Development of Finding-comprehensive Annotation Guideline for Practical Clinical Text Processing

DOI
  • Shinohara E
    Department of Artificial Intelligence in Healthcare, Graduate School of Medicine, the University of Tokyo
  • Kawazoe Y
    Department of Artificial Intelligence in Healthcare, Graduate School of Medicine, the University of Tokyo
  • Shibata D
    Department of Artificial Intelligence in Healthcare, Graduate School of Medicine, the University of Tokyo
  • Shimamoto K
    Department of Artificial Intelligence in Healthcare, Graduate School of Medicine, the University of Tokyo
  • Seki T
    Department of Planning, Information and Management, the University of Tokyo Hospital

Bibliographic Information

Other Title
  • 症例報告に対する網羅的な所見アノテーションのためのアノテーション基準の構築

Abstract

<p>　Clinical narratives contain important information such as symptoms and findings, and there is a need for technology to automatically extract this information. The development of practical technology requires a corpus with annotations that cover all the described information, while such a corpus does not exist at present. We have developed and published a corpus of case reports with comprehensive annotations on patient conditions. In this paper, we report on the establishment of the annotation criteria. As a result of repeatedly annotating case reports and modifying the annotation criteria, we obtained annotation criteria consisting of 50 entity types, 14 attributes, and 36 relations, which not only allow us to express more detailed information than previous studies, but also allow us to capture temporal changes in factuality that could not be expressed before.</p>

Journal

Keywords

Details 詳細情報について

  • CRID
    1390015564796448768
  • DOI
    10.14948/jami.42.3
  • ISSN
    21888469
    02898055
  • Text Lang
    ja
  • Data Source
    • JaLC
  • Abstract License Flag
    Disallowed

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