Publication Name	World Journal of Psychiatry
Manuscript ID	108199
Country	China

Category	Psychiatry
Manuscript Type	Minireviews
Article Title	Large language models in clinical psychiatry: Applications and optimization strategies
Manuscript Source	Invited Manuscript
All Author List	Yi-Fan Wang, Ming-Da Li, Su-Hong Wang, Yin Fang, Jie Sun, Lin Lu and Wei Yan
Funding Agency and Grant Number	Funding Agency Grant Number STI2030-Major Projects No. 2021ZD0203400 and No. 2021ZD0200800 National Natural Science Foundation of China No. 82171477
Corresponding Author	Wei Yan, Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Huayuan Bei Road, Beijing 100191, China. weiyan@bjmu.edu.cn
Key Words	Large language models; Clinical psychiatry; Mixture of experts; Mental health; Research progress
Core Tip	This article comprehensively reviews the application scenarios and research advancements of large language models (LLMs) in psychiatry, ranging from outpatient reception, diagnosis and therapy, clinical nursing, medication safety, to prognosis tracking. It explores optimization methods for LLMs in psychiatry. These methods combine the techniques such as pre-training, supervised fine-tuning, retrieval-augmented generation, agent systems, and prompt engineering. Based on the research findings, we propose a clinical LLM for mental health using the Mixture of Experts framework. This approach addresses the shortcomings of single LLM system and aims to improve the accuracy of psychiatric diagnosis and therapeutic interventions.
Citation	Wang YF, Li MD, Wang SH, Fang Y, Sun J, Lu L, Yan W. Large language models in clinical psychiatry: Applications and optimization strategies. World J Psychiatry 2025; In press

Received	2025-04-14 07:04
Peer-Review Started	2025-04-21 00:18
To Make the First Decision
Return for Revision	2025-05-13 12:15
Revised	2025-05-27 00:18
Second Decision	2025-09-03 02:46
Accepted by Journal Editor-in-Chief
Accepted by Executive Editor-in-Chief	2025-09-03 08:05
Articles in Press	2025-09-03 08:05
Publication Fee Transferred
Edit the Manuscript by Language Editor
Typeset the Manuscript

ISSN	2220-3206 (online)
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