Large multimodal models assist in psychiatry disorders prevention and diagnosis of students

Abstract

Students are considered one of the groups most affected by psychological problems. Given the highly dangerous nature of mental illnesses and the increasingly serious state of global mental health, it is imperative for us to explore new methods and approaches concerning the prevention and treatment of mental illnesses. Large multimodal models (LMMs), as the most advanced artificial intelligence models (i.e. ChatGPT-4), have brought new hope to the accurate prevention, diagnosis, and treatment of psychiatric disorders. The assistance of these models in the promotion of mental health is critical, as the latter necessitates a strong foundation of medical knowledge and professional skills, emotional support, stigma mitigation, the encouragement of more honest patient self-disclosure, reduced health care costs, improved medical efficiency, and greater mental health service coverage. However, these models must address challenges related to health, safety, hallucinations, and ethics simultaneously. In the future, we should address these challenges by developing relevant usage manuals, accountability rules, and legal regulations; implementing a human-centered approach; and intelligently upgrading LMMs through the deep optimization of such models, their algorithms, and other means. This effort will thus substantially contribute not only to the maintenance of students’ health but also to the achievement of global sustainable development goals.