PubMed · 2007 · 107 citations · 7 references
ComputingBiomedical InformaticsHealth InformaticsBiomedical Text MiningClinical InformaticsNatural Language ProcessingAnnotationClinical Data InterpretationClinical DocumentationClinical Natural Language ProcessingInformation ExtractionNamed Entity RecognitionAnnotator AgreementClinical Named Entity RecognitionClinical Relation ExtractionClinical Text AnnotationCorpus CreationInformation Extraction From Biomedical TextInter-annotator AgreementManual Annotation Curation
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.
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GENIA corpus—a semantically annotated corpus for bio-textmining
JD Kim, Tomoko Ohta, Yuka Tateisi et al. · Bioinformatics · 2003 · 1.2K citations
Philip V. Ogren · 2006 · 161 citations · Full text
Building and evaluating annotated corpora for medical NLP systems.
Philip V. Ogren, Guergana Savova, James D. Buntrock et al. · PubMed · 2006 · 19 citations · Full text
Language Studies, Biomedical Informatics, Computer Science +17