ComputingBiomedical InformaticsHealth InformaticsClinical Data ManagementClinical InformaticsHealth Data StandardsAnnotationClinical DocumentationClinical Natural Language ProcessingCorpus AnnotationKnowledge AnnotationAssertion GenerationClinical Text AnnotationConcept AnnotationData AnnotationQualitative InterviewingReference Standard ConstructionRelation ClassificationSemi-structured Interviews
The Department of Veterans Affairs (VA) and the Informatics for Integrating Biology and the Bedside (i2b2) team partnered to generate the reference standard for the 2010 i2b2/VA challenge task on concept extraction, assertion classification, and relation classification. The purpose of this paper is to report an in-depth qualitative analysis of the experience and perceptions of human annotators for these tasks. Transcripts of semi-structured interviews were analyzed using qualitative methods to identify key constructs and themes related to these annotation tasks. Interventions were embedded with these tasks using pre-annotation of clinical concepts and a modified annotation workflow. From the human perspective, annotation tasks involve an inherent conflict between bias, accuracy, and efficiency. This analysis deepens understanding of the biases, complexities and impact of variations in the annotation process that may affect annotation task reliability and reference standard validity that are generalizable for other similar large-scale clinical corpus annotation projects.
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Message Understanding Conference-6
Ralph Grishman, Beth Sundheim · 1996 · 1.4K citations · Full text
Overview of BioCreAtIvE: critical assessment of information extraction for biology
Lynette Hirschman, Alexander Yeh, Christian Blaschke et al. · BMC Bioinformatics · 2005 · 542 citations · Full text
Medicine, Bioinformatics, Biology +15