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Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System

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Published on: July 11, 2025

Improving Psychiatry Services with Artificial Intelligence: Opportunities and Challenges.

Muhammed Balli, Aslı Ercan Doğan, Hale Yapici Eser

Turk Psikiyatri Dergisi = Turkish Journal of Psychiatry

|January 9, 2025

Summary

Artificial intelligence (AI) can enhance psychiatric care globally and in Türkiye by improving diagnosis and treatment accessibility. Addressing AI biases and ethical concerns is crucial for its effective integration into mental health services.

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Last Updated: Jul 6, 2026

Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System

Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System

Published on: July 11, 2025

Area of Science:

Psychiatry
Artificial Intelligence
Public Health

Background:

Mental disorders pose a significant global public health challenge with increasing prevalence and economic burden.
Türkiye faces a shortage of psychiatrists, impacting mental health service quality and accessibility.
Artificial intelligence (AI) presents potential solutions to address these challenges in psychiatric care.

Purpose of the Study:

To review the potential of AI, particularly large language models (LLMs), to transform psychiatric care worldwide and in Türkiye.
To explore AI applications in diagnosis, personalized treatment, and monitoring of mental disorders.
To identify challenges and propose strategies for AI integration in mental health.

Main Methods:

Review of current AI technologies (machine learning, deep learning) and their applications in mental health.
Analysis of data sources used by AI, including speech patterns, neuroimaging, and behavioral measures.
Examination of challenges like algorithmic bias, data privacy, ethical concerns, and LLM confabulation.

Main Results:

AI demonstrates promising capabilities in enhancing diagnostic accuracy and accessibility of mental health services.
LLMs and other AI tools can analyze diverse data for mental disorder assessment and treatment.
Significant challenges remain, including bias, privacy, ethics, and reliability issues.

Conclusions:

AI offers transformative potential for psychiatric care, improving accuracy and access while maintaining human-centered care.
Interdisciplinary collaboration is essential to develop culturally adapted AI tools for the Turkish context.
Rigorous research and ethical frameworks are necessary for the effective and equitable integration of AI in mental health.