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The CLEF corpus: semantic annotation of clinical text.
Roberts, Angus; Gaizauskas, Robert; Hepple, Mark; Davis, Neil; Demetriou, George; Guo, Yikun; Kola, Jay; Roberts, Ian; Setzer, Andrea; Tapuria, Archana; Wheeldin, Bill.
Afiliação
  • Roberts A; Natural Language Processing Group, University of Sheffield, UK.
AMIA Annu Symp Proc ; : 625-9, 2007 Oct 11.
Article em En | MEDLINE | ID: mdl-18693911
ABSTRACT
The Clinical E-Science Framework (CLEF) project is building a framework for the capture, integration and presentation of clinical information for clinical research, evidence-based health care and genotype-meets-phenotype informatics. A significant portion of the information required by such a framework originates as text, even in EHR-savvy organizations. CLEF uses Information Extraction (IE) to make this unstructured information available. An important part of IE is the identification of semantic entities and relationships. Typical approaches require human annotated documents to provide both evaluation standards and material for system development. CLEF has a corpus of clinical narratives, histopathology reports and imaging reports from 20 thousand patients. We describe the selection of a subset of this corpus for manual annotation of clinical entities and relationships. We describe an annotation methodology and report encouraging initial results of inter-annotator agreement. Comparisons are made between different text sub-genres, and between annotators with different skills.
Assuntos

Texto completo: 1 Bases de dados: MEDLINE Assunto principal: Processamento de Linguagem Natural / Armazenamento e Recuperação da Informação / Sistemas Computadorizados de Registros Médicos Tipo de estudo: Guideline / Prognostic_studies Limite: Humans Idioma: En Revista: AMIA Annu Symp Proc Assunto da revista: INFORMATICA MEDICA Ano de publicação: 2007 Tipo de documento: Article País de afiliação: Reino Unido

Texto completo: 1 Bases de dados: MEDLINE Assunto principal: Processamento de Linguagem Natural / Armazenamento e Recuperação da Informação / Sistemas Computadorizados de Registros Médicos Tipo de estudo: Guideline / Prognostic_studies Limite: Humans Idioma: En Revista: AMIA Annu Symp Proc Assunto da revista: INFORMATICA MEDICA Ano de publicação: 2007 Tipo de documento: Article País de afiliação: Reino Unido