Aggregating UMLS semantic types for reducing conceptual complexity.
about
Anne O'Tate: A tool to support user-driven summarization, drill-down and browsing of PubMed search resultsCollaborative development of the Arrowsmith two node search interface designed for laboratory investigatorsSocial tagging in the life sciences: characterizing a new metadata resource for bioinformaticsA review of auditing methods applied to the content of controlled biomedical terminologiesApproaches to eliminating cycles in the UMLS Metathesaurus: naïve vs. formalImpact of Predicting Health Care Utilization Via Web Search Behavior: A Data-Driven AnalysisBio-SCoRes: A Smorgasbord Architecture for Coreference Resolution in Biomedical TextDevelopment of an informatics infrastructure for data exchange of biomolecular simulations: Architecture, data models and ontologyIntegrating Multiple On-line Knowledge Bases for Disease-Lab Test Relation ExtractionKnowLife: a versatile approach for constructing a large knowledge graph for biomedical sciencesChallenges and practical approaches with word sense disambiguation of acronyms and abbreviations in the clinical domainClustering cliques for graph-based summarization of the biomedical research literatureA hybrid knowledge-based and data-driven approach to identifying semantically similar conceptsUnderstanding PubMed user search behavior through log analysisExtraction of chemical-induced diseases using prior knowledge and textual informationSocial media engagement analysis of U.S. Federal health agencies on FacebookUsing contextual and lexical features to restructure and validate the classification of biomedical conceptsMethodology for creating UMLS content views appropriate for biomedical natural language processingAn object-oriented model for representing semantic locality in the UMLS.Methods for exploring the semantics of the relationships between co-occurring UMLS concepts.Strength in numbers: exploring redundancy in hierarchical relations across biomedical terminologies.Interpreting hypernymic propositions in an online medical encyclopediaExploring semantic groups through visual approaches.Finding UMLS Metathesaurus concepts in MEDLINE.Integrating a hypernymic proposition interpreter into a semantic processor for biomedical texts.Automatically identifying health outcome information in MEDLINE records.Semantic classification of biomedical concepts using distributional similarity.Knowledge-based methods to help clinicians find answers in MEDLINE.Identifying risk factors for metabolic syndrome in biomedical text.The first step toward data reuse: disambiguating concept representation of the locally developed ICU nursing flowsheets.UMLS content views appropriate for NLP processing of the biomedical literature vs. clinical text.Two approaches to integrating phenotype and clinical information.The UMLS-CORE project: a study of the problem list terminologies used in large healthcare institutions.Detecting clinically relevant new information in clinical notes across specialties and settings.Auditing associative relations across two knowledge sources.Easing semantically enriched information retrieval-An interactive semi-automatic annotation system for medical documents.Semantic mappings and locality of nursing diagnostic concepts in UMLSQuality evaluation of value sets from cancer study common data elements using the UMLS semantic groups.Profiling risk factors for chronic uveitis in juvenile idiopathic arthritis: a new model for EHR-based research.Source authenticity in the UMLS--a case study of the Minimal Standard Terminology
P2860
Q21093182-0492A6A2-58A3-493C-B8E3-B4860CC5B338Q21203541-CD58B8F4-3E48-422D-B039-7D319868D25FQ21284373-8411354B-6DE3-45D9-9138-57DEBCC53C5AQ24607323-71B0CDE0-AAA4-40AB-AFCC-ACF4F8176176Q24675840-A83D240C-1063-4E7C-8D1B-41106FDE9998Q27928068-EDD32DD4-3E52-4E07-A15D-C2696F109A4CQ28550481-D7F5AF52-0048-45C1-B9F1-86B8F9333A8BQ28606604-D2850BED-0206-43AC-8175-17A608E2BAABQ28645604-36C44F8D-CEF9-4598-AE2F-DCF99A3FD7A1Q28646868-2EE3A2C8-61C1-4340-ABA7-81FA0C848100Q28649857-7F6EE302-2969-46B8-B9DB-D40993E4A27EQ28681399-83B250EF-7A16-46D6-957B-7090615A826CQ28730096-F1566CFF-3B51-4816-A221-8CE54B713B70Q28749483-1DC078DB-0CBF-4B58-B0A2-670FF58FF149Q28834680-A29EEF23-9E7D-4957-9695-B69D1E1AC47AQ29570803-6C495E82-1C93-4FBC-9620-4E938CA6082AQ30480209-709B666D-2E1A-4A8D-81B1-AFE3442B03E4Q30854082-F6A54DF7-1741-4A09-8FB4-46DB246B10E1Q31017416-1F9F0229-C441-47CA-9A8A-9EE5C273B2CBQ31017427-5F1EF42B-F4C9-4AF6-A7FF-7F56E44D376AQ31036274-A4C732FE-8C1A-448B-BD1F-269284227D36Q31036356-0CF50591-E90B-4282-BCBD-4210178FC007Q31040274-5DBB1D45-8FCC-4297-B716-7FE2563857EBQ31120213-00908D5B-1FE3-499B-A7FA-ACAD247CD524Q33196873-7EF428E1-96FF-4B77-AC46-8E74C36EF0B1Q33225083-408A1AA4-2BA9-4AEF-954E-665224065D95Q33282824-1D47F73B-DE54-4DC3-B1C5-093D1C187FD5Q33294807-4A6FC866-8270-4963-ACEE-008471170DFBQ33359171-18B1267B-2CDA-461B-8B6E-F7DD7617EAC8Q33366355-88DC13EA-8169-4795-BA52-6093BBD25700Q33530991-8687D9DC-33AE-4660-8461-B7EABAD96C38Q33626681-F02A3A2B-B8BF-4D20-9D57-9E4C1AB9E289Q33723768-1B8DBDDF-C202-4271-8B76-5BDD8CB64CF8Q33896284-A9A93B0E-4842-448B-9DE6-BDEDA430AE0FQ33940045-3B80E725-76C1-4E71-80F4-C59186BDC995Q33941740-A66669E4-BAA0-4683-A0C3-39B4DE318C55Q34032748-C637416B-AD09-4824-B36D-CEDCF6D27C35Q34236286-C5D089C5-B197-450E-9B39-B50DF06943FDQ34248642-5CE3089A-3198-4375-BB4B-5E3795F5EF58Q34348940-E27F60C9-15B9-4DDF-8043-165E61227E7B
P2860
Aggregating UMLS semantic types for reducing conceptual complexity.
description
2001 nî lūn-bûn
@nan
2001 թուականի Յունուարին հրատարակուած գիտական յօդուած
@hyw
2001 թվականի հունվարին հրատարակված գիտական հոդված
@hy
2001年の論文
@ja
2001年論文
@yue
2001年論文
@zh-hant
2001年論文
@zh-hk
2001年論文
@zh-mo
2001年論文
@zh-tw
2001年论文
@wuu
name
Aggregating UMLS semantic types for reducing conceptual complexity.
@ast
Aggregating UMLS semantic types for reducing conceptual complexity.
@en
type
label
Aggregating UMLS semantic types for reducing conceptual complexity.
@ast
Aggregating UMLS semantic types for reducing conceptual complexity.
@en
prefLabel
Aggregating UMLS semantic types for reducing conceptual complexity.
@ast
Aggregating UMLS semantic types for reducing conceptual complexity.
@en
P2860
P1476
Aggregating UMLS semantic types for reducing conceptual complexity
@en
P2093
A T McCray
O Bodenreider
P2860
P304
P50
P577
2001-01-01T00:00:00Z