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

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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