| Sumario: | Background: Mental disorders are a major contributor to the global burden of disease, highlighting the urgent need for more effective, accessible, and personalized psychiatric care. In parallel, rapid development of digital technologies has accelerated the integration of artificial intelligence (AI) into medicine. Objective: The objective of this manuscript is to provide an overview of current state of knowledge regarding AI applications in psychiatry, with the emphasis on associated limitations, challenges and directions for future research. Material and Methods: This review was based on scientific publications retrieved from PubMed and Google Scholar databases which were then subjected into a comprehensive review. Results: Potential benefits of AI include improved diagnostic accuracy, earlier detection of mental disorders, enhanced treatment personalization, and increased accessibility of psychiatric services. However, despite promising developments, AI implementation into psychiatry raises significant challenges. Key limitations include issues related to data quality, algorithmic bias, lack of transparency, and limited generalizability of models across diverse populations. Ethical and legal concerns, such as patient privacy, informed consent, and responsibility for clinical decisions, remain critical barriers to widespread implementation. Conclusions: AI holds substantial promise for transforming psychiatric care, but its safe and effective integration requires rigorous validation, ethical oversight, and interdisciplinary collaboration.
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