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©The Author(s) 2024. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Psychiatry. Oct 19, 2024; 14(10): 1415-1421
Published online Oct 19, 2024. doi: 10.5498/wjp.v14.i10.1415
Published online Oct 19, 2024. doi: 10.5498/wjp.v14.i10.1415
Large multimodal models assist in psychiatry disorders prevention and diagnosis of students
Xin-Qiao Liu, Xin Wang, School of Education, Tianjin University, Tianjin 300350, China
Hui-Rui Zhang, Faculty of Education, The Open University of China, Beijing 100039, China
Author contributions: Liu XQ and Zhang HR designed the study; Liu XQ, Wang X and Zhang HR wrote the manuscript; All authors have read and approved the final manuscript.
Conflict-of-interest statement: All the authors report no relevant conflicts of interest for this article.
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/
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
Received: April 10, 2024
Revised: September 3, 2024
Accepted: September 25, 2024
Published online: October 19, 2024
Processing time: 190 Days and 1.2 Hours
Revised: September 3, 2024
Accepted: September 25, 2024
Published online: October 19, 2024
Processing time: 190 Days and 1.2 Hours
Core Tip
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.