Document Type : Original Article
Authors
University of Tabriz
Abstract
Purpose: This study mapped the global scientific landscape of artificial intelligence applications in children with developmental disorders through a bibliometric analysis, identifying publication trends, influential contributors, collaboration networks, thematic evolution, and emerging research directions.
Methodology: This applied descriptive study employed scientometric methods to analyze 1,349 publications indexed in the Web of Science between 1994 and November 2024. Data were retrieved using an advanced search strategy and analyzed using the Relative Specialization Index (RSI), Microsoft Excel, HistCite, and VOSviewer to examine publication growth, collaboration patterns, and knowledge structures.
Findings: Scientific output increased substantially after 2019, peaking in 2024 with 413 publications (30.6%). The USA was the most productive country (382 publications), whereas the UK achieved the highest local citation impact. Saudi Arabia (RSI = 0.65) and Greece (RSI = 0.55) exhibited the highest levels of research specialization. Dennis Wall (Stanford University) was the most influential author, and Frontiers in Psychiatry emerged as the leading publication outlet. Co-occurrence analysis identified eight thematic clusters, with AI and autism spectrum disorder representing the dominant research themes. Overlay analysis further highlighted neuroimaging and explainable AI as emerging research topics.
Conclusion: The findings indicate a clear evolution of the field toward precision psychiatry, multimodal digital monitoring, and explainable AI, reflecting growing interest in interpretable and clinically applicable AI approaches.
Value: This study provides a comprehensive overview of the intellectual structure, thematic evolution, and emerging research frontiers of AI applications in developmental disorders, offering valuable evidence to support future research, interdisciplinary collaboration, and informed research policy.
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