing environment to support concurrent indexing and query processing operations on large patent collections.

A Three Dimensional Electronic Retina Architecture.

DTIC Science & Technology

1987-12-01

not guarantee that a biological entity is in fact the best design because of the unique constraining factors of a biological organism and the associated...4. PERFORMING ORGANIZATION REPORT NUMBER(S) 5. MONITORING ORGANIZATION REPORT NUMBER(S) AFIT/GCS/ENG/87D-23 6a. NAME OF PERFORMING ORGANIZATION 6b...OFFICE SYMBOL 7a. NAME OF MONITORING ORGANIZATION (If applicable) School of Engineering AFIT/ENG 6c. ADDRESS (City, State, and ZIP Code) 7b. ADDRESS

Cybersecurity: Utilizing Fusion Centers to Protect State, Local, Tribal, and Territorial Entities Against Cyber Threats

DTIC Science & Technology

2016-09-01

PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) Naval Postgraduate School Monterey, CA 93943-5000 8. PERFORMING ORGANIZATION REPORT NUMBER 9...state- and local-level computer networks fertile ground for the cyber adversary. This research focuses on the threat to SLTT computer networks and how...institutions, and banking systems. The array of responsibilities and the cybersecurity threat landscape make state- and local-level computer networks fertile

Primary intraosseous squamous cell carcinoma in odontogenic keratocyst: A rare entity

PubMed Central

Saxena, Chitrapriya; Aggarwal, Pooja; Wadhwan, Vijay; Bansal, Vishal

2015-01-01

Squamous cell carcinoma (SCC) arising from the wall of an odontogenic cyst (also known as primary intraosseous carcinoma) is a rare tumor which occurs only in jaw bones. This tumor was first described by Loos in 1913 as a central epidermoid carcinoma of the jaw. Primary intraosseous carcinomas (PIOC) may theoretically arise from the lining of an odontogenic cyst or de novo from presumed odontogenic cell rests. According to the new histological classification of tumors of the World Health Organization, odontogenic keratocyst is nowadays considered a specific odontogenic tumor and the PIOC derived from it is considered as a specific entity which is different from other PIOCs derived from the odontogenic cysts. The following report describes a case of such extremely rare entity that is primary intraosseous SCC of the mandible derived from an OKC in a 60-year-old male patient with brief review of literature. PMID:26980976

Cryptogenic stroke. A non-diagnosis.

PubMed

Gutiérrez-Zúñiga, Raquel; Fuentes, Blanca; Díez-Tejedor, Exuperio

2018-04-30

The term cryptogenic stroke refers to a stroke for which there is no specific attributable cause after a comprehensive evaluation. However, there are differences between the diagnostic criteria of etiological classifications used in clinical practice. An improvement in diagnostic tools such advances in monitoring for atrial fibrillation, advances in vascular imaging and evidence regarding the implication of patent foramen oval on the risk of stroke specially in young patients are reducing the proportion of stroke patients without etiological diagnosis. We carried out a critical review of the current concept of cryptogenic stroke, as a non-diagnosis, avoiding the simplification of it and reviewing the different entities that could fall under this diagnosis and reviewing the different entities that could fall under this diagnosis; and therefore avoid the same treatment for differents entities with uncertains results. Copyright © 2018 Elsevier España, S.L.U. All rights reserved.

Categorizing entities by common role.

PubMed

Goldwater, Micah B; Markman, Arthur B

2011-04-01

Many categories group together entities that play a common role across situations. For example, guest and host refer to complementary roles in visiting situations and, thus, are role-governed categories (A. B. Markman & Stilwell, Journal of Experiment & Theoretical Artificial Intelligence, 13, 329-358, 2001). However, categorizing an entity by role is one of many possible classification strategies. This article examines factors that promote role-governed categorization over thematic-relation-based categorization (Lin & Murphy, Journal of Experimental Psychology: General, 130, 3-28, 2001). In Experiments 1a and 1b, we demonstrate that the use of novel category labels facilitates role-governed categorization. In Experiments 2a and 2b, we demonstrate that analogical comparison facilitates role-governed categorization. In Experiments 1b and 2b, we show that these facilitatory factors induce a general sensitivity to role information, as opposed to only promoting role-governed categorization on an item-by-item basis.

Primary disorders of the lymphatic vessels--a unified concept.

PubMed

Levine, C

1989-03-01

Congenital defects of lymphatics constitute a spectrum of disorders that may manifest with a variety of clinical presentations including lymphedema, chylous effusions, lymphangiomatous malformations with cystic masses and localized gigantism, and intestinal lymphangiectasia with malabsorption. These entities constitute a relatively rare group of disorders, the origin of which remains somewhat controversial, but in some it appears to be due to early lymphatic obstruction. Five cases are described, which demonstrate the anatomical pathology of these entities. A classification and description of the defects is also presented. An attempt is made to present a unified theory of origin for this seemingly diverse group of diseases. While these entities may be challenging from a diagnostic and therapeutic standpoint, a wide variety of imaging modalities, which includes lymphography, computed tomography scanning, and ultrasound, may be used to diagnose the extent and internal structural characteristics of the abnormalities.

Object-based delineation and classification of alluvial fans by application of mean-shift segmentation and support vector machines

NASA Astrophysics Data System (ADS)

Pipaud, Isabel; Lehmkuhl, Frank

2017-09-01

In the field of geomorphology, automated extraction and classification of landforms is one of the most active research areas. Until the late 2000s, this task has primarily been tackled using pixel-based approaches. As these methods consider pixels and pixel neighborhoods as the sole basic entities for analysis, they cannot account for the irregular boundaries of real-world objects. Object-based analysis frameworks emerging from the field of remote sensing have been proposed as an alternative approach, and were successfully applied in case studies falling in the domains of both general and specific geomorphology. In this context, the a-priori selection of scale parameters or bandwidths is crucial for the segmentation result, because inappropriate parametrization will either result in over-segmentation or insufficient segmentation. In this study, we describe a novel supervised method for delineation and classification of alluvial fans, and assess its applicability using a SRTM 1‧‧ DEM scene depicting a section of the north-eastern Mongolian Altai, located in northwest Mongolia. The approach is premised on the application of mean-shift segmentation and the use of a one-class support vector machine (SVM) for classification. To consider variability in terms of alluvial fan dimension and shape, segmentation is performed repeatedly for different weightings of the incorporated morphometric parameters as well as different segmentation bandwidths. The final classification layer is obtained by selecting, for each real-world object, the most appropriate segmentation result according to fuzzy membership values derived from the SVM classification. Our results show that mean-shift segmentation and SVM-based classification provide an effective framework for delineation and classification of a particular landform. Variable bandwidths and terrain parameter weightings were identified as being crucial for consideration of intra-class variability, and, in turn, for a constantly high segmentation quality. Our analysis further reveals that incorporation of morphometric parameters quantifying specific morphological aspects of a landform is indispensable for developing an accurate classification scheme. Alluvial fans exhibiting accentuated composite morphologies were identified as a major challenge for automatic delineation, as they cannot be fully captured by a single segmentation run. There is, however, a high probability that this shortcoming can be overcome by enhancing the presented approach with a routine merging fan sub-entities based on their spatial relationships.

[Haemolytic uremic syndrome and thrombotic thrombocytopenic purpura: classification based on molecular etiology and review of recent developments in diagnostics].

PubMed

Prohászka, Zoltán

2008-07-06

Haemolytic uremic syndrome and thrombotic thrombocytopenic purpura are overlapping clinical entities based on historical classification. Recent developments in the unfolding of the pathomechanisms of these diseases resulted in the creation of a molecular etiology-based classification. Understanding of some causative relationships yielded detailed diagnostic approaches, novel therapeutic options and thorough prognostic assortment of the patients. Although haemolytic uremic syndrome and thrombotic thrombocytopenic purpura are rare diseases with poor prognosis, the precise molecular etiology-based diagnosis might properly direct the therapy of the affected patients. The current review focuses on the theoretical background and detailed description of the available diagnostic possibilities, and some practical information necessary for the interpretation of their results.

Automated system for characterization and classification of malaria-infected stages using light microscopic images of thin blood smears.

PubMed

Das, D K; Maiti, A K; Chakraborty, C

2015-03-01

In this paper, we propose a comprehensive image characterization cum classification framework for malaria-infected stage detection using microscopic images of thin blood smears. The methodology mainly includes microscopic imaging of Leishman stained blood slides, noise reduction and illumination correction, erythrocyte segmentation, feature selection followed by machine classification. Amongst three-image segmentation algorithms (namely, rule-based, Chan-Vese-based and marker-controlled watershed methods), marker-controlled watershed technique provides better boundary detection of erythrocytes specially in overlapping situations. Microscopic features at intensity, texture and morphology levels are extracted to discriminate infected and noninfected erythrocytes. In order to achieve subgroup of potential features, feature selection techniques, namely, F-statistic and information gain criteria are considered here for ranking. Finally, five different classifiers, namely, Naive Bayes, multilayer perceptron neural network, logistic regression, classification and regression tree (CART), RBF neural network have been trained and tested by 888 erythrocytes (infected and noninfected) for each features' subset. Performance evaluation of the proposed methodology shows that multilayer perceptron network provides higher accuracy for malaria-infected erythrocytes recognition and infected stage classification. Results show that top 90 features ranked by F-statistic (specificity: 98.64%, sensitivity: 100%, PPV: 99.73% and overall accuracy: 96.84%) and top 60 features ranked by information gain provides better results (specificity: 97.29%, sensitivity: 100%, PPV: 99.46% and overall accuracy: 96.73%) for malaria-infected stage classification. © 2014 The Authors Journal of Microscopy © 2014 Royal Microscopical Society.

Human-machine interaction to disambiguate entities in unstructured text and structured datasets

NASA Astrophysics Data System (ADS)

Ward, Kevin; Davenport, Jack

2017-05-01

Creating entity network graphs is a manual, time consuming process for an intelligence analyst. Beyond the traditional big data problems of information overload, individuals are often referred to by multiple names and shifting titles as they advance in their organizations over time which quickly makes simple string or phonetic alignment methods for entities insufficient. Conversely, automated methods for relationship extraction and entity disambiguation typically produce questionable results with no way for users to vet results, correct mistakes or influence the algorithm's future results. We present an entity disambiguation tool, DRADIS, which aims to bridge the gap between human-centric and machinecentric methods. DRADIS automatically extracts entities from multi-source datasets and models them as a complex set of attributes and relationships. Entities are disambiguated across the corpus using a hierarchical model executed in Spark allowing it to scale to operational sized data. Resolution results are presented to the analyst complete with sourcing information for each mention and relationship allowing analysts to quickly vet the correctness of results as well as correct mistakes. Corrected results are used by the system to refine the underlying model allowing analysts to optimize the general model to better deal with their operational data. Providing analysts with the ability to validate and correct the model to produce a system they can trust enables them to better focus their time on producing higher quality analysis products.

Mesh Oriented datABase

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

Tautges, Timothy J.

MOAB is a component for representing and evaluating mesh data. MOAB can store stuctured and unstructured mesh, consisting of elements in the finite element "zoo". The functional interface to MOAB is simple yet powerful, allowing the representation of many types of metadata commonly found on the mesh. MOAB is optimized for efficiency in space and time, based on access to mesh in chunks rather than through individual entities, while also versatile enough to support individual entity access. The MOAB data model consists of a mesh interface instance, mesh entities (vertices and elements), sets, and tags. Entities are addressed through handlesmore » rather than pointers, to allow the underlying representation of an entity to change without changing the handle to that entity. Sets are arbitrary groupings of mesh entities and other sets. Sets also support parent/child relationships as a relation distinct from sets containing other sets. The directed-graph provided by set parent/child relationships is useful for modeling topological relations from a geometric model or other metadata. Tags are named data which can be assigned to the mesh as a whole, individual entities, or sets. Tags are a mechanism for attaching data to individual entities and sets are a mechanism for describing relations between entities; the combination of these two mechanisms isa powerful yet simple interface for representing metadata or application-specific data. For example, sets and tags can be used together to describe geometric topology, boundary condition, and inter-processor interface groupings in a mesh. MOAB is used in several ways in various applications. MOAB serves as the underlying mesh data representation in the VERDE mesh verification code. MOAB can also be used as a mesh input mechanism, using mesh readers induded with MOAB, or as a t’anslator between mesh formats, using readers and writers included with MOAB.« less

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.

78 FR 42910 - Community Right-to-Know; Adoption of 2012 North American Industry Classification System (NAICS...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-07-18

... www.regulations.gov or email. The www.regulations.gov Web site is an ``anonymous access'' system...-7672, http://www.epa.gov/epaoswer/hotline/ . SUPPLEMENTARY INFORMATION: I. Why is EPA issuing this... entity, consult the person listed in the FOR FURTHER INFORMATION CONTACT section. III. What should I...

[Cystic renal neoplasms. New entities and molecular findings].

PubMed

Moch, H

2010-10-01

Renal neoplasms with dominant cysts represent a broad spectrum of known as well as novel renal tumor entities. Established renal tumors with dominant cysts include cystic nephroma, mixed epithelial and stromal tumor, synovial sarcoma and multilocular cystic renal cancer (WHO classification 2004). Novel tumor types have recently been reported, which are also characterized by marked cyst formation. Examples are tubulocystic renal cancer and renal cancer in end-stage renal disease. These tumors are very likely to be included in a future WHO classification due to their characteristic phenotype and molecular features. Cysts and clear cell renal cell carcinoma frequently coexist in the kidneys of patients with von Hippel-Lindau disease. Cysts are also a component of many sporadic clear cell renal cell carcinomas. Multilocular cystic renal cell carcinoma is composed almost exclusively of cysts and is regarded as a specific subtype of clear cell renal cancer. Recent molecular findings suggest that clear cell renal cancer may develop via a cyst-dependent mechanism in von Hippel-Lindau syndrome as well as via cyst-independent molecular pathways in sporadic clear cell renal cancer.

