Artificial Intelligence–Based Clinical Assessment in Mood Disorders: A Narrative Review

Abstract

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.

Keywords

• artificial intelligence
• clinical assessment
• mood disorders
• depression
• bipolar disorders

Duygudurum Bozukluklarında Yapay Zekâ Destekli Klinik Değerlendirme: Bir Anlatı Derlemesi

Öz

Duygudurum bozuklukları, özellikle majör depresif bozukluk ve bipolar bozukluk, klinik tanı süreçlerinde önemli güçlükler barındırmaktadır. Son yıllarda yapay zekâ teknolojilerinin hızla gelişmesiyle birlikte, bu bozukluklarda tanı doğruluğunun arttırılması, hastalık seyrinin izlenmesi ve kişiselleştirilmiş tedavi yaklaşımlarının geliştirilmesi yönünde yeni olanaklar ortaya çıkmıştır. Bu çalışmada, yapay zekâ destekli yöntemlerin duygudurum bozukluklarının erken tanısı ve hastalık sürecinin izlenmesi bağlamında nasıl katkı sağladığı güncel ve kapsamlı bir anlatı derlemesi tekniği ile ele alınacaktır. Yapay zekânın alt disiplinlerinden olan makine öğrenmesi ve derin öğrenme teknikleri sayesinde, yüz ifadeleri, ses özellikleri, vücut hareketleri ve sosyal medya içerikleri gibi çok çeşitli veri kaynakları analiz edilebilmekte ve böylece hastaların duygudurumları objektif ölçütlerle değerlendirilebilmektedir. Buna ek olarak, yüksek doğruluk oranlarına sahip akıllı telefonlar ve giyilebilir cihazlar üzerinden toplanan biyobelirteç verileri aracılığıyla depresif ve manik dönemler izlenebilmekte, bu dönemleri tahmin eden öngörü modelleri geliştirilebilmektedir. Kısaca, yapay zekâ tabanlı teknolojilerin ruh sağlığı alanındaki kullanımı, erken müdahale olanaklarının artırılması ve kişiye özel tedavi planlarının oluşturulması açısından önemli bir potansiyele sahiptir. Bununla birlikte, etik, mahremiyet ve veri güvenliği gibi konular, bu teknolojilerin klinik uygulamalara entegrasyonunda önemli sınırlılıklar doğurmaktadır. Bu nedenle, söz konusu teknolojilerin uygulanabilirliği üzerine daha kapsamlı ve disiplinlerarası araştırmalara gereksinim bulunmaktadır.

Anahtar Kelimeler

• yapay zekâ
• klinik değerlendirme
• duygudurum bozuklukları
• depresyon
• bipolar bozukluk

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