AI-Driven Clinical Decision Support Optimizes Treatment Accuracy for Mental Illness
DOI:
https://doi.org/10.71222/474btc69Keywords:
artificial intelligence, mental illness, clinical decision support, multimodal fusion, interpretabilityAbstract
This paper focuses on exploring the application of AI-based clinical decision support systems in the precise treatment of mental disorders, and analyzes their mechanisms of action, key techniques, and technical solutions. This paper proposes a series of system architecture methods, including unstructured data processing, multi-modal feature fusion, individualized treatment modeling, and interpretable process design, to improve the efficiency and individualization of precise treatment for mental disorders. Meanwhile, an experimental verification system was proposed to comprehensively verify the functional performance and practical value of the system, providing good technical support for the intelligent diagnosis and treatment of clinical mental disorders by this system.
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