77 FR 54663 - Administrative Simplification: Adoption of a Standard for a Unique Health Plan Identifier...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-09-05

...This final rule adopts the standard for a national unique health plan identifier (HPID) and establishes requirements for the implementation of the HPID. In addition, it adopts a data element that will serve as an other entity identifier (OEID), or an identifier for entities that are not health plans, health care providers, or individuals, but that need to be identified in standard transactions. This final rule also specifies the circumstances under which an organization covered health care provider must require certain noncovered individual health care providers who are prescribers to obtain and disclose a National Provider Identifier (NPI). Lastly, this final rule changes the compliance date for the International Classification of Diseases, 10th Revision, Clinical Modification (ICD- 10-CM) for diagnosis coding, including the Official ICD-10-CM Guidelines for Coding and Reporting, and the International Classification of Diseases, 10th Revision, Procedure Coding System (ICD-10-PCS) for inpatient hospital procedure coding, including the Official ICD-10-PCS Guidelines for Coding and Reporting, from October 1, 2013 to October 1, 2014.

A stacked sequential learning method for investigator name recognition from web-based medical articles

NASA Astrophysics Data System (ADS)

Zhang, Xiaoli; Zou, Jie; Le, Daniel X.; Thoma, George

2010-01-01

"Investigator Names" is a newly required field in MEDLINE citations. It consists of personal names listed as members of corporate organizations in an article. Extracting investigator names automatically is necessary because of the increasing volume of articles reporting collaborative biomedical research in which a large number of investigators participate. In this paper, we present an SVM-based stacked sequential learning method in a novel application - recognizing named entities such as the first and last names of investigators from online medical journal articles. Stacked sequential learning is a meta-learning algorithm which can boost any base learner. It exploits contextual information by adding the predicted labels of the surrounding tokens as features. We apply this method to tag words in text paragraphs containing investigator names, and demonstrate that stacked sequential learning improves the performance of a nonsequential base learner such as an SVM classifier.

Diagnosis of narcolepsy and idiopathic hypersomnia. An update based on the International classification of sleep disorders, 2nd edition.

PubMed

Billiard, Michel

2007-10-01

Defining the precise nosological limits of narcolepsy and idiopathic hypersomnia is an ongoing process dating back to the first description of the two conditions. The most recent step forward has been done within the preparation of the second edition of the "International classification of sleep disorders" published in June 2005. Appointed by Dr Emmanuel Mignot, the Task Force on "Hypersomnias of central origin, not due to a circadian rhythm sleep disorder, sleep related breathing disorder, or other causes of disturbed nocturnal sleep" thoroughly revisited the nosology of narcolepsy and of idiopathic hypersomnia. Narcolepsy is now distinguished into three different entities, narcolepsy with cataplexy, narcolepsy without cataplexy and narcolepsy due to medical condition, and idiopathic hypersomnia into two entities, idiopathic hypersomnia with long sleep time and idiopathic hypersomnia without long sleep time. Nevertheless there are still a number of pending issues. What are the limits of narcolepsy without cataplexy? Is there a continuum in the pathophysiology of narcolepsy with and without cataplexy? Should sporadic and familial forms of narcolepsy with cataplexy appear as subgroups in the classification? Are idiopathic hypersomnia with long sleep time and idiopathic hypersomnia without long sleep time, two forms of the same condition or two different conditions? Is there a pathophysiological relationship between narcolepsy without cataplexy and idiopathic hypersomnia without long sleep time?

Using landscape limnology to classify freshwater ecosystems for multi-ecosystem management and conservation

USGS Publications Warehouse

Soranno, Patricia A.; Cheruvelil, Kendra Spence; Webster, Katherine E.; Bremigan, Mary T.; Wagner, Tyler; Stow, Craig A.

2010-01-01

Governmental entities are responsible for managing and conserving large numbers of lake, river, and wetland ecosystems that can be addressed only rarely on a case-by-case basis. We present a system for predictive classification modeling, grounded in the theoretical foundation of landscape limnology, that creates a tractable number of ecosystem classes to which management actions may be tailored. We demonstrate our system by applying two types of predictive classification modeling approaches to develop nutrient criteria for eutrophication management in 1998 north temperate lakes. Our predictive classification system promotes the effective management of multiple ecosystems across broad geographic scales by explicitly connecting management and conservation goals to the classification modeling approach, considering multiple spatial scales as drivers of ecosystem dynamics, and acknowledging the hierarchical structure of freshwater ecosystems. Such a system is critical for adaptive management of complex mosaics of freshwater ecosystems and for balancing competing needs for ecosystem services in a changing world.

Mixed anxiety depression should not be included in DSM-5.

PubMed

Batelaan, Neeltje M; Spijker, Jan; de Graaf, Ron; Cuijpers, Pim

2012-06-01

Subthreshold anxiety and subthreshold depressive symptoms often co-occur in the general population and in primary care. Based on their associated significant distress and impairment, a psychiatric classification seems justified. To enable classification, mixed anxiety depression (MAD) has been proposed as a new diagnostic category in DSM-5. In this report, we discuss arguments against the classification of MAD. More research is needed before reifying a new category we know so little about. Moreover, we argue that in patients with MAD symptoms and a history of an anxiety or depressive disorder, symptoms should be labeled as part of the course trajectories of these disorders, rather than calling it a different diagnostic entity. In patients with incident co-occurring subthreshold anxiety and subthreshold depression, subthreshold categories of both anxiety and depression could be classified to maintain a consistent classification system at both threshold and subthreshold levels.

Taking on Nationalism in the Name of Intercultural Competence

ERIC Educational Resources Information Center

Meadows, Bryan

2010-01-01

Nationalism presents significant challenges to intercultural competence instruction. On the one hand, nationalism promotes the compartmentalization of communities into mutually-exclusive and discretely-defined nationalist entities. In complementary fashion, nationalism also advocates the homogenization of cultural and linguistic practices within…

20 CFR 627.215 - Relocation.

Code of Federal Regulations, 2010 CFR

2010-04-01

... the original location. (b) For 120 days after the commencement or the expansion of commercial... original location. (c) For the purposes of this section, relocating establishment means a business entity... review should include names under which the establishment does business, including successors-in-interest...

Evaluation of Fly Ash Quality Control Tools

DOT National Transportation Integrated Search

2010-06-30

Many entities currently use fly ash in portland cement concrete (PCC) pavements and structures. Although the body of knowledge is : great concerning the use of fly ash, several projects per year are subject to poor performance where fly ash is named ...

Evaluation of fly ash quality control tools.

DOT National Transportation Integrated Search

2010-06-30

Many entities currently use fly ash in portland cement concrete (PCC) pavements and structures. Although the body of knowledge is : great concerning the use of fly ash, several projects per year are subject to poor performance where fly ash is named ...

Using nanoinformatics methods for automatically identifying relevant nanotoxicology entities from the literature.

PubMed

García-Remesal, Miguel; García-Ruiz, Alejandro; Pérez-Rey, David; de la Iglesia, Diana; Maojo, Víctor

2013-01-01

Nanoinformatics is an emerging research field that uses informatics techniques to collect, process, store, and retrieve data, information, and knowledge on nanoparticles, nanomaterials, and nanodevices and their potential applications in health care. In this paper, we have focused on the solutions that nanoinformatics can provide to facilitate nanotoxicology research. For this, we have taken a computational approach to automatically recognize and extract nanotoxicology-related entities from the scientific literature. The desired entities belong to four different categories: nanoparticles, routes of exposure, toxic effects, and targets. The entity recognizer was trained using a corpus that we specifically created for this purpose and was validated by two nanomedicine/nanotoxicology experts. We evaluated the performance of our entity recognizer using 10-fold cross-validation. The precisions range from 87.6% (targets) to 93.0% (routes of exposure), while recall values range from 82.6% (routes of exposure) to 87.4% (toxic effects). These results prove the feasibility of using computational approaches to reliably perform different named entity recognition (NER)-dependent tasks, such as for instance augmented reading or semantic searches. This research is a "proof of concept" that can be expanded to stimulate further developments that could assist researchers in managing data, information, and knowledge at the nanolevel, thus accelerating research in nanomedicine.

The J-Staff System, Network Synchronisation and Noise

DTIC Science & Technology

2014-06-01

GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT NUMBER 5e. TASK NUMBER 5f. WORK UNIT NUMBER 7. PERFORMING ORGANIZATION NAME(S... work . A key challenge of such structures is their tendency to fall into extreme dynamical modes. One is a ‘two-speed’ mode, where units interacting with...longer term planning, led by the J5 Planning Branch, fall into a slow cycle of work , while those entities interacting predominately with operations

[Classification of memory systems: a revision].

PubMed

Agrest, M

2001-12-01

The present paper exposes the arguments against considering memory as a monolytic entity and how is it to be divided into several systems in order to understand its operation. Historically this division was acknowledge by different authors but in the last few decades it received the confirmation from the scientific research. The most accepted taxonomy establishes the existence of two major memory systems: declarative and non declarative memory. The article also presents the arguments for and against this kind of division, as well as an alternative classification in five major systems: procedural, perceptual representation, semantic, primary and episodic.

Data model and relational database design for the New England Water-Use Data System (NEWUDS)

USGS Publications Warehouse

Tessler, Steven

2001-01-01

The New England Water-Use Data System (NEWUDS) is a database for the storage and retrieval of water-use data. NEWUDS can handle data covering many facets of water use, including (1) tracking various types of water-use activities (withdrawals, returns, transfers, distributions, consumptive-use, wastewater collection, and treatment); (2) the description, classification and location of places and organizations involved in water-use activities; (3) details about measured or estimated volumes of water associated with water-use activities; and (4) information about data sources and water resources associated with water use. In NEWUDS, each water transaction occurs unidirectionally between two site objects, and the sites and conveyances form a water network. The core entities in the NEWUDS model are site, conveyance, transaction/rate, location, and owner. Other important entities include water resources (used for withdrawals and returns), data sources, and aliases. Multiple water-exchange estimates can be stored for individual transactions based on different methods or data sources. Storage of user-defined details is accommodated for several of the main entities. Numerous tables containing classification terms facilitate detailed descriptions of data items and can be used for routine or custom data summarization. NEWUDS handles single-user and aggregate-user water-use data, can be used for large or small water-network projects, and is available as a stand-alone Microsoft? Access database structure. Users can customize and extend the database, link it to other databases, or implement the design in other relational database applications.

On Developing a Taxonomy for Multidisciplinary Design Optimization: A Decision-Based Perspective

NASA Technical Reports Server (NTRS)

Lewis, Kemper; Mistree, Farrokh

1995-01-01

In this paper, we approach MDO from a Decision-Based Design (DBD) perspective and explore classification schemes for designing complex systems and processes. Specifically, we focus on decisions, which are only a small portion of the Decision Support Problem (DSP) Technique, our implementation of DBD. We map coupled nonhierarchical and hierarchical representations from the DSP Technique into the Balling-Sobieski (B-S) framework (Balling and Sobieszczanski-Sobieski, 1994), and integrate domain-independent linguistic terms to complete our taxonomy. Application of DSPs to the design of complex, multidisciplinary systems include passenger aircraft, ships, damage tolerant structural and mechanical systems, and thermal energy systems. In this paper we show that Balling-Sobieski framework is consistent with that of the Decision Support Problem Technique through the use of linguistic entities to describe the same type of formulations. We show that the underlying linguistics of the solution approaches are the same and can be coalesced into a homogeneous framework with which to base the research, application, and technology MDO upon. We introduce, in the Balling-Sobieski framework, examples of multidisciplinary design, namely, aircraft, damage tolerant structural and mechanical systems, and thermal energy systems.

45 CFR 164.508 - Uses and disclosures for which an authorization is required.

Code of Federal Regulations, 2011 CFR

2011-10-01

... is in the form of: (A) A face-to-face communication made by a covered entity to an individual; or (B... meaningful fashion. (ii) The name or other specific identification of the person(s), or class of persons...

45 CFR 164.508 - Uses and disclosures for which an authorization is required.

Code of Federal Regulations, 2010 CFR

2010-10-01

... is in the form of: (A) A face-to-face communication made by a covered entity to an individual; or (B... meaningful fashion. (ii) The name or other specific identification of the person(s), or class of persons...

Information Tailoring Enhancements for Large-Scale Social Data

DTIC Science & Technology

2016-06-15

Intelligent Automation Incorporated Information Tailoring Enhancements for Large-Scale... Automation Incorporated Progress Report No. 3 Information Tailoring Enhancements for Large-Scale Social Data Submitted in accordance with...1 Work Performed within This Reporting Period .................................................... 2 1.1 Enhanced Named Entity Recognition (NER

Hierarchical Higher Order Crf for the Classification of Airborne LIDAR Point Clouds in Urban Areas

NASA Astrophysics Data System (ADS)

Niemeyer, J.; Rottensteiner, F.; Soergel, U.; Heipke, C.

2016-06-01

We propose a novel hierarchical approach for the classification of airborne 3D lidar points. Spatial and semantic context is incorporated via a two-layer Conditional Random Field (CRF). The first layer operates on a point level and utilises higher order cliques. Segments are generated from the labelling obtained in this way. They are the entities of the second layer, which incorporates larger scale context. The classification result of the segments is introduced as an energy term for the next iteration of the point-based layer. This framework iterates and mutually propagates context to improve the classification results. Potentially wrong decisions can be revised at later stages. The output is a labelled point cloud as well as segments roughly corresponding to object instances. Moreover, we present two new contextual features for the segment classification: the distance and the orientation of a segment with respect to the closest road. It is shown that the classification benefits from these features. In our experiments the hierarchical framework improve the overall accuracies by 2.3% on a point-based level and by 3.0% on a segment-based level, respectively, compared to a purely point-based classification.

Sweet Syndrome: A Review and Update.

PubMed

Villarreal-Villarreal, C D; Ocampo-Candiani, J; Villarreal-Martínez, A

2016-06-01

Sweet syndrome is the most representative entity of febrile neutrophilic dermatoses. It typically presents in patients with pirexya, neutrophilia, painful tender erytomatous papules, nodules and plaques often distributed asymmetrically. Frequent sites include the face, neck and upper extremities. Affected sites show a characteristical neutrophilic infiltrate in the upper dermis. Its etiology remains elucidated, but it seems that can be mediated by a hypersensitivity reaction in which cytokines, followed by infiltration of neutrophils, may be involved. Systemic corticosteroids are the first-line of treatment in most cases. We present a concise review of the pathogenesis, classification, diagnosis and treatment update of this entity. Copyright © 2015 AEDV. Published by Elsevier España, S.L.U. All rights reserved.

