ARTIFICIAL INTELLIGENCE IN PSYCHIATRY: APPLICATIONS AND CHALLENGES

Authors : Hasan Belli, Selin Laçin
Pages : 224-233
Doi:10.54270/atljm.2025.96
View : 148 | Download : 854
Publication Date : 2025-10-29
Article Type : Review Paper
Abstract :The increasing global mental illness burden is leading to inequalities in access to mental health services, particularly in low- and middle-income countries. The COVID-19 pandemic further exacerbated this situation and increased the need for digital solutions, new intervention methods. In this context, artificial intelligence offers significant transformative potential in psychiatry and psychotherapy. Artificial intelligence, through subtechnologies, is increasingly used for diagnosis, prognosis, treatment, and psychoeducation. Clinical decision support systems, natural language processing-based sentiment analysis, mobile applications, and telepsychiatry solutions offer significant opportunities for healthcare professionals to reduce workload and improve access to care. In affective disorders, electroencephalography-based deep learning models achieve high diagnostic accuracy; virtual therapy tools have also demonstrated significant effects in psychoeducation and symptom reduction. Algorithms used in schizophrenia, bipolar disorder, and autism have delivered promising results in disease progression prediction and early detection. However, data protection, ethics, and the need for clinical validation remain the main obstacles to widespread application of these technologies. Although artificial intelligence offers significant opportunities in mental health, due to ethical risks and reduced human interaction, it can only be effective if applied in a human-centered, transparent, and impartial manner. In summary, artificial intelligence’s role in psychiatry is growing rapidly and is expected to contribute to the provision of more accessible, cost-effective, and personalized mental health care services in the future. In this process, it is crucial to uphold ethical principles, protect patient privacy, and adopt human-centered approaches.
Keywords : Yapay Zeka, Öğrenme, Ruhsal Bozukluklar, Etik

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