This paper is in the following e-collection/theme issue:

Natural Language Processing (877) AI Language Models in Health Care (172) Big Data (306) Information Seeking, Information Needs (546) Machine Learning (1997) Methods and Instruments in Medical Informatics (182) New Technologies (106) Ontologies, Classifications, and Coding (311) Secondary Use of Clinical Data for Research and Surveillance (459) Tools, Programs and Algorithms (364)

Published on in Vol 13 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/68863, first published .
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

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

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

Authors of this article:

Yukiko Ohno1 Author Orcid Image ;   Tohru Aomori2 Author Orcid Image ;   Tomohiro Nishiyama3 Author Orcid Image ;   Riri Kato4 Author Orcid Image ;   Reina Fujiki5 Author Orcid Image ;   Haruki Ishikawa5 Author Orcid Image ;   Keisuke Kiyomiya4 Author Orcid Image ;   Minae Isawa4 Author Orcid Image ;   Mayumi Mochizuki4 Author Orcid Image ;   Eiji Aramaki3 Author Orcid Image ;   Hisakazu Ohtani1, 5, 6 Author Orcid Image
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Journals

  1. Hossain B, Preum S, Rabbi M, Ara R, Ali M. Extracting Symptoms of Complex Conditions From Online Discourse (Subreddit to Symptomatology): Lexicon-Based Approach. JMIR Medical Informatics 2025;13:e70940 View