Trends in Artificial Intelligence for Autism Spectrum Disorder: A Bibliometric Analysis Study - Ozek, Muzeyyen Bulut; Gulmus, Merve (Int Soc Technology Education & Science-Istes, 2025)
This study aims to analyze the bibliometric trends of research articles on applying Artificial Intelligence (AI) technology in individuals with Autism Spectrum Disorder (ASD). Within the scope of this study, bibliometric data from 1345 articles published in the Web of Science database between 2014 and 2024 were examined. The analysis revealed a significant increase in studies on using AI technology in the diagnosis and educational processes of individuals with ASD since 2018. The findings indicate that the United States (USA), China, and India are the leading contributors in terms of publication volume in this field. Additionally, the most frequently used keywords in these publications include ASD, Machine Learning, and Deep Learning. In addition, the notable contributions of researchers such as Dennis Wall, Peter Washington, and Aaron Kline have drawn attention. This study highlights the potential of AI technologies in facilitating accurate and rapid diagnosis of ASD and in enhancing personalized educational processes. Moreover, it provides a foundation for future research by identifying key trends in the literature.
Keywords: Autism Spectrum Disorder; ASD; Artificial Intelligence; Autism; AI; Bibliometric analysis