Abstract Anxiety disorders are prevalent mental health conditions characterized by intense worry, fear, and apprehension, which negatively impact individuals’ quality of life and functional capacity. These disorders encompass various subtypes, including separation anxiety, selective mutism, specific phobia, social anxiety, panic disorder, agoraphobia, and generalized anxiety disorder. If left untreated, anxiety disorders can adversely affect individuals’ social, academic, and occupational functioning and may lead to the development of additional psychological problems. In recent years, artificial intelligence based technologies have offered innovative solutions in the diagnosis and treatment of anxiety disorders, contributing to more objective and effective diagnostic processes. This study aims to examine scientific publications that employ Artificial intelligence approaches in the diagnosis and treatment of anxiety disorders using bibliometric analysis methods. The bibliometric analysis, which included 2491 studies retrieved from the Scopus and Web of Science databases, reveals that the field exhibits multidimensional and interdisciplinary development both theore
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