Performance Improvement of a Natural Language Processing Tool for Extracting Patient Narratives Related to Medical States From Japanese Pharmaceutical Care Records by Increasing the Amount of Training Data: Natural Language Processing Analysis and Validation Study.

Journal: JMIR medical informatics
PMID: 40053805

Abstract

BACKGROUND: Patients' oral expressions serve as valuable sources of clinical information to improve pharmacotherapy. Natural language processing (NLP) is a useful approach for analyzing unstructured text data, such as patient narratives. However, few studies have focused on using NLP for narratives in the Japanese language.

Authors

  • Yukiko Ohno
    Graduate School of Pharmaceutical Sciences, Keio University, Tokyo, Japan.
  • Tohru Aomori
    Faculty of Pharmacy, Takasaki University of Health and Welfare, Takasaki, Japan.
  • Tomohiro Nishiyama
    Division of Information Science, Graduate School of Science and Technology, Nara Institute of Science and Technology, Nara, Japan.
  • Riri Kato
    Faculty of Pharmacy, Keio University, Tokyo, Japan.
  • Reina Fujiki
    Department of Pharmacy, Keio University Hospital, Tokyo, Japan.
  • Haruki Ishikawa
    Department of Pharmacy, Keio University Hospital, Tokyo, Japan.
  • Keisuke Kiyomiya
    Faculty of Pharmacy, Keio University, Tokyo, Japan.
  • Minae Isawa
    Faculty of Pharmacy, Keio University, Tokyo, Japan.
  • Mayumi Mochizuki
    Faculty of Pharmacy, Keio University, Tokyo, Japan.
  • Eiji Aramaki
    Nara Institute of Science and Technology (NAIST), Japan.
  • Hisakazu Ohtani
    Graduate School of Pharmaceutical Sciences, Keio University, Tokyo, Japan.

Keywords

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