Towards an Obesity-Cancer Knowledge Base: Biomedical Entity Identification and Relation Detection

PubMed Central

Lossio-Ventura, Juan Antonio; Hogan, William; Modave, François; Hicks, Amanda; Hanna, Josh; Guo, Yi; He, Zhe; Bian, Jiang

2017-01-01

Obesity is associated with increased risks of various types of cancer, as well as a wide range of other chronic diseases. On the other hand, access to health information activates patient participation, and improve their health outcomes. However, existing online information on obesity and its relationship to cancer is heterogeneous ranging from pre-clinical models and case studies to mere hypothesis-based scientific arguments. A formal knowledge representation (i.e., a semantic knowledge base) would help better organizing and delivering quality health information related to obesity and cancer that consumers need. Nevertheless, current ontologies describing obesity, cancer and related entities are not designed to guide automatic knowledge base construction from heterogeneous information sources. Thus, in this paper, we present methods for named-entity recognition (NER) to extract biomedical entities from scholarly articles and for detecting if two biomedical entities are related, with the long term goal of building a obesity-cancer knowledge base. We leverage both linguistic and statistical approaches in the NER task, which supersedes the state-of-the-art results. Further, based on statistical features extracted from the sentences, our method for relation detection obtains an accuracy of 99.3% and a f-measure of 0.993. PMID:28503356

Super-hydrophobicity fundamentals: implications to biofouling prevention.

PubMed

Marmur, Abraham

2006-01-01

The theory of wetting on super-hydrophobic surfaces is presented and discussed, within the general framework of equilibrium wetting and contact angles. Emphasis is put on the implications of super-hydrophobicity to the prevention of biofouling. Two main lines of thought are discussed, viz. i) "mirror imaging" of the Lotus effect, namely designing a surface that repels biological entities by being super-hydrophilic, and ii) designing a surface that minimises the water-wetted area when submerged in water (by keeping an air film between the water and the surface), so that the suspended biological entities have a low probability of encountering the solid surface.

Taking the fifth amendment in Turing's imitation game

NASA Astrophysics Data System (ADS)

Warwick, Kevin; Shah, Huma

2017-03-01

In this paper, we look at a specific issue with practical Turing tests, namely the right of the machine to remain silent during interrogation. In particular, we consider the possibility of a machine passing the Turing test simply by not saying anything. We include a number of transcripts from practical Turing tests in which silence has actually occurred on the part of a hidden entity. Each of the transcripts considered here resulted in a judge being unable to make the 'right identification', i.e., they could not say for certain which hidden entity was the machine.

[Vinyl chloride and 1,2-dichloroethane: classification and assessment of carcinogenicity, guidelines, threshold values, and standards developed by national and international entities, organizations, and agencies].

PubMed

Binetti, R; Costamagna, F M; Marcello, I

2001-01-01

International, national and regulatory classification, evaluation, guidelines and occupational exposure values regarding vinyl chloride and 1,2-dichloroethane, carried out by European Union (EU). Environmental Protection Agency (US EPA), International Agency for Research on Cancer (IARC), Italian National Advisory Toxicological Committee (CCTN), Occupational Safety and Health Administration (OSHA), World Health Organization (WHO), National Institute for Occupational Safety and Health (NIOSH), American Conference of Governmental Industrial Hygienists (ACGIH) and other institutions, have been considered with particular reference to the carcinogenic effects. Moreover information is reported in support of classification and evaluation and a short historical review since early 1970s, when first evidence that occupational exposure to VC could lead to angiosarcoma was published.

NERBio: using selected word conjunctions, term normalization, and global patterns to improve biomedical named entity recognition.

PubMed

Tsai, Richard Tzong-Han; Sung, Cheng-Lung; Dai, Hong-Jie; Hung, Hsieh-Chuan; Sung, Ting-Yi; Hsu, Wen-Lian

2006-12-18

Biomedical named entity recognition (Bio-NER) is a challenging problem because, in general, biomedical named entities of the same category (e.g., proteins and genes) do not follow one standard nomenclature. They have many irregularities and sometimes appear in ambiguous contexts. In recent years, machine-learning (ML) approaches have become increasingly common and now represent the cutting edge of Bio-NER technology. This paper addresses three problems faced by ML-based Bio-NER systems. First, most ML approaches usually employ singleton features that comprise one linguistic property (e.g., the current word is capitalized) and at least one class tag (e.g., B-protein, the beginning of a protein name). However, such features may be insufficient in cases where multiple properties must be considered. Adding conjunction features that contain multiple properties can be beneficial, but it would be infeasible to include all conjunction features in an NER model since memory resources are limited and some features are ineffective. To resolve the problem, we use a sequential forward search algorithm to select an effective set of features. Second, variations in the numerical parts of biomedical terms (e.g., "2" in the biomedical term IL2) cause data sparseness and generate many redundant features. In this case, we apply numerical normalization, which solves the problem by replacing all numerals in a term with one representative numeral to help classify named entities. Third, the assignment of NE tags does not depend solely on the target word's closest neighbors, but may depend on words outside the context window (e.g., a context window of five consists of the current word plus two preceding and two subsequent words). We use global patterns generated by the Smith-Waterman local alignment algorithm to identify such structures and modify the results of our ML-based tagger. This is called pattern-based post-processing. To develop our ML-based Bio-NER system, we employ conditional random fields, which have performed effectively in several well-known tasks, as our underlying ML model. Adding selected conjunction features, applying numerical normalization, and employing pattern-based post-processing improve the F-scores by 1.67%, 1.04%, and 0.57%, respectively. The combined increase of 3.28% yields a total score of 72.98%, which is better than the baseline system that only uses singleton features. We demonstrate the benefits of using the sequential forward search algorithm to select effective conjunction feature groups. In addition, we show that numerical normalization can effectively reduce the number of redundant and unseen features. Furthermore, the Smith-Waterman local alignment algorithm can help ML-based Bio-NER deal with difficult cases that need longer context windows.

15 CFR 747.4 - Steps you must follow to apply for a SIRL.

Code of Federal Regulations, 2010 CFR

2010-01-01

... classifications, where available, as this will assist BIS to rule upon the application quickly. (2) Form BIS-748P... entity, the contract or work order which formed the basis of the transaction, and any identification number or project code for that contract or work order; (3) Explanation of how the project will...

THE PHYSICAL ASPECTS OF URBANIZATION, PHYSICAL CONSIDERATIONS IN COMMUNITY ACTION. KANSAS STATE UNIVERSITY SHORT COURSE SERIES IN PLANNING AND DEVELOPMENT, 5.

ERIC Educational Resources Information Center

MCGRAW, EUGENE T.

PART OF A KANSAS STATE UNIVERSITY SERIES ON COMMUNITY PLANNING AND DEVELOPMENT, THIS MONOGRAPH DESCRIBES AND DEFINES THE NATURE OF URBAN CENTERS AS PHYSICAL ENTITIES. BASIC LAND USE CATEGORIES AND SUBDIVISIONS, FUNCTIONAL CLASSIFICATIONS OF COMMUNITIES IN THE UNITED STATES (MANUFACTURING, RETAIL, WHOLESALE, DIVERSIFIED, TRANSPORTATION, MINING,…

Simple and Flexible Classification of Gene Expression Microarrays Via Swirls and Ripples | Division of Cancer Prevention

Cancer.gov

By Stuart G. Baker The program requires Mathematica 7.01.0 The key function is Classify [datalist,options] where datalist={data, genename, dataname} data ={matrix for class 0, matrix for class 1}, matrix is gene expression by specimen genename a list of names of genes, dataname ={name of data set, name of class0, name of class1} |

Type specimens and basic principles of avian taxonomy

USGS Publications Warehouse

Banks, Richard C.; Goodman, Steven M.; Lanyon, Scott M.; Schulenberg, Thomas S.

1993-01-01

"Ornithology" may be defined as the scientific study of birds. No aspect of avian biology, including management and conservation, can be carried out without reference by name to birds at some taxonomic level. Thus, the names of species of birds, and of groups of species, can fairly be considered to be of primary importance in ornithology. To be useful, these names themselves must be defined and related to biological entities. The definition of a name is accomplished by the designation of a "type." The International Code of Zoological Nomenclature, in paragraph (C) of Article 72 (third edition, 1985), establishes criteria for eligibility of a name-bearing type. The type of a species or sub-species name is the biological specimen defined by the name, and later use of the name implies specific or subspecific identity with the type. It is imperative, therefore, that a type be available for study and comparison so that the identity of other material with it can be established.

DOD’s POW/MIA Mission: Top-Level Leadership Attention Needed to Resolve Longstanding Challenges in Accounting for Missing Persons from Past Conflicts

DTIC Science & Technology

2013-07-01

ELEMENT NUMBER 6. AUTHOR (S) 5d. PROJECT NUMBER 5e. TASK NUMBER 5f. WORK UNIT NUMBER 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) U.S...persons for whom DOD must account. A committee report accompanying the National Defense Authorization Act for Fiscal Year 2013 mandated GAO to...many organizations and each reports through a different line of authority . Thus, no single entity is responsible for communitywide personnel and

To the Question about the Quality of Economic Education

ERIC Educational Resources Information Center

Dyshaeva, Lyudmila

2015-01-01

The article discusses the shortcomings of the methodology of neoclassical theory as a basic theory determining the content of contemporary economic theory course at Russian educational institutions namely unrealistic conditions of perfect competition, rationality of economic behavior of business entities, completeness and authenticity of…

47 CFR 27.1170 - Payment Issues.

Code of Federal Regulations, 2010 CFR

2010-10-01

... is required to file a notice containing site-specific data with the clearinghouse. The notice... name of the transmitting base station, the geographic coordinates corresponding to that base station... the site-data filing requirement by submitting a copy of their PCN to the clearinghouse. AWS entities...

78 FR 52553 - Privacy Act of 1974; Department of Homeland Security/ALL-035 Common Entity Index Prototype System...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-08-23

... data elements: Full Name; Alias(es); Gender; Date of Birth; Country of Birth; Country of Citizenship... locked drawer behind a locked door. The records may be stored on magnetic disc, tape, or digital media...

The 2015 WHO Classification of Tumors of the Thymus: Continuity and Changes

PubMed Central

Marx, Alexander; Chan, John K.C.; Coindre, Jean-Michel; Detterbeck, Frank; Girard, Nicolas; Harris, Nancy L.; Jaffe, Elaine S.; Kurrer, Michael O.; Marom, Edith M.; Moreira, Andre L.; Mukai, Kiyoshi; Orazi, Attilio; Ströbel, Philipp

2015-01-01

This overview of the 4th edition of the WHO Classification of thymic tumors has two aims. First, to comprehensively list the established and new tumour entities and variants that are described in the new WHO Classification of thymic epithelial tumors, germ cell tumors, lymphomas, dendritic cell and myeloid neoplasms, and soft tissue tumors of the thymus and mediastinum; second, to highlight major differences in the new WHO Classification that result from the progress that has been made since the 3rd edition in 2004 at immunohistochemical, genetic and conceptual levels. Refined diagnostic criteria for type A, AB, B1–B3 thymomas and thymic squamous cell carcinoma are given and will hopefully improve the reproducibility of the classification and its clinical relevance. The clinical perspective of the classification has been strengthened by involving experts from radiology, thoracic surgery and oncology; by incorporating state-of-the-art PET/CT images; and by depicting prototypic cytological specimens. This makes the thymus section of the new WHO Classification of Tumours of the Lung, Pleura, Thymus and Heart a valuable tool for pathologists, cytologists and clinicians alike. The impact of the new WHO Classification on therapeutic decisions is exemplified in this overview for thymic epithelial tumors and mediastinal lymphomas, and future perspectives and challenges are discussed. PMID:26295375

A Cladist is a systematist who seeks a natural classification: some comments on Quinn (2017).

PubMed

Williams, David M; Ebach, Malte C

2018-01-01

In response to Quinn (Biol Philos, 2017. 10.1007/s10539-017-9577-z) we identify cladistics to be about natural classifications and their discovery and thereby propose to add an eighth cladistic definition to Quinn's list, namely the systematist who seeks to discover natural classifications, regardless of their affiliation, theoretical or methodological justifications.

46 CFR 148.01-9 - Filing of special petition for special permit.

Code of Federal Regulations, 2010 CFR

2010-10-01

... permits, and any other supporting information. (4) The chemical name, common name, hazard classification...) Unless there is a good reason for priority treatment, each proposal is considered in the order in which...

Synopsis of Phyllosticta in China

PubMed Central

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

2015-01-01

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

TwiMed: Twitter and PubMed Comparable Corpus of Drugs, Diseases, Symptoms, and Their Relations

PubMed Central

Miyao, Yusuke; Collier, Nigel

2017-01-01

Background Work on pharmacovigilance systems using texts from PubMed and Twitter typically target at different elements and use different annotation guidelines resulting in a scenario where there is no comparable set of documents from both Twitter and PubMed annotated in the same manner. Objective This study aimed to provide a comparable corpus of texts from PubMed and Twitter that can be used to study drug reports from these two sources of information, allowing researchers in the area of pharmacovigilance using natural language processing (NLP) to perform experiments to better understand the similarities and differences between drug reports in Twitter and PubMed. Methods We produced a corpus comprising 1000 tweets and 1000 PubMed sentences selected using the same strategy and annotated at entity level by the same experts (pharmacists) using the same set of guidelines. Results The resulting corpus, annotated by two pharmacists, comprises semantically correct annotations for a set of drugs, diseases, and symptoms. This corpus contains the annotations for 3144 entities, 2749 relations, and 5003 attributes. Conclusions We present a corpus that is unique in its characteristics as this is the first corpus for pharmacovigilance curated from Twitter messages and PubMed sentences using the same data selection and annotation strategies. We believe this corpus will be of particular interest for researchers willing to compare results from pharmacovigilance systems (eg, classifiers and named entity recognition systems) when using data from Twitter and from PubMed. We hope that given the comprehensive set of drug names and the annotated entities and relations, this corpus becomes a standard resource to compare results from different pharmacovigilance studies in the area of NLP. PMID:28468748

TwiMed: Twitter and PubMed Comparable Corpus of Drugs, Diseases, Symptoms, and Their Relations.

