Kaygı Bozukluklarının Tanısal Amaçlı Klinik Değerlendirmesi ve Yapay Zekâ

Abstract

Bu çalışma kaygı bozukluklarının klinik değerlendirilmesinde yapay zekâ uygulamalarının rolü üzerine güncel bir alanyazın incelemesidir. Kaygı bozuklukları, aşırı korku ve endişe ile karakterize olup kişinin işlevselliğini olumsuz yönde etkileyen psikolojik rahatsızlıklardır. Son yıllarda, yapay zekâ teknolojilerindeki gelişmeler ruh sağlık alanında yeni değerlendirme yaklaşımlarının ortaya çıkmasında etkili olmaktadır. Bu kapsamda, kaygı bozukluklarının tanılanması ve izlenmesinde doğal dil işleme, makine öğrenmesi ve derin öğrenme ile birlikte giyilebilir teknolojiler, sohbet botları, nörogörüntüleme analizleri ve sanal gerçeklik uygulamalarının tanı ve tedavi süreçlerindeki kullanımı incelenmiştir. İncelenen çalışmalar yapay zekâ temelli teknolojilerin fizyolojik belirtilerin anlık takibi, verileri bütüncül olarak işleyebilme, erişilebilirlik ve kişiye özel değerlendirme yapabilme gibi avantajlarının olduğunu göstermektedir. Bununla birlikte veri güvenliği, etik standartlar ve terapötik ilişkideki zorluklar gibi konular bu teknolojilerin temel dezavantajları olarak öne çıkmaktadır. Sonuç olarak, yapay zekâ temelli teknolojiler kaygı bozukluklarının klinik değerlendirilmesinde yüksek bir potansiyel sergilese de bu potansiyelin klinik uygulamalarda güvenli ve etik bir zeminde standardize edilebilmesi için daha kapsamlı çalışmalara ihtiyaç duyulmaktadır.

Keywords

• kaygı bozuklukları
• yapay zekâ
• klinik değerlendirme
• tanı.

Clinical Assessment of Anxiety Disorders for Diagnostic Purposes and Artificial Intelligence

Abstract

This study is a current literature review examining the role of artificial intelligence applications in the clinical assessment of anxiety disorders. Anxiety disorders are psychological conditions characterized by excessive fear and anxiety that negatively affect an individual’s level of functioning. In recent years, advancements in artificial intelligence technologies have contributed to the emergence of new assessment approaches in the field of mental health. In this context, the use of natural language processing, machine learning, and deep learning methods, along with wearable technologies, chatbots, neuroimaging analyses, and virtual reality applications, in the diagnosis and monitoring processes of anxiety disorders has been examined. The reviewed studies indicate that artificial intelligence–based technologies offer advantages such as real-time monitoring of physiological symptoms, the ability to process data in an integrated manner, accessibility, and the capacity to provide personalized assessments. However, issues related to data security, ethical standards, and therapeutic relationship emerge as major limitations of these technologies. In conclusion, although artificial intelligence–based technologies demonstrate high potential in the clinical assessment of anxiety disorders, more comprehensive studies are needed to ensure that this potential can be standardized within clinical practice on a safe and ethical basis.

Keywords

• anxiety disorders
• artificial intelligence
• clinical assessment
• diagnosis

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