The Role of Artificial Intelligence in Mental Health Diagnosis and Treatment

Abstract

Artificial intelligence (AI) is reshaping the field of mental health, with particularly strong potential in diagnosis and treatment. In diagnostics, AI systems can perform disease classification, risk prediction, early screening, and emotion recognition. Research shows that multimodal models combining neuroimaging, clinical scales, and behavioral signals significantly improve accuracy in identifying common psychological disorders such as depression and anxiety. They also enable continuous monitoring and personalized profiling.In treatment, AI tools are mainly applied to depression, anxiety, emotion regulation, and suicide prevention. Chatbots based on cognitive behavioral therapy (CBT), acceptance and commitment therapy (ACT), and narrative therapy transform the core therapeutic process into immediate dialogue and feedback. Applications and wearable devices have further enabled daily emotion management and crisis intervention. Randomized controlled trials and systematic reviews have shown that these tools can produce moderate to strong effects in alleviating symptoms while lowering the barriers to accessing mental health services.For future development directions, AI needs to achieve breakthroughs in three aspects: First, it should strengthen scientific validation through multi-center and longitudinal research to address the lack of long-term and cross-cultural data; Second, embed crisis identification and referral mechanisms in the dialogue system to enhance clinical safety; Third, improve the fairness, interpretability and privacy protection of algorithms, and establish transparent and responsible application standards. Overall, AI is not an autonomous diagnostic or therapeutic agent, but it has become an important complementary tool for enhancing the accessibility and efficiency of mental health care.