Publication Name	World Journal of Psychiatry
Manuscript ID	127446
DOI	10.5498/wjp.127446
Country	China

Category	Psychiatry
Manuscript Type	Minireviews
Article Title	Ethical, regulatory and clinical challenges of implementing explainable artificial intelligence-driven structural magnetic resonance imaging violence prediction in schizophrenia care
Manuscript Source	Invited Manuscript
All Author List	Shi-Han Liu, Chang-Yong Zheng, Jian-Fei Kan and Fu-Jian Chen
Funding Agency and Grant Number	Funding Agency Grant Number 2025 Jining Key Research and Development Program 2025YXNS114
Corresponding Author	Fu-Jian Chen, Associate Chief Physician, Associate Professor, Director, MD, Department of Imaging, Shandong Daizhuang Hospital, No. 1 Jidai Road, Rencheng District, Jining 272051, Shandong Province, China. dzyyyxk2014@163.com
Key Words	Explainable artificial intelligence; Structural magnetic resonance imaging; Schizophrenia; Violence risk prediction; Medical ethics; Health care regulation
Core Tip	Violent and aggressive behavior produces substantial burdens in schizophrenia care, and traditional risk-assessment approaches remain subjective with limited predictive capacity. Structural magnetic resonance imaging-based explainable artificial intelligence represents investigational risk-support approaches for violence-risk stratification; however, clinical translation confronts major barriers, including neurodata privacy risks, algorithmic bias, inadequate validation standards, and ambiguous medicolegal liability. Effective real-world deployment of this neuro-artificial intelligence (AI) technology depends on multidisciplinary collaboration among clinicians, AI developers, ethicists, regulators, and patients. Jointly built governance frameworks are urgently needed to support its safe, fair, and clinically meaningful use in routine psychiatric practice, avoiding over-optimistic expectations and preventing potential social harm stemming from misapplied predictive tools.
Citation	Liu SH, Zheng CY, Kan JF, Chen FJ. Ethical, regulatory and clinical challenges of implementing explainable artificial intelligence-driven structural magnetic resonance imaging violence prediction in schizophrenia care. World J Psychiatry 2026; In press DOI: https://doi.org/10.5498/wjp.127446
PDF	127446-in-press.pdf

Received	2026-08-31 09:09
Peer-Review Started	2026-08-31 09:09
First Decision by Editorial Office Director
Return for Revision	2026-09-10 03:02
Revised	2026-09-23 07:19
Publication Fee Transferred
Second Decision by Editor	2026-10-29 07:08
Second Decision by Editor-in-Chief
Final Decision by Editorial Office Director	2026-10-29 10:28
Articles in Press	2026-10-29 10:28
Edit the Manuscript by Language Editor
Typeset the Manuscript

ISSN	2220-3206 (online)
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