PubMed

Alvaro, Nestor; Miyao, Yusuke; Collier, Nigel

2017-05-03

Work on pharmacovigilance systems using texts from PubMed and Twitter typically target at different elements and use different annotation guidelines resulting in a scenario where there is no comparable set of documents from both Twitter and PubMed annotated in the same manner. This study aimed to provide a comparable corpus of texts from PubMed and Twitter that can be used to study drug reports from these two sources of information, allowing researchers in the area of pharmacovigilance using natural language processing (NLP) to perform experiments to better understand the similarities and differences between drug reports in Twitter and PubMed. We produced a corpus comprising 1000 tweets and 1000 PubMed sentences selected using the same strategy and annotated at entity level by the same experts (pharmacists) using the same set of guidelines. The resulting corpus, annotated by two pharmacists, comprises semantically correct annotations for a set of drugs, diseases, and symptoms. This corpus contains the annotations for 3144 entities, 2749 relations, and 5003 attributes. We present a corpus that is unique in its characteristics as this is the first corpus for pharmacovigilance curated from Twitter messages and PubMed sentences using the same data selection and annotation strategies. We believe this corpus will be of particular interest for researchers willing to compare results from pharmacovigilance systems (eg, classifiers and named entity recognition systems) when using data from Twitter and from PubMed. We hope that given the comprehensive set of drug names and the annotated entities and relations, this corpus becomes a standard resource to compare results from different pharmacovigilance studies in the area of NLP. ©Nestor Alvaro, Yusuke Miyao, Nigel Collier. Originally published in JMIR Public Health and Surveillance (http://publichealth.jmir.org), 03.05.2017.

Clinical application of modified bag-of-features coupled with hybrid neural-based classifier in dengue fever classification using gene expression data.

PubMed

Chatterjee, Sankhadeep; Dey, Nilanjan; Shi, Fuqian; Ashour, Amira S; Fong, Simon James; Sen, Soumya

2018-04-01

Dengue fever detection and classification have a vital role due to the recent outbreaks of different kinds of dengue fever. Recently, the advancement in the microarray technology can be employed for such classification process. Several studies have established that the gene selection phase takes a significant role in the classifier performance. Subsequently, the current study focused on detecting two different variations, namely, dengue fever (DF) and dengue hemorrhagic fever (DHF). A modified bag-of-features method has been proposed to select the most promising genes in the classification process. Afterward, a modified cuckoo search optimization algorithm has been engaged to support the artificial neural (ANN-MCS) to classify the unknown subjects into three different classes namely, DF, DHF, and another class containing convalescent and normal cases. The proposed method has been compared with other three well-known classifiers, namely, multilayer perceptron feed-forward network (MLP-FFN), artificial neural network (ANN) trained with cuckoo search (ANN-CS), and ANN trained with PSO (ANN-PSO). Experiments have been carried out with different number of clusters for the initial bag-of-features-based feature selection phase. After obtaining the reduced dataset, the hybrid ANN-MCS model has been employed for the classification process. The results have been compared in terms of the confusion matrix-based performance measuring metrics. The experimental results indicated a highly statistically significant improvement with the proposed classifier over the traditional ANN-CS model.

A pilot study for distinguishing chromophobe renal cell carcinoma and oncocytoma using second harmonic generation imaging and convolutional neural network analysis of collagen fibrillar structure

NASA Astrophysics Data System (ADS)

Judd, Nicolas; Smith, Jason; Jain, Manu; Mukherjee, Sushmita; Icaza, Michael; Gallagher, Ryan; Szeligowski, Richard; Wu, Binlin

2018-02-01

A clear distinction between oncocytoma and chromophobe renal cell carcinoma (chRCC) is critically important for clinical management of patients. But it may often be difficult to distinguish the two entities based on hematoxylin and eosin (H and E) stained sections alone. In this study, second harmonic generation (SHG) signals which are very specific to collagen were used to image collagen fibril structure. We conduct a pilot study to develop a new diagnostic method based on the analysis of collagen associated with kidney tumors using convolutional neural networks (CNNs). CNNs comprise a type of machine learning process well-suited for drawing information out of images. This study examines a CNN model's ability to differentiate between oncocytoma (benign), and chRCC (malignant) kidney tumor images acquired with second harmonic generation (SHG), which is very specific for collagen matrix. To the best of our knowledge, this is the first study that attempts to distinguish the two entities based on their collagen structure. The model developed from this study demonstrated an overall classification accuracy of 68.7% with a specificity of 66.3% and sensitivity of 74.6%. While these results reflect an ability to classify the kidney tumors better than chance, further studies will be carried out to (a) better realize the tumor classification potential of this method with a larger sample size and (b) combining SHG with two-photon excited intrinsic fluorescence signal to achieve better classification.

5 CFR 581.203 - Information minimally required to accompany legal process.

Code of Federal Regulations, 2014 CFR

2014-01-01

... accompany legal process. 581.203 Section 581.203 Administrative Personnel OFFICE OF PERSONNEL MANAGEMENT... Process § 581.203 Information minimally required to accompany legal process. (a) Sufficient identifying information must accompany the legal process in order to enable processing by the governmental entity named...

5 CFR 581.203 - Information minimally required to accompany legal process.

Code of Federal Regulations, 2011 CFR

2011-01-01

... accompany legal process. 581.203 Section 581.203 Administrative Personnel OFFICE OF PERSONNEL MANAGEMENT... Process § 581.203 Information minimally required to accompany legal process. (a) Sufficient identifying information must accompany the legal process in order to enable processing by the governmental entity named...

5 CFR 581.203 - Information minimally required to accompany legal process.

Code of Federal Regulations, 2013 CFR

2013-01-01

... accompany legal process. 581.203 Section 581.203 Administrative Personnel OFFICE OF PERSONNEL MANAGEMENT... Process § 581.203 Information minimally required to accompany legal process. (a) Sufficient identifying information must accompany the legal process in order to enable processing by the governmental entity named...

5 CFR 581.203 - Information minimally required to accompany legal process.

Code of Federal Regulations, 2012 CFR

2012-01-01

... accompany legal process. 581.203 Section 581.203 Administrative Personnel OFFICE OF PERSONNEL MANAGEMENT... Process § 581.203 Information minimally required to accompany legal process. (a) Sufficient identifying information must accompany the legal process in order to enable processing by the governmental entity named...

5 CFR 581.203 - Information minimally required to accompany legal process.

Code of Federal Regulations, 2010 CFR

2010-01-01

... accompany legal process. 581.203 Section 581.203 Administrative Personnel OFFICE OF PERSONNEL MANAGEMENT... Process § 581.203 Information minimally required to accompany legal process. (a) Sufficient identifying information must accompany the legal process in order to enable processing by the governmental entity named...

Linked Data for Software Security Concepts and Vulnerability Descriptions

DTIC Science & Technology

2013-07-01

named entity (NE) extractors such as DBpedia Spotlight, Alchemy API1, Extractiv2, OpenCalais3 and Zemanta were compared for their overall performance...presents substantial agreement for URI dis- ambiguation. Alchemy API, although preserving good performance in NE extraction and 1http://www.alchemyapi.com

25 CFR 141.23 - Posted statement of ownership.

Code of Federal Regulations, 2010 CFR

2010-04-01

... legible to customers stating the form of the business entity, the names and addresses of all other... Indians BUREAU OF INDIAN AFFAIRS, DEPARTMENT OF THE INTERIOR FINANCIAL ACTIVITIES BUSINESS PRACTICES ON THE NAVAJO, HOPI AND ZUNI RESERVATIONS General Business Practices § 141.23 Posted statement of...

Rapid Training of Information Extraction with Local and Global Data Views

DTIC Science & Technology

2012-05-01

relation type extension system based on active learning a relation type extension system based on semi-supervised learning, and a crossdomain...bootstrapping system for domain adaptive named entity extraction. The active learning procedure adopts features extracted at the sentence level as the local

78 FR 50396 - Common Format for Federal Entity Transition Plans

Federal Register 2010, 2011, 2012, 2013, 2014

2013-08-19

..., Associate Administrator, Office of Spectrum Management. [FR Doc. 2013-20149 Filed 8-16-13; 8:45 am] BILLING..., Office of Spectrum Management. Each commenter should include the name of the person or organization... Spectrum Management, National Telecommunications and Information Administration, U.S. Department of...

BVDV: Detection, Risk Management and Control

USDA-ARS?s Scientific Manuscript database

The terms bovine viral diarrhea (BVD) and bovine viral diarrhea viruses (BVDV) are difficult to define in simple straightforward statements because both are umbrella terms covering a wide range of observations and entities. While diarrhea is in the name, BVD, it is used in reference to a number of ...

Report of a rare case and review of adult intestinal duplication at the opposite side of mesenteric margin.

PubMed

Huang, Zhi-Hao; Wan, Zi-Hao; Vikash, Vikash; Vikash, Sindhu; Jiang, Cong-Qing

2018-01-01

To study the previously discovered clinical entity of adult intestinal duplication and its treatment, and propose an extension to its existing classification. We report the case of an adult male with abdominal pain, constipation and vomiting. This patient underwent surgical separation of adhesions, reduction of torsion and intestinal decompression. Postoperative pathological findings confirmed the rare diagnosis of intestinal duplication. Adult intestinal duplication is quite rare. Its clinical manifestations are nonspecific. From this finding of intestinal duplication originating at the opposite side of the mesenteric margin, a further extension of the existing anatomical classification is proposed.

The Classification and Evaluation of Computer-Aided Software Engineering Tools

DTIC Science & Technology

1990-09-01

International Business Machines Corporation Customizer is a Registered Trademark of Index Technology Corporation Data Analyst is a Registered Trademark of...years, a rapid series of new approaches have been adopted including: information engineering, entity- relationship modeling, automatic code generation...support true information sharing among tools and automated consistency checking. Moreover, the repository must record and manage the relationships and

78 FR 42875 - Community Right-to-Know; Adoption of 2012 North American Industry Classification System (NAICS...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-07-18

....regulations.gov or email. The www.regulations.gov Web site is an ``anonymous access'' system, which means EPA.../ . SUPPLEMENTARY INFORMATION: I. Why is EPA using a direct final rule? EPA is publishing this rule without a prior... entity, consult the person listed in the FOR FURTHER INFORMATION CONTACT section. III. What should I...

The Importance of Being Coherent: Category Coherence, Cross-Classification, and Reasoning

ERIC Educational Resources Information Center

Patalano, Andrea L.; Chin-Parker, Seth; Ross, Brian H.

2006-01-01

Category-based inference is crucial for using past experiences to make sense of new ones. One challenge to inference of this kind is that most entities in the world belong to multiple categories (e.g., a jogger, a professor, and a vegetarian). We tested the hypothesis that the "degree of coherence" of a category-the degree to which category…

U.S. Coast Guard Fleet Mix Planning: A Decision Support System Prototype

DTIC Science & Technology

1991-03-01

91-16785 Al ’ 1 1 1 Unclassified SECURITY CLASSIFICATION OF ThIS PAGE REPORT DOCUMENTATION PAGE I L REPORTSECURITY CLASSIFICATION lb. RESTRICTIVE...MARKINGS Unclassified 2a. SECURITY CLASSIFICATION AUTHORITY 3. DISTRIBUTION/ AVAILABITY OF REPORT Approved for public release; distribution is inlimited...2b. DECIASSIFICATION/DOWNGRADING SCHEDULE 4. PERFORMING ORGANIZATION REPORT NUMBER(S) 5. MONITORING ORGANIZATION REPORT NUMBER(S) 6a. NAME OF

Low-Level Wind Systems in the Warsaw Pact Countries.

DTIC Science & Technology

1985-03-01

CLASSIFICATION OF THIS PAGE o i REPORT DOCUMENTATION PAGE I le. REPORT SECURITY CLASSIFICATION lb. RESTRICTIVE MARKINGS Unclassified 2e, SECURITY...CLASSIFICATION AUTHORITY 3. OISTRIBUTION/AVAI LAOBILfTY OF REPORT 2b. ECLSSIICAIONDOWNRADNG CHEULEApproved for public release; distribution * 2b OELASSFICTIO...OOWGRAING CHEULEunlimited * 4. PERFORMING ORGANIZATION REPORT NUMBER(S) 5. MONITORING ORGANIZATION REPORT NUMBER(S) USAFETAC/TN-85/0Ol 6a. NAME OF

Text mining in livestock animal science: introducing the potential of text mining to animal sciences.

PubMed

Sahadevan, S; Hofmann-Apitius, M; Schellander, K; Tesfaye, D; Fluck, J; Friedrich, C M

2012-10-01

In biological research, establishing the prior art by searching and collecting information already present in the domain has equal importance as the experiments done. To obtain a complete overview about the relevant knowledge, researchers mainly rely on 2 major information sources: i) various biological databases and ii) scientific publications in the field. The major difference between the 2 information sources is that information from databases is available, typically well structured and condensed. The information content in scientific literature is vastly unstructured; that is, dispersed among the many different sections of scientific text. The traditional method of information extraction from scientific literature occurs by generating a list of relevant publications in the field of interest and manually scanning these texts for relevant information, which is very time consuming. It is more than likely that in using this "classical" approach the researcher misses some relevant information mentioned in the literature or has to go through biological databases to extract further information. Text mining and named entity recognition methods have already been used in human genomics and related fields as a solution to this problem. These methods can process and extract information from large volumes of scientific text. Text mining is defined as the automatic extraction of previously unknown and potentially useful information from text. Named entity recognition (NER) is defined as the method of identifying named entities (names of real world objects; for example, gene/protein names, drugs, enzymes) in text. In animal sciences, text mining and related methods have been briefly used in murine genomics and associated fields, leaving behind other fields of animal sciences, such as livestock genomics. The aim of this work was to develop an information retrieval platform in the livestock domain focusing on livestock publications and the recognition of relevant data from cattle and pigs. For this purpose, the rather noncomprehensive resources of pig and cattle gene and protein terminologies were enriched with orthologue synonyms, integrated in the NER platform, ProMiner, which is successfully used in human genomics domain. Based on the performance tests done, the present system achieved a fair performance with precision 0.64, recall 0.74, and F(1) measure of 0.69 in a test scenario based on cattle literature.

Using Ontology Fingerprints to disambiguate gene name entities in the biomedical literature

PubMed Central

Chen, Guocai; Zhao, Jieyi; Cohen, Trevor; Tao, Cui; Sun, Jingchun; Xu, Hua; Bernstam, Elmer V.; Lawson, Andrew; Zeng, Jia; Johnson, Amber M.; Holla, Vijaykumar; Bailey, Ann M.; Lara-Guerra, Humberto; Litzenburger, Beate; Meric-Bernstam, Funda; Jim Zheng, W.

