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心理健康领域的人工智能:整合多模态深度学习在精神障碍预防与治疗中的机遇与挑战

Artificial intelligence in mental health: integrating opportunities and challenges of multimodal deep learning for mental disorder prevention and treatment.

作者信息

Narimani Mohammad, Naeim Mahdi

机构信息

Department of Psychology, University of Mohaghegh Ardabili, Ardabil, Iran.

出版信息

Ann Med Surg (Lond). 2025 Jul 22;87(9):5757-5761. doi: 10.1097/MS9.0000000000003624. eCollection 2025 Sep.

Abstract

BACKGROUND

Artificial intelligence (AI), through multimodal deep learning and predictive analytics, holds transformative potential in the prevention and treatment of mental disorders. This study explores the opportunities and challenges of these technologies.

OBJECTIVE

To present a conceptual framework for the responsible application of AI in mental health care.

METHODS

This integrative review analyzed selected sources from Google Scholar up to June 2025. Both qualitative and quantitative analyses were conducted to identify opportunities and challenges.

RESULTS

Key opportunities include early detection, personalized treatment, and enhanced access to mental health services. Major challenges involve ethical concerns, algorithmic bias, and data quality issues.

CONCLUSION

AI can revolutionize mental health care, but it requires standardization and regulatory oversight. Future research should focus on addressing ethical dilemmas and improving data quality.

摘要

背景

人工智能(AI)通过多模态深度学习和预测分析,在精神障碍的预防和治疗方面具有变革潜力。本研究探讨了这些技术的机遇与挑战。

目的

提出一个在精神卫生保健中负责任应用人工智能的概念框架。

方法

本综合综述分析了截至2025年6月从谷歌学术搜索中选取的资料来源。进行了定性和定量分析以确定机遇和挑战。

结果

关键机遇包括早期检测、个性化治疗以及增加获得精神卫生服务的机会。主要挑战涉及伦理问题、算法偏差和数据质量问题。

结论

人工智能可以彻底改变精神卫生保健,但需要标准化和监管监督。未来的研究应侧重于解决伦理困境和提高数据质量。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a479/12401332/2c223709d69e/ms9-87-5757-g001.jpg

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