Automated System to Capture Patient Symptoms From Multitype Japanese Clinical Texts: Retrospective Study.

Journal: JMIR medical informatics
PMID: 39316418

Abstract

BACKGROUND: Natural language processing (NLP) techniques can be used to analyze large amounts of electronic health record texts, which encompasses various types of patient information such as quality of life, effectiveness of treatments, and adverse drug event (ADE) signals. As different aspects of a patient's status are stored in different types of documents, we propose an NLP system capable of processing 6 types of documents: physician progress notes, discharge summaries, radiology reports, radioisotope reports, nursing records, and pharmacist progress notes.

Authors

  • Tomohiro Nishiyama
    Division of Information Science, Graduate School of Science and Technology, Nara Institute of Science and Technology, Nara, Japan.
  • Ayane Yamaguchi
    Graduate School of Medicine, Kyoto University, Kyoto, Japan.
  • Peitao Han
    Department of Information Science, Nara Institute of Science and Technology, Ikoma, Japan.
  • Lis Weiji Kanashiro Pereira
    Center for Information and Neural Networks, Advanced ICT Research Institute, Osaka, Japan.
  • Yuka Otsuki
    Department of Information Science, Nara Institute of Science and Technology, Ikoma, Japan.
  • Gabriel Herman Bernardim Andrade
    Department of Information Science, Nara Institute of Science and Technology, Ikoma, Japan.
  • Noriko Kudo
    Department of Information Science, Nara Institute of Science and Technology, Ikoma, Japan.
  • Shuntaro Yada
    Graduate School of Science and Technology, Nara Institute of Science and Technology, Ikoma, Nara, Japan.
  • Shoko Wakamiya
    Nara Institute of Science and Technology (NAIST), Japan.
  • Eiji Aramaki
    Nara Institute of Science and Technology (NAIST), Japan.
  • Masahiro Takada
    Department of Breast Surgery, Kyoto University Hospital, 54 Kawaharacho, Shogoin, Sakyo-ku, Kyoto, 606-8507, Japan. masahiro@kuhp.kyoto-u.ac.jp.
  • Masakazu Toi
    Department of Breast Surgery, Kyoto University Hospital, 54 Kawaharacho, Shogoin, Sakyo-ku, Kyoto, 606-8507, Japan.

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