Publication Name	World Journal of Psychiatry
Manuscript ID	95434
Country	China

Received	2024-04-10 08:04
Peer-Review Started	2024-04-10 08:05
To Make the First Decision
Return for Revision	2024-08-25 02:04
Revised	2024-09-03 15:51
Second Decision	2024-09-25 02:37
Accepted by Journal Editor-in-Chief
Accepted by Executive Editor-in-Chief	2024-09-25 08:22
Articles in Press	2024-09-25 08:22
Publication Fee Transferred
Edit the Manuscript by Language Editor
Typeset the Manuscript	2024-09-30 06:24
Publish the Manuscript Online	2024-10-17 09:04

ISSN	2220-3206 (online)
Open Access	This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/licenses/by-nc/4.0/
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Category	Psychiatry
Manuscript Type	Editorial
Article Title	Large multimodal models assist in psychiatry disorders prevention and diagnosis of students
Manuscript Source	Invited Manuscript
All Author List	Xin-Qiao Liu, Xin Wang and Hui-Rui Zhang
ORCID	Author(s) ORCID Number Xin-Qiao Liu http://orcid.org/0000-0001-6620-4119 Xin Wang http://orcid.org/0009-0001-1098-0589
Funding Agency and Grant Number
Corresponding Author	Xin-Qiao Liu, PhD, Associate Professor, School of Education, Tianjin University, No. 135 Yaguan Road, Jinnan District, Tianjin 300350, China. xinqiaoliu@pku.edu.cn
Key Words	Large multimodal models; ChatGPT; Psychiatric disorders; Mental health; Student
Core Tip	Large multimodal models represented by ChatGPT have become a new approach for diagnosing, treating, and addressing students’ mental health issues. However, there are, notably, both opportunities and challenges in the diagnosis and prevention of mental disorders by students. To unleash the full potential of large multimodal models and truly achieve the empowerment of psychological well-being through technology, it is necessary to obtain a correct understanding of their strengths and weaknesses and to continuously explore the organic integration of artificial intelligence and students’ mental health.
Publish Date	2024-10-17 09:04
Citation	<p>Liu XQ, Wang X, Zhang HR. Large multimodal models assist in psychiatry disorders prevention and diagnosis of students. <i>World J Psychiatry</i> 2024; 14(10): 1415-1421</p>
URL	https://www.wjgnet.com/2220-3206/full/v14/i10/1415.htm
DOI	https://dx.doi.org/10.5498/wjp.v14.i10.1415

Full Article (PDF)	WJP-14-1415-with-cover.pdf
Manuscript File	95434_Auto_Edited_092817.docx
Answering Reviewers	95434-answering-reviewers.pdf
Audio Core Tip	95434-audio.mp3
Conflict-of-Interest Disclosure Form	95434-conflict-of-interest-statement.pdf
Copyright License Agreement	95434-copyright-assignment.pdf
Non-Native Speakers of English Editing Certificate	95434-non-native-speakers.pdf
Peer-review Report	95434-peer-reviews.pdf
Scientific Misconduct Check	95434-scientific-misconduct-check.png
Scientific Editor Work List	95434-scientific-editor-work-list.pdf
CrossCheck Report	95434-crosscheck-report.pdf
CrossCheck Report	95434-crosscheck-report.png