Applications and challenges of generative artificial intelligence in psychiatry

doi:10.3969/j.issn.1674-8115.2025.10.002

Abstract

Abstract:

Mental disorders pose a significant challenge to global public health, profoundly affecting the quality of life of a vast number of individuals and imposing a heavy health burden on society. Nonetheless, there remains a substantial gap between the current societal capacity to provide prevention, diagnosis, and treatment for mental disorders and the existing demand for such services. In recent years, the development and application of artificial intelligence (AI) technologies have provided unprecedented opportunities to enhance mental healthcare services. As one of the fastest-growing fields of AI, generative AI has played a pivotal role in analyzing diverse forms of data, including medical image processing, protein structure prediction, clinical document generation, auxiliary diagnostic discrimination, and clinical decision support. These advancements have significantly strengthened capabilities in clinical diagnosis, data reconstruction, and adjunctive therapeutic interventions. This review highlights the potential applications of generative AI in advancing fundamental psychiatric research, identifying early risk factors for mental disorders, and assisting clinicians in diagnosis and treatment. Additionally, it addresses the challenges and limitations currently facing the application of generative AI to mental healthcare, including biases, privacy breaches, and insufficient interpretability. Finally, the review summarizes strategies to enhance AI's capacity to deliver mental health services, aiming to leverage new technologies to reduce the global burden of mental disorders and improve the quality of life of affected individuals.

Key words: generative artificial intelligence, psychiatry, assisted screening, assisted treatment

CLC Number:

R749

SONG Yijie, CHEN Tianzhen, ZHONG Na, ZHAO Min. Applications and challenges of generative artificial intelligence in psychiatry[J]. Journal of Shanghai Jiao Tong University (Medical Science), 2025, 45(10): 1271-1278.

Figures/Tables 1

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References 87

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