2015-01-01

Ambiguous gene names in the biomedical literature are a barrier to accurate information extraction. To overcome this hurdle, we generated Ontology Fingerprints for selected genes that are relevant for personalized cancer therapy. These Ontology Fingerprints were used to evaluate the association between genes and biomedical literature to disambiguate gene names. We obtained 93.6% precision for the test gene set and 80.4% for the area under a receiver-operating characteristics curve for gene and article association. The core algorithm was implemented using a graphics processing unit-based MapReduce framework to handle big data and to improve performance. We conclude that Ontology Fingerprints can help disambiguate gene names mentioned in text and analyse the association between genes and articles. Database URL: http://www.ontologyfingerprint.org PMID:25858285

Classification of lymphoid neoplasms: the microscope as a tool for disease discovery

PubMed Central

Harris, Nancy Lee; Stein, Harald; Isaacson, Peter G.

2008-01-01

In the past 50 years, we have witnessed explosive growth in the understanding of normal and neoplastic lymphoid cells. B-cell, T-cell, and natural killer (NK)–cell neoplasms in many respects recapitulate normal stages of lymphoid cell differentiation and function, so that they can be to some extent classified according to the corresponding normal stage. Likewise, the molecular mechanisms involved the pathogenesis of lymphomas and lymphoid leukemias are often based on the physiology of the lymphoid cells, capitalizing on deregulated normal physiology by harnessing the promoters of genes essential for lymphocyte function. The clinical manifestations of lymphomas likewise reflect the normal function of lymphoid cells in vivo. The multiparameter approach to classification adopted by the World Health Organization (WHO) classification has been validated in international studies as being highly reproducible, and enhancing the interpretation of clinical and translational studies. In addition, accurate and precise classification of disease entities facilitates the discovery of the molecular basis of lymphoid neoplasms in the basic science laboratory. PMID:19029456

Integrated Internet based tools for learning and evaluating the International Classification of Nursing Practice.

PubMed

Alecu, C S; Jitaru, E; Moisil, I

2000-01-01

This paper presents some tools designed and implemented for learning-related purposes; these tools can be downloaded or run on the TeleNurse web site. Among other facilities, TeleNurse web site is hosting now the version 1.2 of SysTerN (terminology system for nursing) which can be downloaded on request and also the "Evaluation of Translation" form which has been designed in order to improve the Romanian translation of the ICNP (the International Classification of Nursing Practice). SysTerN has been developed using the framework of the TeleNurse ID--ENTITY Telematics for Health EU project. This version is using the beta version of ICNP containing Phenomena and Actions classification. This classification is intended to facilitate documentation of nursing practice, by providing a terminology or vocabulary for use in the description of the nursing process. The TeleNurse site is bilingual, Romanian-English, in order to enlarge the discussion forum with members from other CEE (or Non-CEE) countries.

Reconsidering the classification of tick-borne encephalitis virus within the Siberian subtype gives new insights into its evolutionary history.

PubMed

Kovalev, S Y; Mukhacheva, T A

2017-11-01

Tick-borne encephalitis is widespread in Eurasia and transmitted by Ixodes ticks. Classification of its causative agent, tick-borne encephalitis virus (TBEV), includes three subtypes, namely Far-Eastern, European, and Siberian (TBEV-Sib), as well as a group of 886-84-like strains with uncertain taxonomic status. TBEV-Sib is subdivided into three phylogenetic lineages: Baltic, Asian, and South-Siberian. A reason to reconsider TBEV-Sib classification was the analysis of 186 nucleotide sequences of an E gene fragment submitted to GenBank during the last two years. Within the South-Siberian lineage, we have identified a distinct group with prototype strains Aina and Vasilchenko as an individual lineage named East-Siberian. The analysis of reclassified lineages has promoted a new model of the evolutionary history of TBEV-Sib lineages and TBEV-Sib as a whole. Moreover, we present arguments supporting separation of 886-84-like strains into an individual TBEV subtype, which we propose to name Baikalian (TBEV-Bkl). Copyright © 2017 Elsevier B.V. All rights reserved.

Nomenclature and the National Wetland Plant List

DTIC Science & Technology

2009-05-01

older or previously used scientific names that are no longer viewed as acceptable or accurate based on current standards and ideology ). All synonyms...name ) classification system (one name to indicate the genus one to indicate the species). Scientific names, consisting of genus and species...mostly of either Greek or Latin origin, make up the binomial. An example is Acer rubrum L., where Acer is the genus , rubrum is the species, and L. is the

12 CFR 612.2145 - Director reporting.

Code of Federal Regulations, 2010 CFR

2010-01-01

...) The name and the nature of the business of any entity in which the director has a material financial... activity that is required to be reported under this section or could constitute a conflict of interest... determination of whether the relationship, transaction, or activity is, in fact, a conflict of interest. (d...

Proposal to conserve Tamarix ramosissima against T. pentandra Tamaricaceae)

USDA-ARS?s Scientific Manuscript database

Ledebour described Tamarix ramosissima in 1829 from plants collected in Kazakhstan (Lake Noor Zaisan). In the protologue he overlooked T. pentandra Pall. (l.c.) and T. pallasii Desv. (l.c.), two earlier names which apply to the same biological entity, also widespread through Central and Western Asia...

78 FR 23194 - Federal Acquisition Regulation; Commercial and Government Entity Code

Federal Register 2010, 2011, 2012, 2013, 2014

2013-04-18

... Award Management Name Change, Phase 1 Implementation) which will make a global update to all of the... outside the United States; and Support supply chain traceability and integrity efforts. II. Discussion and.... For Contractors registered in the System for Award Management (SAM), the DLA Logistics Information...

ALDOL REACTION VIA IN SITU OLEFIN MIGRATION IN WATER. (R828129)

EPA Science Inventory

Mingwen Wang and Chao-Jun Li

Department of Chemistry, Tulane University, Ne...

The Role of Instruments in Three Chemical Revolutions

ERIC Educational Resources Information Center

Chamizo, José Antonio

2014-01-01

This paper attempts to show one of the ways history of chemistry can be teachable for chemistry teachers, it means something more than an undifferentiated mass of names and dates, establishing a temporal framework based on chemical entities that all students use. Represents a difficult equilibrium between over-simplification versus…

47 CFR 52.15 - Central office code administration.

Code of Federal Regulations, 2010 CFR

2010-10-01

... forecast data to the NANPA. (ii) Reporting shall be by separate legal entity and must include company name, company headquarters address, Operating Company Number (OCN), parent company OCN, and the primary type of... headquarters address, OCN, parent company's OCN(s), and the primary type of business in which the numbering...

40 CFR 59.501 - Am I subject to this subpart?

Code of Federal Regulations, 2010 CFR

2010-07-01

... (CONTINUED) NATIONAL VOLATILE ORGANIC COMPOUND EMISSION STANDARDS FOR CONSUMER AND COMMERCIAL PRODUCTS... subpart? (a) The regulated entities for an aerosol coating product are the manufacturer or importer of an aerosol coating product and a distributor of an aerosol coating product if it is named on the label or if...

Americans With Disabilities Act (ADA) Accessibility Guidelines for Transportation Vehicles. Final rule.

PubMed

2016-12-14

The Architectural and Transportation Barriers Compliance Board (Access Board or Board) is issuing a final rule that revises its existing accessibility guidelines for non-rail vehicles--namely, buses, over-the-road buses, and vans--acquired or remanufactured by entities covered by the Americans with Disabilities Act. The revised guidelines ensure that such vehicles are readily accessible to, and usable by, individuals with disabilities. The U.S. Department of Transportation (DOT) is required to revise its accessibility standards for transportation vehicles acquired or remanufactured by entities covered by the Americans with Disabilities Act (ADA) to be consistent with the final rule.

Classification Algorithms for Big Data Analysis, a Map Reduce Approach

NASA Astrophysics Data System (ADS)

Ayma, V. A.; Ferreira, R. S.; Happ, P.; Oliveira, D.; Feitosa, R.; Costa, G.; Plaza, A.; Gamba, P.

2015-03-01

Since many years ago, the scientific community is concerned about how to increase the accuracy of different classification methods, and major achievements have been made so far. Besides this issue, the increasing amount of data that is being generated every day by remote sensors raises more challenges to be overcome. In this work, a tool within the scope of InterIMAGE Cloud Platform (ICP), which is an open-source, distributed framework for automatic image interpretation, is presented. The tool, named ICP: Data Mining Package, is able to perform supervised classification procedures on huge amounts of data, usually referred as big data, on a distributed infrastructure using Hadoop MapReduce. The tool has four classification algorithms implemented, taken from WEKA's machine learning library, namely: Decision Trees, Naïve Bayes, Random Forest and Support Vector Machines (SVM). The results of an experimental analysis using a SVM classifier on data sets of different sizes for different cluster configurations demonstrates the potential of the tool, as well as aspects that affect its performance.

Web 2.0-Based Crowdsourcing for High-Quality Gold Standard Development in Clinical Natural Language Processing

PubMed Central

Deleger, Louise; Li, Qi; Kaiser, Megan; Stoutenborough, Laura

2013-01-01

Background A high-quality gold standard is vital for supervised, machine learning-based, clinical natural language processing (NLP) systems. In clinical NLP projects, expert annotators traditionally create the gold standard. However, traditional annotation is expensive and time-consuming. To reduce the cost of annotation, general NLP projects have turned to crowdsourcing based on Web 2.0 technology, which involves submitting smaller subtasks to a coordinated marketplace of workers on the Internet. Many studies have been conducted in the area of crowdsourcing, but only a few have focused on tasks in the general NLP field and only a handful in the biomedical domain, usually based upon very small pilot sample sizes. In addition, the quality of the crowdsourced biomedical NLP corpora were never exceptional when compared to traditionally-developed gold standards. The previously reported results on medical named entity annotation task showed a 0.68 F-measure based agreement between crowdsourced and traditionally-developed corpora. Objective Building upon previous work from the general crowdsourcing research, this study investigated the usability of crowdsourcing in the clinical NLP domain with special emphasis on achieving high agreement between crowdsourced and traditionally-developed corpora. Methods To build the gold standard for evaluating the crowdsourcing workers’ performance, 1042 clinical trial announcements (CTAs) from the ClinicalTrials.gov website were randomly selected and double annotated for medication names, medication types, and linked attributes. For the experiments, we used CrowdFlower, an Amazon Mechanical Turk-based crowdsourcing platform. We calculated sensitivity, precision, and F-measure to evaluate the quality of the crowd’s work and tested the statistical significance (P<.001, chi-square test) to detect differences between the crowdsourced and traditionally-developed annotations. Results The agreement between the crowd’s annotations and the traditionally-generated corpora was high for: (1) annotations (0.87, F-measure for medication names; 0.73, medication types), (2) correction of previous annotations (0.90, medication names; 0.76, medication types), and excellent for (3) linking medications with their attributes (0.96). Simple voting provided the best judgment aggregation approach. There was no statistically significant difference between the crowd and traditionally-generated corpora. Our results showed a 27.9% improvement over previously reported results on medication named entity annotation task. Conclusions This study offers three contributions. First, we proved that crowdsourcing is a feasible, inexpensive, fast, and practical approach to collect high-quality annotations for clinical text (when protected health information was excluded). We believe that well-designed user interfaces and rigorous quality control strategy for entity annotation and linking were critical to the success of this work. Second, as a further contribution to the Internet-based crowdsourcing field, we will publicly release the JavaScript and CrowdFlower Markup Language infrastructure code that is necessary to utilize CrowdFlower’s quality control and crowdsourcing interfaces for named entity annotations. Finally, to spur future research, we will release the CTA annotations that were generated by traditional and crowdsourced approaches. PMID:23548263

Evaluation of linear classifiers on articles containing pharmacokinetic evidence of drug-drug interactions.

PubMed

Kolchinsky, A; Lourenço, A; Li, L; Rocha, L M

2013-01-01

Drug-drug interaction (DDI) is a major cause of morbidity and mortality. DDI research includes the study of different aspects of drug interactions, from in vitro pharmacology, which deals with drug interaction mechanisms, to pharmaco-epidemiology, which investigates the effects of DDI on drug efficacy and adverse drug reactions. Biomedical literature mining can aid both kinds of approaches by extracting relevant DDI signals from either the published literature or large clinical databases. However, though drug interaction is an ideal area for translational research, the inclusion of literature mining methodologies in DDI workflows is still very preliminary. One area that can benefit from literature mining is the automatic identification of a large number of potential DDIs, whose pharmacological mechanisms and clinical significance can then be studied via in vitro pharmacology and in populo pharmaco-epidemiology. We implemented a set of classifiers for identifying published articles relevant to experimental pharmacokinetic DDI evidence. These documents are important for identifying causal mechanisms behind putative drug-drug interactions, an important step in the extraction of large numbers of potential DDIs. We evaluate performance of several linear classifiers on PubMed abstracts, under different feature transformation and dimensionality reduction methods. In addition, we investigate the performance benefits of including various publicly-available named entity recognition features, as well as a set of internally-developed pharmacokinetic dictionaries. We found that several classifiers performed well in distinguishing relevant and irrelevant abstracts. We found that the combination of unigram and bigram textual features gave better performance than unigram features alone, and also that normalization transforms that adjusted for feature frequency and document length improved classification. For some classifiers, such as linear discriminant analysis (LDA), proper dimensionality reduction had a large impact on performance. Finally, the inclusion of NER features and dictionaries was found not to help classification.

