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Improving Psychiatry Services with Artificial Intelligence: Opportunities and Challenges

Muhammed BALLI, Aslı ERCAN DOĞAN, Hale YAPICI ESER
2024 35(4): 317-328
DOI: 10.5080/u27604
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İNGİLİZCE ÖZET

Mental disorders are a critical global public health problem due to their
increasing prevalence, rising costs, and significant economic burden.
Despite efforts to increase the mental health workforce in Türkiye, there is
a significant shortage of psychiatrists, limiting the quality and accessibility
of mental health services. This review examines the potential of artificial
intelligence (AI), especially large language models, to transform psychiatric
care in the world and in Türkiye. AI technologies, including machine
learning and deep learning, offer innovative solutions for the diagnosis,
personalization of treatment, and monitoring of mental disorders using
a variety of data sources, such as speech patterns, neuroimaging, and
behavioral measures. Although AI has shown promising capabilities
in improving diagnostic accuracy and access to mental health services,
challenges such as algorithmic biases, data privacy concerns, ethical
implications, and the confabulation phenomenon of large language
models prevent the full implementation of AI in practice. The review
highlights the need for interdisciplinary collaboration to develop
culturally and linguistically adapted AI tools, particularly in the Turkish
context, and suggests strategies such as fine-tuning, retrieval-augmented
generation, and reinforcement learning from human feedback to increase
AI reliability. Advances suggest that AI can improve mental health care
by increasing diagnostic accuracy and accessibility while preserving the
essential human elements of medical care. Current limitations need to be
addressed through rigorous research and ethical frameworks for effective
and equitable integration of AI into mental health care.
Keywords: Artificial İntelligence, Health, Large Language Model,
Machine Learning, Psychiatry