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

IF 1.6 Q2 MEDICINE, GENERAL & INTERNAL

Annals of Medicine and Surgery Pub Date : 2025-07-22 eCollection Date: 2025-09-01 DOI:10.1097/MS9.0000000000003624

Mohammad Narimani, Mahdi Naeim

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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.

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精神健康中的人工智能：整合多模态深度学习用于精神障碍预防和治疗的机遇和挑战。

背景：人工智能（AI）通过多模态深度学习和预测分析，在预防和治疗精神障碍方面具有变革性潜力。本研究探讨了这些技术的机遇和挑战。目的：提出人工智能在精神卫生保健中负责任应用的概念框架。方法：本综合综述分析了谷歌Scholar截至2025年6月的精选文献。进行了定性和定量分析，以确定机遇和挑战。结果：关键机会包括早期发现、个性化治疗和增加获得精神卫生服务的机会。主要的挑战包括伦理问题、算法偏见和数据质量问题。结论：人工智能可以彻底改变精神卫生保健，但它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。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Annals of Medicine and Surgery MEDICINE, GENERAL & INTERNAL-

自引率

5.90%

发文量

1665