Accessibility settings

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

Formative Evaluation of Digital Health Interventions (4918) Clinical Informatics (2139) Natural Language Processing (1227) Clinical Mental Health Informatics (129) Generative Language Models Including ChatGPT (1419) AI Language Models in Health Care (696)

Published on in Vol 10 (2026)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/85671, first published .
Two people reviewing a daily report schedule on a clipboard, one writing.

Comparative Analysis of Japanese Clinical Note Styles Between Physicians and Large Language Models Using Identical Psychiatric Cases: Quantitative Text Analysis

Comparative Analysis of Japanese Clinical Note Styles Between Physicians and Large Language Models Using Identical Psychiatric Cases: Quantitative Text Analysis

Authors of this article:

Wataru Arihisa1 Author Orcid Image ;   Tomohiro Nishiyama1 Author Orcid Image ;   Shoko Wakamiya1 Author Orcid Image ;   Eiji Aramaki1 Author Orcid Image
Article Authors Cited by (1) Tweetations Metrics

Journals

  1. Ye J, Shen Z, Li B, Yan W. A generative two-stage semantic intermediary framework for explainable mental health early warning in higher education. Frontiers in Psychiatry 2026;17 View