Building an Ontology for Radiological Diagnoses using Syntactic Analysis and Medical Attributes

DOI 3 Citations 17 References
  • Imai T
    Dept. of Planning, Information and Management, The University of Tokyo Hospital
  • Aramaki E
    Dept. of Planning, Information and Management, The University of Tokyo Hospital
  • Kajino M
    Japan Research Group for Medical Ontology
  • Miyo K
    Dept. of Planning, Information and Management, The University of Tokyo Hospital
  • Ohe K
    Dept. of Planning, Information and Management, The University of Tokyo Hospital

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  • 構文情報と医学用語属性を用いた画像診断所見オントロジーの構築の試み

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Abstract

[Objectives]: To propose a method for extracting relations between diseases and radiological findings.<br/> [Materials and Methods]: 1,155 sentences relating to radiological findings were selected from an electronical medical textbook for this study. First, dependency trees of the sentences were determined using syntactic analysis, and next, subtrees relating to radiological diagnoses were extracted from dependency trees using medical attributes. Finally, relations between a disease name, which is an entry word, and each finding in a subtree were extracted with a positive or negative attribute.<br/> [Results]: Relations between 124 diseases and 794 radiological findings were extracted with positive or negative attributes. Recall of relation extraction was at a rate of 66%, and precision was at a rate of 95%.<br/> [Conclusion]: Our feasibility study suggests the efficiency of our method for extracting relations between diseases and radiological findings which are useful for building medical ontology for radiological diagnoses.

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