Integrated Bio-Entity Network: A System for Biological Knowledge Discovery

PubMed Central

Bell, Lindsey; Chowdhary, Rajesh; Liu, Jun S.; Niu, Xufeng; Zhang, Jinfeng

2011-01-01

A significant part of our biological knowledge is centered on relationships between biological entities (bio-entities) such as proteins, genes, small molecules, pathways, gene ontology (GO) terms and diseases. Accumulated at an increasing speed, the information on bio-entity relationships is archived in different forms at scattered places. Most of such information is buried in scientific literature as unstructured text. Organizing heterogeneous information in a structured form not only facilitates study of biological systems using integrative approaches, but also allows discovery of new knowledge in an automatic and systematic way. In this study, we performed a large scale integration of bio-entity relationship information from both databases containing manually annotated, structured information and automatic information extraction of unstructured text in scientific literature. The relationship information we integrated in this study includes protein–protein interactions, protein/gene regulations, protein–small molecule interactions, protein–GO relationships, protein–pathway relationships, and pathway–disease relationships. The relationship information is organized in a graph data structure, named integrated bio-entity network (IBN), where the vertices are the bio-entities and edges represent their relationships. Under this framework, graph theoretic algorithms can be designed to perform various knowledge discovery tasks. We designed breadth-first search with pruning (BFSP) and most probable path (MPP) algorithms to automatically generate hypotheses—the indirect relationships with high probabilities in the network. We show that IBN can be used to generate plausible hypotheses, which not only help to better understand the complex interactions in biological systems, but also provide guidance for experimental designs. PMID:21738677

Determining similarity of scientific entities in annotation datasets

PubMed Central

Palma, Guillermo; Vidal, Maria-Esther; Haag, Eric; Raschid, Louiqa; Thor, Andreas

2015-01-01

Linked Open Data initiatives have made available a diversity of scientific collections where scientists have annotated entities in the datasets with controlled vocabulary terms from ontologies. Annotations encode scientific knowledge, which is captured in annotation datasets. Determining relatedness between annotated entities becomes a building block for pattern mining, e.g. identifying drug–drug relationships may depend on the similarity of the targets that interact with each drug. A diversity of similarity measures has been proposed in the literature to compute relatedness between a pair of entities. Each measure exploits some knowledge including the name, function, relationships with other entities, taxonomic neighborhood and semantic knowledge. We propose a novel general-purpose annotation similarity measure called ‘AnnSim’ that measures the relatedness between two entities based on the similarity of their annotations. We model AnnSim as a 1–1 maximum weight bipartite match and exploit properties of existing solvers to provide an efficient solution. We empirically study the performance of AnnSim on real-world datasets of drugs and disease associations from clinical trials and relationships between drugs and (genomic) targets. Using baselines that include a variety of measures, we identify where AnnSim can provide a deeper understanding of the semantics underlying the relatedness of a pair of entities or where it could lead to predicting new links or identifying potential novel patterns. Although AnnSim does not exploit knowledge or properties of a particular domain, its performance compares well with a variety of state-of-the-art domain-specific measures. Database URL: http://www.yeastgenome.org/ PMID:25725057

Determining similarity of scientific entities in annotation datasets.

PubMed

Palma, Guillermo; Vidal, Maria-Esther; Haag, Eric; Raschid, Louiqa; Thor, Andreas

2015-01-01

Linked Open Data initiatives have made available a diversity of scientific collections where scientists have annotated entities in the datasets with controlled vocabulary terms from ontologies. Annotations encode scientific knowledge, which is captured in annotation datasets. Determining relatedness between annotated entities becomes a building block for pattern mining, e.g. identifying drug-drug relationships may depend on the similarity of the targets that interact with each drug. A diversity of similarity measures has been proposed in the literature to compute relatedness between a pair of entities. Each measure exploits some knowledge including the name, function, relationships with other entities, taxonomic neighborhood and semantic knowledge. We propose a novel general-purpose annotation similarity measure called 'AnnSim' that measures the relatedness between two entities based on the similarity of their annotations. We model AnnSim as a 1-1 maximum weight bipartite match and exploit properties of existing solvers to provide an efficient solution. We empirically study the performance of AnnSim on real-world datasets of drugs and disease associations from clinical trials and relationships between drugs and (genomic) targets. Using baselines that include a variety of measures, we identify where AnnSim can provide a deeper understanding of the semantics underlying the relatedness of a pair of entities or where it could lead to predicting new links or identifying potential novel patterns. Although AnnSim does not exploit knowledge or properties of a particular domain, its performance compares well with a variety of state-of-the-art domain-specific measures. Database URL: http://www.yeastgenome.org/ © The Author(s) 2015. Published by Oxford University Press.

Inventorship and Authorship

PubMed Central

Konski, Antoinette F.; Wu, Linda X.

2015-01-01

Ownership of a U.S. patent is based on inventorship. In the United States, an inventor is the owner of the claimed invention unless it is assigned to another entity. The correct naming of inventors is important, and the improper naming of inventors in a patent can be grounds for rendering the patent unenforceable. Each inventor must make an intellectual contribution, solely or jointly, to at least one element of a claim in the patent. This is in contrast to authorship of a research article, where authors may be named to acknowledge contribution to the reported research rather than an intellectual contribution. Thus, identifying inventors for a patent is not the same as identifying authors for a publication. PMID:26253091

Abiotic Supramolecular Systems

DTIC Science & Technology

2011-05-02

REPORT Abiotic Supramolecular Systems 14. ABSTRACT 16. SECURITY CLASSIFICATION OF: The goal of this research project was to develop new concepts for the...decision, unless so designated by other documentation. 12. DISTRIBUTION AVAILIBILITY STATEMENT Approved for Public Release; Distribution Unlimited UU...9. SPONSORING/MONITORING AGENCY NAME(S) AND ADDRESS(ES) 6. AUTHORS 7. PERFORMING ORGANIZATION NAMES AND ADDRESSES U.S. Army Research Office P.O

A modular framework for biomedical concept recognition

PubMed Central

2013-01-01

Background Concept recognition is an essential task in biomedical information extraction, presenting several complex and unsolved challenges. The development of such solutions is typically performed in an ad-hoc manner or using general information extraction frameworks, which are not optimized for the biomedical domain and normally require the integration of complex external libraries and/or the development of custom tools. Results This article presents Neji, an open source framework optimized for biomedical concept recognition built around four key characteristics: modularity, scalability, speed, and usability. It integrates modules for biomedical natural language processing, such as sentence splitting, tokenization, lemmatization, part-of-speech tagging, chunking and dependency parsing. Concept recognition is provided through dictionary matching and machine learning with normalization methods. Neji also integrates an innovative concept tree implementation, supporting overlapped concept names and respective disambiguation techniques. The most popular input and output formats, namely Pubmed XML, IeXML, CoNLL and A1, are also supported. On top of the built-in functionalities, developers and researchers can implement new processing modules or pipelines, or use the provided command-line interface tool to build their own solutions, applying the most appropriate techniques to identify heterogeneous biomedical concepts. Neji was evaluated against three gold standard corpora with heterogeneous biomedical concepts (CRAFT, AnEM and NCBI disease corpus), achieving high performance results on named entity recognition (F1-measure for overlap matching: species 95%, cell 92%, cellular components 83%, gene and proteins 76%, chemicals 65%, biological processes and molecular functions 63%, disorders 85%, and anatomical entities 82%) and on entity normalization (F1-measure for overlap name matching and correct identifier included in the returned list of identifiers: species 88%, cell 71%, cellular components 72%, gene and proteins 64%, chemicals 53%, and biological processes and molecular functions 40%). Neji provides fast and multi-threaded data processing, annotating up to 1200 sentences/second when using dictionary-based concept identification. Conclusions Considering the provided features and underlying characteristics, we believe that Neji is an important contribution to the biomedical community, streamlining the development of complex concept recognition solutions. Neji is freely available at http://bioinformatics.ua.pt/neji. PMID:24063607

A Framework for Classifying and Resolving Semantic Conflicts Using the Enhanced Entity-Relationship Model

DTIC Science & Technology

1992-09-01

rank, social security number, and date of birth, sex , race, etc. It also keeps data on marital status, number of dependents, and whether a member’s...specification as listed in the appendix. OPINS stores similar common personnel information to that in the ADMI database, such as name, rank, sex , etc.. The...34+ NAME (comp) "+ DATE..OF-.BIRTH (comp) "+ SEX "+ BACE-MIHNIC "+ ETHNIC..GROUP "+ PAYýENTRY-.BASE..DATE (comp) "+ SERVICE "+ MOS (comp) "+ DATE-OF

OCLC Participating Institutions: Arranged by Network and Subarranged by Institution Name.

ERIC Educational Resources Information Center

OCLC Online Computer Library Center, Inc., Dublin, OH.

This directory of institutions participating in the Ohio College Library Center (OCLC) presents the following information for each: assigned OCLC symbol, institution name and address, affiliated network, classification scheme in use, and identification symbol assigned by Library of Congress. (SC)

Physical Human Activity Recognition Using Wearable Sensors.

PubMed

Attal, Ferhat; Mohammed, Samer; Dedabrishvili, Mariam; Chamroukhi, Faicel; Oukhellou, Latifa; Amirat, Yacine

2015-12-11

This paper presents a review of different classification techniques used to recognize human activities from wearable inertial sensor data. Three inertial sensor units were used in this study and were worn by healthy subjects at key points of upper/lower body limbs (chest, right thigh and left ankle). Three main steps describe the activity recognition process: sensors' placement, data pre-processing and data classification. Four supervised classification techniques namely, k-Nearest Neighbor (k-NN), Support Vector Machines (SVM), Gaussian Mixture Models (GMM), and Random Forest (RF) as well as three unsupervised classification techniques namely, k-Means, Gaussian mixture models (GMM) and Hidden Markov Model (HMM), are compared in terms of correct classification rate, F-measure, recall, precision, and specificity. Raw data and extracted features are used separately as inputs of each classifier. The feature selection is performed using a wrapper approach based on the RF algorithm. Based on our experiments, the results obtained show that the k-NN classifier provides the best performance compared to other supervised classification algorithms, whereas the HMM classifier is the one that gives the best results among unsupervised classification algorithms. This comparison highlights which approach gives better performance in both supervised and unsupervised contexts. It should be noted that the obtained results are limited to the context of this study, which concerns the classification of the main daily living human activities using three wearable accelerometers placed at the chest, right shank and left ankle of the subject.

The Classification Ability with Naked Eyes According to the Understanding Level about Rocks of Pre-service Science Teachers

NASA Astrophysics Data System (ADS)

Seong, Cho Kyu; Ho, Chung Duk; Pyo, Hong Deok; Kyeong Jin, Park

2016-04-01

This study aimed to investigate the classification ability with naked eyes according to the understanding level about rocks of pre-service science teachers. We developed a questionnaire concerning misconception about minerals and rocks. The participant were 132 pre-service science teachers. Data were analyzed using Rasch model. Participants were divided into a master group and a novice group according to their understanding level. Seventeen rocks samples (6 igneous, 5 sedimentary, and 6 metamorphic rocks) were presented to pre-service science teachers to examine their classification ability, and they classified the rocks according to the criteria we provided. The study revealed three major findings. First, the pre-service science teachers mainly classified rocks according to textures, color, and grain size. Second, while they relatively easily classified igneous rocks, participants were confused when distinguishing sedimentary and metamorphic rocks from one another by using the same classification criteria. On the other hand, the understanding level of rocks has shown a statistically significant correlation with the classification ability in terms of the formation mechanism of rocks, whereas there was no statically significant relationship found with determination of correct name of rocks. However, this study found that there was a statistically significant relationship between the classification ability with regard the formation mechanism of rocks and the determination of correct name of rocks Keywords : Pre-service science teacher, Understanding level, Rock classification ability, Formation mechanism, Criterion of classification

Physical Human Activity Recognition Using Wearable Sensors

PubMed Central

Attal, Ferhat; Mohammed, Samer; Dedabrishvili, Mariam; Chamroukhi, Faicel; Oukhellou, Latifa; Amirat, Yacine

2015-01-01

This paper presents a review of different classification techniques used to recognize human activities from wearable inertial sensor data. Three inertial sensor units were used in this study and were worn by healthy subjects at key points of upper/lower body limbs (chest, right thigh and left ankle). Three main steps describe the activity recognition process: sensors’ placement, data pre-processing and data classification. Four supervised classification techniques namely, k-Nearest Neighbor (k-NN), Support Vector Machines (SVM), Gaussian Mixture Models (GMM), and Random Forest (RF) as well as three unsupervised classification techniques namely, k-Means, Gaussian mixture models (GMM) and Hidden Markov Model (HMM), are compared in terms of correct classification rate, F-measure, recall, precision, and specificity. Raw data and extracted features are used separately as inputs of each classifier. The feature selection is performed using a wrapper approach based on the RF algorithm. Based on our experiments, the results obtained show that the k-NN classifier provides the best performance compared to other supervised classification algorithms, whereas the HMM classifier is the one that gives the best results among unsupervised classification algorithms. This comparison highlights which approach gives better performance in both supervised and unsupervised contexts. It should be noted that the obtained results are limited to the context of this study, which concerns the classification of the main daily living human activities using three wearable accelerometers placed at the chest, right shank and left ankle of the subject. PMID:26690450

Measuring the Interestingness of Articles in a Limited User Environment Prospectus

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

Pon, Raymond K.

2007-04-18

Search engines, such as Google, assign scores to news articles based on their relevancy to a query. However, not all relevant articles for the query may be interesting to a user. For example, if the article is old or yields little new information, the article would be uninteresting. Relevancy scores do not take into account what makes an article interesting, which would vary from user to user. Although methods such as collaborative filtering have been shown to be effective in recommendation systems, in a limited user environment there are not enough users that would make collaborative filtering effective. I presentmore » a general framework for defining and measuring the ''interestingness'' of articles, called iScore, incorporating user-feedback including tracking multiple topics of interest as well as finding interesting entities or phrases in a complex relationship network. I propose and have shown the validity of the following: 1. Filtering based on only topic relevancy is insufficient for identifying interesting articles. 2. No single feature can characterize the interestingness of an article for a user. It is the combination of multiple features that yields higher quality results. For each user, these features have different degrees of usefulness for predicting interestingness. 3. Through user-feedback, a classifier can combine features to predict interestingness for the user. 4. Current evaluation corpora, such as TREC, do not capture all aspects of personalized news filtering systems necessary for system evaluation. 5. Focusing on only specific evolving user interests instead of all topics allows for more efficient resource utilization while yielding high quality recommendation results. 6. Multiple profile vectors yield significantly better results than traditional methods, such as the Rocchio algorithm, for identifying interesting articles. Additionally, the addition of tracking multiple topics as a new feature in iScore, can improve iScore's classification performance. 7. Multiple topic tracking yields better results than the best results from the last TREC adaptive filtering run. As future work, I will address the following hypothesis: Entities and the relationship among these entities using current information extraction technology can be utilized to identify entities of interest and relationships of interest, using a scheme such as PageRank. And I will address one of the following two hypotheses: 1. By addressing the multiple reading roles that a single user may have, classification results can be improved. 2. By tailoring the operating parameters of MTT, better classification results can be achieved.« less

1961-1968 New Construction Report.

