The review article conducted by our department’s academics, Research Assistant Merve Nur Çömlekci and Assoc. Prof. Dr. Tuğba Yılmaz, has been published in Current Approaches in Psychiatry.
Mood disorders, particularly major depressive disorder and bipolar disorder, pose significant challenges in clinical diagnosis. With the rapid advancement of artificial intelligence (AI) technologies in recent years, new opportunities have emerged to enhance diagnostic accuracy, monitor disease progression, and develop personalized treatment approaches for these disorders. This study aims to explore how AI–supported methods contribute to the early diagnosis and monitoring of mood disorders through a comprehensive and up-to-date narrative review approach.
Through machine learning and deep learning techniques (subfields of AI) various data sources such as facial expressions, speech features, body movements, and social media content can be analyzed, allowing for the objective assessment of patients' mood states. Moreover, biomarker data collected through high-accuracy smartphones and wearable devices can be used to monitor depressive and manic episodes and to develop predictive models for these periods. Briefly, the use of AI-based technologies in the field of mental health holds critical potential for improving early intervention opportunities and creating personalized treatment plans. However, issues related to ethics, privacy, and data security present significant limitations to the integration of these technologies into clinical practice. Therefore, more comprehensive and interdisciplinary research is needed to assess the applicability of these technologies.
