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

ABSTRACT:

Background

Depressive disorder affects over 300 million people globally, with only 30% to 40% of patients achieving remission with initial antidepressant monotherapy. This low response rate highlights the critical need for digital mental health tools that can identify treatment response early in the clinical pathway.

Objective

This study aimed to evaluate whether reasoning-based large language models (LLMs) could accurately predict 12-week remission in patients with depressive disorder undergoing antidepressant monotherapy and to assess the clinical validity and interpretability of model-generated rationales for integration into digital mental health workflows.

Methods

We analyzed data from 390 patients in the MAKE Biomarker discovery study who were undergoing first-s

SUBMITTER: Park JH 

PROVIDER: S-EPMC12829737 | biostudies-literature | 2026 Jan

REPOSITORIES: biostudies-literature