ERIC Educational Resources Information Center

National Association of Physical Plant Administrators of Universities and Colleges, Richmond, IN.

137 NAPPA colleges and universities provided data for this summary. Projects are summarized by thirteen building classifications. Under each classification the following information headings are used--(1) name of institution, (2) project completion date, (3) gross square feet, (4) net assignable area, (5) construction costs, (6) number of stories,…

77 FR 32111 - Privacy Act System of Records

Federal Register 2010, 2011, 2012, 2013, 2014

2012-05-31

... or fraud, or harm to the security or integrity of this system or other systems or programs (whether... to comment. FCC/MB-2 System Name: Broadcast Station Public Inspection Files. Security Classification: The FCC's Security Operations Center (SOC) has not assigned a security classification to this system...

Chronic daily headache: correlation between the 2004 and the 1988 International Headache Society diagnostic criteria.

PubMed

Bigal, Marcelo E; Tepper, Stewart J; Sheftell, Fred D; Rapoport, Alan M; Lipton, Richard B

2004-01-01

In a previous study, we compared the 1988 International Headache Society (IHS) criteria and the Silberstein-Lipton criteria (S-L) in a subspeciality clinic sample of 638 patients with chronic daily headache (CDH) assessed both clinically and with headache diaries. Both systems allowed for the classification of most patients with CDH. The 1988 IHS classification required multiple diagnoses and was more complex to apply. The aim of this study was to revisit the same database, now comparing the prior classification systems with the new 2004 IHS classification. In contrast with the 1st edition, the 2nd edition includes criteria for chronic migraine (CM), new daily persistent headache (NDPH), and hemicrania continua (HC). We reviewed the clinical records and the headache diaries of 638 patients seen between 1980 and 2001 at a headache center. All patients had primary CDH according to the S-L criteria. Using the S-L criteria as a reference, of the 158 patients with transformed migraine (TM) without medication overuse, just 9 (5.6%) met 2004 IHS criteria for CM. Most of the subjects were classified using combinations of migraine and CTTH diagnoses, much like the 1988 IHS classification. Similarly, using the new IHS system, just 41/399 (10.2%) subjects with TM with medication overuse were classified as probable CM with probable medication overuse. Most patients with NDPH without overuse were easily classified using the 2004 criteria (95.8%). Regarding NDPH with medication overuse, the diagnostic groups were much like results for the 1st edition. All patients with chronic tension-type headache (CTTH) and hemicrania continua (HC) according to the S-L system were easily classified using the 2004 IHS criteria. We conclude that the 2004 IHS criteria facilitate the classification of NDPH without medication overuse and HC. For subjects with TM according to the S-L system, the new IHS criteria are complex to use and require multiple diagnoses. Very few patients with TM in the S-L system could be classified with a single diagnosis in the 2004 IHS classification. In fact, CM was so rare that it would be virtually impossible to conduct clinical trials of this entity using the 2004 IHS criteria. Clinical trials of this entity should therefore be conducted using the S-L criteria. Finally, we propose that in the 3rd edition of the IHS classification, the diagnosis of NDPH be revised so as not to exclude migraine features.

Wishart Deep Stacking Network for Fast POLSAR Image Classification.

PubMed

Jiao, Licheng; Liu, Fang

2016-05-11

Inspired by the popular deep learning architecture - Deep Stacking Network (DSN), a specific deep model for polarimetric synthetic aperture radar (POLSAR) image classification is proposed in this paper, which is named as Wishart Deep Stacking Network (W-DSN). First of all, a fast implementation of Wishart distance is achieved by a special linear transformation, which speeds up the classification of POLSAR image and makes it possible to use this polarimetric information in the following Neural Network (NN). Then a single-hidden-layer neural network based on the fast Wishart distance is defined for POLSAR image classification, which is named as Wishart Network (WN) and improves the classification accuracy. Finally, a multi-layer neural network is formed by stacking WNs, which is in fact the proposed deep learning architecture W-DSN for POLSAR image classification and improves the classification accuracy further. In addition, the structure of WN can be expanded in a straightforward way by adding hidden units if necessary, as well as the structure of the W-DSN. As a preliminary exploration on formulating specific deep learning architecture for POLSAR image classification, the proposed methods may establish a simple but clever connection between POLSAR image interpretation and deep learning. The experiment results tested on real POLSAR image show that the fast implementation of Wishart distance is very efficient (a POLSAR image with 768000 pixels can be classified in 0.53s), and both the single-hidden-layer architecture WN and the deep learning architecture W-DSN for POLSAR image classification perform well and work efficiently.

[Addictive behaviours from DSM-IV to DSM-5].

PubMed

van den Brink, W

2014-01-01

The 5th edition of the DSM was published in May, 2013. The new edition incorporates important changes in the classification of addiction. To compare the classification of addictive behaviours presented in DSM-IV with the classification presented in DSM-5 and to comment on the changes introduced into the new version. First of all, the historical developments of the concept of addiction and the classification of addictive behaviours up to DSM-IV are summarised. Then the changes that have been incorporated into DSM-5 are described. The main changes are: (1) DSM-IV substance related disorders and DSM-IV pathological gambling have been combined into one new DSM-5 category, namely 'Substance Related and Addictive Disorders'; (2) DSM-IV abuse and dependence have been combined into one new DSM-5 diagnosis, namely 'Substance Use Disorder'; (2a) the DSM-IV abuse criterion 'recurrent substance-related legal problems' and the DSM-5 criterion 'craving' has been introduced; and (2b) the criteria for (partial) remission have been sharpened. DSM-5 is an improvement on DSM-IV, but for the diagnosis of a psychiatric disorder and the treatment of a psychiatric patient, classification needs to be complemented with staging and profiling.

10 CFR 95.37 - Classification and preparation of documents.

Code of Federal Regulations, 2014 CFR

2014-01-01

... Information must contain the identity of the source document or the classification guide, including the agency.../Exemption) Classifier: (Name/Title/Number) (2) For Restricted Data documents: (i) Identity of the classifier. The identity of the classifier must be shown by completion of the “Derivative Classifier” line. The...

10 CFR 95.37 - Classification and preparation of documents.

Code of Federal Regulations, 2012 CFR

2012-01-01

... Information must contain the identity of the source document or the classification guide, including the agency.../Exemption) Classifier: (Name/Title/Number) (2) For Restricted Data documents: (i) Identity of the classifier. The identity of the classifier must be shown by completion of the “Derivative Classifier” line. The...

10 CFR 95.37 - Classification and preparation of documents.

Code of Federal Regulations, 2013 CFR

2013-01-01

... Information must contain the identity of the source document or the classification guide, including the agency.../Exemption) Classifier: (Name/Title/Number) (2) For Restricted Data documents: (i) Identity of the classifier. The identity of the classifier must be shown by completion of the “Derivative Classifier” line. The...

Hawaii Census 2000 Blocks

EPA Pesticide Factsheets

This data layer represents Census 2000 demographic data derived from the PL94-171 redistricting files and SF3. Census geographic entities include blocks, blockgroups and tracts. Tiger line files are the source of the geometry representing the Census blocks. Attributes include total population counts, racial/ethnic, and poverty/income information. Racial/ethnic classifications are represented in units of blocks, blockgroups and tracts. Poverty and income data are represented in units of blockgroups and tracts. Percentages of each racial/ethnic group have been calculated from the population counts. Total Minority counts and percentages were compiled from each racial/ethnic non-white category. Categories compiled to create the Total Minority count includes the following: African American, Asian, American Indian, Pacific Islander, White Hispanic, Other and all mixed race categories. The percentage poverty attribute represents the percent of the population living at or below poverty level. The per capita income attribute represents the sum of all income within the geographic entity, divided by the total population of that entity. Special fields designed to be used for EJ analysis have been derived from the PL data and include the following: Percentage difference of block, blockgroup and total minority from the state and county averages, percentile rank for each percent total minority within state and county entitie

Hawaii Census 2000 Tracts

EPA Pesticide Factsheets

This data layer represents Census 2000 demographic data derived from the PL94-171 redistricting files and SF3. Census geographic entities include blocks, blockgroups and tracts. Tiger line files are the source of the geometry representing the Census blocks. Attributes include total population counts, racial/ethnic, and poverty/income information. Racial/ethnic classifications are represented in units of blocks, blockgroups and tracts. Poverty and income data are represented in units of blockgroups and tracts. Percentages of each racial/ethnic group have been calculated from the population counts. Total Minority counts and percentages were compiled from each racial/ethnic non-white category. Categories compiled to create the Total Minority count includes the following: African American, Asian, American Indian, Pacific Islander, White Hispanic, Other and all mixed race categories. The percentage poverty attribute represents the percent of the population living at or below poverty level. The per capita income attribute represents the sum of all income within the geographic entity, divided by the total population of that entity. Special fields designed to be used for EJ analysis have been derived from the PL data and include the following: Percentage difference of block, blockgroup and total minority from the state and county averages, percentile rank for each percent total minority within state and county entitie

Hawaii Census 2000 Block Groups

EPA Pesticide Factsheets

This data layer represents Census 2000 demographic data derived from the PL94-171 redistricting files and SF3. Census geographic entities include blocks, blockgroups and tracts. Tiger line files are the source of the geometry representing the Census blocks. Attributes include total population counts, racial/ethnic, and poverty/income information. Racial/ethnic classifications are represented in units of blocks, blockgroups and tracts. Poverty and income data are represented in units of blockgroups and tracts. Percentages of each racial/ethnic group have been calculated from the population counts. Total Minority counts and percentages were compiled from each racial/ethnic non-white category. Categories compiled to create the Total Minority count includes the following: African American, Asian, American Indian, Pacific Islander, White Hispanic, Other and all mixed race categories. The percentage poverty attribute represents the percent of the population living at or below poverty level. The per capita income attribute represents the sum of all income within the geographic entity, divided by the total population of that entity. Special fields designed to be used for EJ analysis have been derived from the PL data and include the following: Percentage difference of block, blockgroup and total minority from the state and county averages, percentile rank for each percent total minority within state and county entitie

Optimized extreme learning machine for urban land cover classification using hyperspectral imagery

NASA Astrophysics Data System (ADS)

Su, Hongjun; Tian, Shufang; Cai, Yue; Sheng, Yehua; Chen, Chen; Najafian, Maryam

2017-12-01

This work presents a new urban land cover classification framework using the firefly algorithm (FA) optimized extreme learning machine (ELM). FA is adopted to optimize the regularization coefficient C and Gaussian kernel σ for kernel ELM. Additionally, effectiveness of spectral features derived from an FA-based band selection algorithm is studied for the proposed classification task. Three sets of hyperspectral databases were recorded using different sensors, namely HYDICE, HyMap, and AVIRIS. Our study shows that the proposed method outperforms traditional classification algorithms such as SVM and reduces computational cost significantly.

Amelogenesis imperfecta and anterior open bite: Etiological, classification, clinical and management interrelationships

PubMed Central

Alachioti, Xanthippi Sofia; Dimopoulou, Eleni; Vlasakidou, Anatoli; Athanasiou, Athanasios E

2014-01-01

Although amelogenesis imperfecta is not a common dental pathological condition, its etiological, classification, clinical and management aspects have been addressed extensively in the scientific literature. Of special clinical consideration is the frequent co-existence of amelogenesis imperfecta with the anterior open bite. This paper provides an updated review on amelogenesis imperfecta as well as anterior open bite, in general, and documents the association of these two separate entities, in particular. Diagnosis and treatment of amelogenesis imperfecta patients presenting also with anterior open bite require a lengthy, comprehensive and multidisciplinary approach, which should aim to successfully address all dental, occlusal, developmental, skeletal and soft tissue problems associated with these two serious clinical conditions. PMID:24987656

Amelogenesis imperfecta and anterior open bite: Etiological, classification, clinical and management interrelationships.

PubMed

Alachioti, Xanthippi Sofia; Dimopoulou, Eleni; Vlasakidou, Anatoli; Athanasiou, Athanasios E

2014-01-01

Although amelogenesis imperfecta is not a common dental pathological condition, its etiological, classification, clinical and management aspects have been addressed extensively in the scientific literature. Of special clinical consideration is the frequent co-existence of amelogenesis imperfecta with the anterior open bite. This paper provides an updated review on amelogenesis imperfecta as well as anterior open bite, in general, and documents the association of these two separate entities, in particular. Diagnosis and treatment of amelogenesis imperfecta patients presenting also with anterior open bite require a lengthy, comprehensive and multidisciplinary approach, which should aim to successfully address all dental, occlusal, developmental, skeletal and soft tissue problems associated with these two serious clinical conditions.

Rule-guided human classification of Volunteered Geographic Information

NASA Astrophysics Data System (ADS)

Ali, Ahmed Loai; Falomir, Zoe; Schmid, Falko; Freksa, Christian

2017-05-01

During the last decade, web technologies and location sensing devices have evolved generating a form of crowdsourcing known as Volunteered Geographic Information (VGI). VGI acted as a platform of spatial data collection, in particular, when a group of public participants are involved in collaborative mapping activities: they work together to collect, share, and use information about geographic features. VGI exploits participants' local knowledge to produce rich data sources. However, the resulting data inherits problematic data classification. In VGI projects, the challenges of data classification are due to the following: (i) data is likely prone to subjective classification, (ii) remote contributions and flexible contribution mechanisms in most projects, and (iii) the uncertainty of spatial data and non-strict definitions of geographic features. These factors lead to various forms of problematic classification: inconsistent, incomplete, and imprecise data classification. This research addresses classification appropriateness. Whether the classification of an entity is appropriate or inappropriate is related to quantitative and/or qualitative observations. Small differences between observations may be not recognizable particularly for non-expert participants. Hence, in this paper, the problem is tackled by developing a rule-guided classification approach. This approach exploits data mining techniques of Association Classification (AC) to extract descriptive (qualitative) rules of specific geographic features. The rules are extracted based on the investigation of qualitative topological relations between target features and their context. Afterwards, the extracted rules are used to develop a recommendation system able to guide participants to the most appropriate classification. The approach proposes two scenarios to guide participants towards enhancing the quality of data classification. An empirical study is conducted to investigate the classification of grass-related features like forest, garden, park, and meadow. The findings of this study indicate the feasibility of the proposed approach.

