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Artificial intelligence in psychiatric education: Enhancing clinical competence through simulation.

作者信息

Ajluni Victor

机构信息

Department of Psychiatry, Wayne State University, Detroit, Michigan, Livonia, MI, USA.

出版信息

Ind Psychiatry J. 2025 Jan-Apr;34(1):11-15. doi: 10.4103/ipj.ipj_377_24. Epub 2025 Jan 15.


DOI:10.4103/ipj.ipj_377_24
PMID:40376628
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12077637/
Abstract

The integration of artificial intelligence (AI) in psychiatric education offers transformative potential to enhance clinical competence through realistic simulations. Traditional educational methods face limitations in replicating complex psychiatric cases, and AI-based tools provide a scalable solution. This narrative review examines current evidence on the efficacy of AI-powered simulations, focusing on their role in skill development, diagnostic accuracy, and safe clinical training. Through a comprehensive literature review of studies from 2010 to 2024, key themes such as AI's ability to standardize patient encounters, provide instant feedback, and improve student confidence are explored. Findings suggest that AI can enhance psychiatric education by offering consistent, adaptable learning experiences that prepare trainees for real-world complexities. However, challenges such as ethical considerations and accessibility disparities must be addressed for AI to be effectively integrated into psychiatric training. This review provides insights into the future of AI in medical education and its potential impact on training the next generation of psychiatrists.

摘要

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本文引用的文献

[1]
The growing field of digital psychiatry: current evidence and the future of apps, social media, chatbots, and virtual reality.

World Psychiatry. 2021-10

[2]
A comparison of deep learning performance against health-care professionals in detecting diseases from medical imaging: a systematic review and meta-analysis.

Lancet Digit Health. 2019-10

[3]
A Framework for Competencies for the Use of Mobile Technologies in Psychiatry and Medicine: Scoping Review.

JMIR Mhealth Uhealth. 2020-2-21

[4]
Introducing Artificial Intelligence Training in Medical Education.

JMIR Med Educ. 2019-12-3

[5]
Dissecting racial bias in an algorithm used to manage the health of populations.

Science. 2019-10-25

[6]
Artificial Intelligence in Medical Education: Best Practices Using Machine Learning to Assess Surgical Expertise in Virtual Reality Simulation.

J Surg Educ. 2019

[7]
Applications and Challenges of Implementing Artificial Intelligence in Medical Education: Integrative Review.

JMIR Med Educ. 2019-6-15

[8]
Transdiagnostic Mobile Health: Smartphone Intervention Reduces Depressive Symptoms in People With Mood and Psychotic Disorders.

JMIR Ment Health. 2019-4-12

[9]
Digital Education in Health Professions: The Need for Overarching Evidence Synthesis.

J Med Internet Res. 2019-2-14

[10]
Machine learning in mental health: a scoping review of methods and applications.

Psychol Med. 2019-2-12

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