skip to main content
Visitante
Meu Espaço
Minha Conta
Sair
Identificação
This feature requires javascript
Tags
Revistas Eletrônicas (eJournals)
Livros Eletrônicos (eBooks)
Bases de Dados
Bibliotecas USP
Ajuda
Ajuda
Idioma:
Inglês
Espanhol
Português
This feature required javascript
This feature requires javascript
Primo Search
Busca Geral
Busca Geral
Acervo Físico
Acervo Físico
Produção Intelectual da USP
Produção USP
Search For:
Clear Search Box
Search in:
Busca Geral
Or hit Enter to replace search target
Or select another collection:
Search in:
Busca Geral
Busca Avançada
Busca por Índices
This feature requires javascript
This feature requires javascript
UMLS::Association - Measuring the Association Between Biomedical Terms
Herbert, Keith B
VCU Scholars Compass 2016
Texto completo disponível
Citações
Citado por
Exibir Online
Detalhes
Resenhas & Tags
Mais Opções
Nº de Citações
This feature requires javascript
Enviar para
Adicionar ao Meu Espaço
Remover do Meu Espaço
E-mail (máximo 30 registros por vez)
Imprimir
Link permanente
Referência
EasyBib
EndNote
RefWorks
del.icio.us
Exportar RIS
Exportar BibTeX
This feature requires javascript
Título:
UMLS::Association - Measuring the Association Between Biomedical Terms
Autor:
Herbert, Keith B
Assuntos:
Computer Science
;
Health Information Technology
;
Medical Informatics
;
MetaMap
;
Natural Language Processing
;
Other Computer Sciences
;
Perl
;
UMLS
Notas:
Undergraduate Research Posters
https://scholarscompass.vcu.edu/context/uresposters/article/1197/viewcontent/herbertkb_poster.pdf
https://scholarscompass.vcu.edu/uresposters/188
Descrição:
UMLS::Association - A Semantic Association Framework for Biomedical Texts Keith Herbert Natural Language Processing Lab, Department of Computer Science Introduction We present UMLS::Association, a software package to explore the semantic association of biomedical terms with applications for literature-based discovery. Literature-based discovery is an endeavour to ”connect the dots” for scientists between the topics of their research and those of unexpected relevance. However, many approaches rely on the exact wording for the ideas in the research papers being analyzed. The Unified Medical Language System (UMLS) provides a way to map natural language phrases in these papers to sequences of abstract yet very specific concepts. These concepts are referred to as Concept Unique Identifiers (CUIs). We can identify which concepts are strongly associated by measuring how often they occur together within a corpus of biomedical texts and applying statistical techniques. Methods We measure the semantic association of CUIs with bigrams: pairs of CUIs that follow each other in some string of symbols. Research articles and clinical studies were first preprocessed by a UMLS tool that generates sequences of CUIs for every phrase within each sentence of the papers. Our framework then extracts bigrams from the CUI sequences to build a database from which we can calculate meaningful statistics for the association of two CUIs. We developed a utility to quickly return a variety of statistical association measures for any two concepts as well as an application programming interface to allow these association measures to be incorporated into new software packages. Results We evaluated UMLS::Association’s predictive performance for semantic association by running it on four datasets which had been tagged by human judges for semantic similarity and relatedness. The results show our semantic association measures to match human judgements on the association between concepts as well or better than current state-of-the art semantic similarity and relatedness measures. Conclusion UMLS::Association provides an easy to use framework for the semantic association of concepts within biomedical literature. Work is in progress to extend the reach of the bigram model with a directed graph representation of the many unique CUI sequences generated for each phrase in a sentence. A user friendly web application interface to our framework is also under development. Besides access to existing functions, it will also feature a directed graph visualization for the search results for concepts strongly associated with some query concept. This will allow any researcher to explore the semantic associations between concepts in a simple and intuitive way. https://scholarscompass.vcu.edu/uresposters/1197/thumbnail.jpg
Editor:
VCU Scholars Compass
Data de criação/publicação:
2016
Idioma:
Inglês
Links
View record in Virginia Commonwealth University$$FView record in $$GVirginia Commonwealth University
This feature requires javascript
This feature requires javascript
Voltar para lista de resultados
This feature requires javascript
This feature requires javascript
Buscando em bases de dados remotas. Favor aguardar.
Buscando por
em
scope:(USP_VIDEOS),scope:("PRIMO"),scope:(USP_FISICO),scope:(USP_EREVISTAS),scope:(USP),scope:(USP_EBOOKS),scope:(USP_PRODUCAO),primo_central_multiple_fe
Mostrar o que foi encontrado até o momento
This feature requires javascript
This feature requires javascript