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

Methods and New Tools in Mental Health Research (911) Clinical Informatics (2287) Digital Mental Health Interventions, e-Mental Health and Cyberpsychology (3229) Clinical Information and Decision Making (3726) Data Science (707) Generative Language Models Including ChatGPT (1533)

Published on in Vol 13 (2026)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/83352, first published .
Doctor shows patient a digital brain scan on a tablet.

Prediction of 12-Week Remission in Patients With Depressive Disorder Using Reasoning-Based Large Language Models: Model Development and Validation Study

Prediction of 12-Week Remission in Patients With Depressive Disorder Using Reasoning-Based Large Language Models: Model Development and Validation Study

Authors of this article:

Jin-Hyun Park1 Author Orcid Image ;   Hee-Ju Kang2 Author Orcid Image ;   Ji Hyeon Jeon2 Author Orcid Image ;   Sung-Gil Kang2 Author Orcid Image ;   Ju-Wan Kim2 Author Orcid Image ;   Jae-Min Kim2 Author Orcid Image ;   Hwamin Lee1 Author Orcid Image
Article Authors Cited by (3) Tweetations Metrics

Journals

  1. Kwon S, Kim Y, Jhon M, Park J, Lim B, Jeon E, Kim J, Kim J, Lee H. On-premises open-source large language models for privacy-preserving multimodal depression screening. International Journal of Medical Informatics 2026;220:106577 View
  2. Shaw S, Bell D. Acceptability of AI-Assisted Psychotherapy to Prospective Patients and Their Intent to Continue Treatment: A Vignette Study. American Journal of Psychotherapy 2026 View
  3. Babirye S, Huang R, Zeng C, Mutinye J, Kemigisha B, Wamala K, Kasujja R, Kalani K, Andres Martinez R, Nakimuli-Mpungu E. Development and External Validation of a Treatment-Adjusted Machine Learning Model to Support Risk-Informed Group-Based Depression Care for People Living with HIV in Uganda. Wellcome Open Research 2026;11:203 View