Epicuticular chemistry reinforces the new taxonomic classification of the Bactrocera dorsalis species complex (Diptera: Tephritidae, Dacinae).

PubMed

Vaníčková, Lucie; Nagy, Radka; Pompeiano, Antonio; Kalinová, Blanka

2017-01-01

Bactrocera invadens Drew, Tsuruta & White, Bactrocera papayae Drew & Hancock, and Bactrocera philippinensis Drew & Hancock, key pest species within the Bactrocera dorsalis species complex, have been recently synonymized under the name Bactrocera dorsalis (Hendel). The closely related Bactrocera carambolae Drew & Hancock remains as a discrete taxonomic entity. Although the synonymizations have been accepted by most researchers, debate about the species limits remains. Because of the economic importance of this group of taxa, any new information available to support or deny the synonymizations is valuable. We investigated the chemical epicuticle composition of males and females of B. dorsalis, B. invadens, B. papayae, B. philippinensis, and B. carambolae by means of one- and two-dimensional gas chromatography-mass spectrometry, followed by multiple factor analyses and principal component analysis. Clear segregation of complex cuticule profiles of both B. carambolae sexes from B. dorsalis (Hendel) was observed. In addition to cuticular hydrocarbons, abundant complex mixtures of sex-specific oxygenated lipids (three fatty acids and 22 fatty acid esters) with so far unknown function were identified in epicuticle extracts from females of all species. The data obtained supports both taxonomic synonymization of B. invadens, B. papayae, and B. philippinensis with B. dorsalis, as well as the exclusion of B. carambolae from B. dorsalis.

Epicuticular chemistry reinforces the new taxonomic classification of the Bactrocera dorsalis species complex (Diptera: Tephritidae, Dacinae)

PubMed Central

Vaníčková, Lucie; Nagy, Radka; Pompeiano, Antonio

2017-01-01

Bactrocera invadens Drew, Tsuruta & White, Bactrocera papayae Drew & Hancock, and Bactrocera philippinensis Drew & Hancock, key pest species within the Bactrocera dorsalis species complex, have been recently synonymized under the name Bactrocera dorsalis (Hendel). The closely related Bactrocera carambolae Drew & Hancock remains as a discrete taxonomic entity. Although the synonymizations have been accepted by most researchers, debate about the species limits remains. Because of the economic importance of this group of taxa, any new information available to support or deny the synonymizations is valuable. We investigated the chemical epicuticle composition of males and females of B. dorsalis, B. invadens, B. papayae, B. philippinensis, and B. carambolae by means of one- and two-dimensional gas chromatography–mass spectrometry, followed by multiple factor analyses and principal component analysis. Clear segregation of complex cuticule profiles of both B. carambolae sexes from B. dorsalis (Hendel) was observed. In addition to cuticular hydrocarbons, abundant complex mixtures of sex-specific oxygenated lipids (three fatty acids and 22 fatty acid esters) with so far unknown function were identified in epicuticle extracts from females of all species. The data obtained supports both taxonomic synonymization of B. invadens, B. papayae, and B. philippinensis with B. dorsalis, as well as the exclusion of B. carambolae from B. dorsalis. PMID:28873446

Serous endometrial intraepithelial carcinoma: a case series and literature review.

PubMed

Pathiraja, P; Dhar, S; Haldar, K

2013-01-01

Minimal uterine serous cancer (MUSC) or serous endometrial intraepithelial carcinoma (EIC) has been described by many different names since 1998. There have been very few cases reported in literature since EIC/MUSC was recognized as a separate entity. The World health Organization (WHO) Classification favors the term serous EIC. Although serous EIC is confined to the uterine endometrium at initial histology diagnosis, a significant number of patients could have distal metastasis at diagnosis, without symptoms. Serous EIC is considered as being the precursor of uterine serous cancer (USC), but pure serous EIC also has an aggressive behavior similar to USC. It is therefore prudent to have an accurate diagnosis and appropriate surgical staging. There are very few published articles in literature that discuss the pure form of serous EIC. The aim of this series is to share our experience and review evidence for optimum management of serous EIC. We report a series of five women treated in our institute in the last 3 years. We reviewed the relevant literature on serous EIC and various management strategies, to recommend best clinical practice. Pure serous EIC is a difficult histopathological diagnosis, which requires ancillary immunohistochemical staining. It can have an aggressive clinical behavior with early recurrence and poor survival. Optimum surgical staging, with appropriate adjuvant treatment, should be discussed when treating these patients.

ICD-11 complex PTSD among Israeli male perpetrators of intimate partner violence: Construct validity and risk factors.

PubMed

Gilbar, Ohad; Hyland, Philip; Cloitre, Marylene; Dekel, Rachel

2018-03-01

The International Classification of Diseases 11th Version (ICD-11) will include Complex Posttraumatic Stress Disorder (CPTSD) as a unique diagnostic entity comprising core PTSD and DSO (disturbances in self-organization) symptoms. The current study had three aims: (1) assessing the validity of CPTSD in a unique population of male perpetrators of intimate partner violence; (2) examining whether exposure to different types of traumatic events would be associated with the two proposed CPTSD factors, namely PTSD or DSO; and (3) assessing the differential association of various sociodemographic and symptom characteristics with each factor. Participants were 234 males drawn randomly from a sample of 2600 men receiving treatment at 66 domestic violence centers in Israel. Data were collected using the International Trauma Questionnaire (ITQ) - Hebrew version. Confirmatory factor analysis supported the factorial validity of ICD-11 CPTSD. Cumulative lifetime trauma and physical childhood neglect were associated with PTSD and DSO, while cumulative childhood violence exposure was associated only with DSO. Anxiety was associated only with DSO; depression more strongly with DSO than PTSD. Religious level contributed only to PTSD; compulsory military service only to DSO. The study supports the distinction between PTSD and DSO in the CPTSD construct and introduces the role of cultural variables. Copyright © 2018 Elsevier Ltd. All rights reserved.

FAP Associated Papillary Thyroid Carcinoma: A Peculiar Subtype of Familial Nonmedullary Thyroid Cancer.

PubMed

Cetta, Francesco

2015-01-01

Familial Nonmedullary Thyroid Carcinoma (FNMTC) makes up to 5-10% of all thyroid cancers, also including those FNMTC occurring as a minor component of familial cancer syndromes, such as Familial Adenomatous Polyposis (FAP). We give evidence that this extracolonic manifestation of FAP is determined by the same germline mutation of the APC gene responsible for colonic polyps and cancer but also shows some unusual features (F : M ratio = 80 : 1, absence of LOH for APC in the thyroid tumoral tissue, and indolent biological behaviour, despite frequent multicentricity and lymph nodal involvement), suggesting that the APC gene confers only a generic susceptibility to thyroid cancer, but perhaps other factors, namely, modifier genes, sex-related factors, or environmental factors, are also required for its phenotypic expression. This great variability is against the possibility of classifying all FNMTC as a single entity, not only with a unique or prevalent causative genetic factor, but also with a unique or common biological behavior and a commonly dismal prognosis. A new paradigm is also suggested that could be useful (1) for a proper classification of FAP associated PTC within the larger group of FNMTC and (2) for making inferences to sporadic carcinogenesis, based on the lesson from FAP.

Using Ontology Fingerprints to disambiguate gene name entities in the biomedical literature.

PubMed

Chen, Guocai; Zhao, Jieyi; Cohen, Trevor; Tao, Cui; Sun, Jingchun; Xu, Hua; Bernstam, Elmer V; Lawson, Andrew; Zeng, Jia; Johnson, Amber M; Holla, Vijaykumar; Bailey, Ann M; Lara-Guerra, Humberto; Litzenburger, Beate; Meric-Bernstam, Funda; Jim Zheng, W

2015-01-01

Ambiguous gene names in the biomedical literature are a barrier to accurate information extraction. To overcome this hurdle, we generated Ontology Fingerprints for selected genes that are relevant for personalized cancer therapy. These Ontology Fingerprints were used to evaluate the association between genes and biomedical literature to disambiguate gene names. We obtained 93.6% precision for the test gene set and 80.4% for the area under a receiver-operating characteristics curve for gene and article association. The core algorithm was implemented using a graphics processing unit-based MapReduce framework to handle big data and to improve performance. We conclude that Ontology Fingerprints can help disambiguate gene names mentioned in text and analyse the association between genes and articles. Database URL: http://www.ontologyfingerprint.org © The Author(s) 2015. Published by Oxford University Press.

Designing a training tool for imaging mental models

NASA Technical Reports Server (NTRS)

Dede, Christopher J.; Jayaram, Geetha

1990-01-01

The training process can be conceptualized as the student acquiring an evolutionary sequence of classification-problem solving mental models. For example a physician learns (1) classification systems for patient symptoms, diagnostic procedures, diseases, and therapeutic interventions and (2) interrelationships among these classifications (e.g., how to use diagnostic procedures to collect data about a patient's symptoms in order to identify the disease so that therapeutic measures can be taken. This project developed functional specifications for a computer-based tool, Mental Link, that allows the evaluative imaging of such mental models. The fundamental design approach underlying this representational medium is traversal of virtual cognition space. Typically intangible cognitive entities and links among them are visible as a three-dimensional web that represents a knowledge structure. The tool has a high degree of flexibility and customizability to allow extension to other types of uses, such a front-end to an intelligent tutoring system, knowledge base, hypermedia system, or semantic network.

Review of in situ and invasive penile squamous cell carcinoma and associated non-neoplastic dermatological conditions.

PubMed

Downes, Michelle R

2015-05-01

Penile carcinoma is a rare genitourinary malignancy in North America and Europe with highest rates recorded in South America, Africa and Asia. Recent classifications have refined the terminology used in classifying intraepithelial/in situ lesions and additionally newer entities have been recognised in the invasive category. While increasing recognition of a bimodal pathway of penile carcinogenesis has facilitated understanding and classification of these tumours, handling and subtyping of penile malignancies presents a challenge to the reporting pathologist, in part due to their rarity. This article reviews the terminology and classification of in situ and invasive carcinomas and their relationship to human papilloma virus status. In addition, associated non-neoplastic dermatological conditions of relevance and appropriate ancillary investigations will be addressed. 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.

Emerging Issues in Virus Taxonomy

PubMed Central

Mahy, Brian W.J.

2004-01-01

Viruses occupy a unique position in biology. Although they possess some of the properties of living systems such as having a genome, they are actually nonliving infectious entities and should not be considered microorganisms. A clear distinction should be drawn between the terms virus, virion, and virus species. Species is the most fundamental taxonomic category used in all biological classification. In 1991, the International Committee on Taxonomy of Viruses (ICTV) decided that the category of virus species should be used in virus classification together with the categories of genus and family. More than 50 ICTV study groups were given the task of demarcating the 1,550 viral species that were recognized in the 7th ICTV report, which was published in 2000. We briefly describe the changes in virus classification that were introduced in that report. We also discuss recent proposals to introduce a nonlatinized binomial nomenclature for virus species. PMID:15078590

Locating and parsing bibliographic references in HTML medical articles

PubMed Central

Zou, Jie; Le, Daniel; Thoma, George R.

2010-01-01

The set of references that typically appear toward the end of journal articles is sometimes, though not always, a field in bibliographic (citation) databases. But even if references do not constitute such a field, they can be useful as a preprocessing step in the automated extraction of other bibliographic data from articles, as well as in computer-assisted indexing of articles. Automation in data extraction and indexing to minimize human labor is key to the affordable creation and maintenance of large bibliographic databases. Extracting the components of references, such as author names, article title, journal name, publication date and other entities, is therefore a valuable and sometimes necessary task. This paper describes a two-step process using statistical machine learning algorithms, to first locate the references in HTML medical articles and then to parse them. Reference locating identifies the reference section in an article and then decomposes it into individual references. We formulate this step as a two-class classification problem based on text and geometric features. An evaluation conducted on 500 articles drawn from 100 medical journals achieves near-perfect precision and recall rates for locating references. Reference parsing identifies the components of each reference. For this second step, we implement and compare two algorithms. One relies on sequence statistics and trains a Conditional Random Field. The other focuses on local feature statistics and trains a Support Vector Machine to classify each individual word, followed by a search algorithm that systematically corrects low confidence labels if the label sequence violates a set of predefined rules. The overall performance of these two reference-parsing algorithms is about the same: above 99% accuracy at the word level, and over 97% accuracy at the chunk level. PMID:20640222

Locating and parsing bibliographic references in HTML medical articles.

PubMed

Zou, Jie; Le, Daniel; Thoma, George R

2010-06-01

The set of references that typically appear toward the end of journal articles is sometimes, though not always, a field in bibliographic (citation) databases. But even if references do not constitute such a field, they can be useful as a preprocessing step in the automated extraction of other bibliographic data from articles, as well as in computer-assisted indexing of articles. Automation in data extraction and indexing to minimize human labor is key to the affordable creation and maintenance of large bibliographic databases. Extracting the components of references, such as author names, article title, journal name, publication date and other entities, is therefore a valuable and sometimes necessary task. This paper describes a two-step process using statistical machine learning algorithms, to first locate the references in HTML medical articles and then to parse them. Reference locating identifies the reference section in an article and then decomposes it into individual references. We formulate this step as a two-class classification problem based on text and geometric features. An evaluation conducted on 500 articles drawn from 100 medical journals achieves near-perfect precision and recall rates for locating references. Reference parsing identifies the components of each reference. For this second step, we implement and compare two algorithms. One relies on sequence statistics and trains a Conditional Random Field. The other focuses on local feature statistics and trains a Support Vector Machine to classify each individual word, followed by a search algorithm that systematically corrects low confidence labels if the label sequence violates a set of predefined rules. The overall performance of these two reference-parsing algorithms is about the same: above 99% accuracy at the word level, and over 97% accuracy at the chunk level.

The College Readiness Data Catalog Tool: User Guide. REL 2014-042

ERIC Educational Resources Information Center

Rodriguez, Sheila M.; Estacion, Angela

2014-01-01

As the name indicates, the College Readiness Data Catalog Tool focuses on identifying data that can indicate a student's college readiness. While college readiness indicators may also signal career readiness, many states, districts, and other entities, including the U.S. Virgin Islands (USVI), do not systematically collect career readiness…