Trends and features of autism spectrum disorder research using artificial intelligence techniques: a bibliometric approach

The prevalence of autism spectrum disorder (ASD) has risen rapidly in recent decades. Owing to its success across disciplines, the use of artificial intelligence (AI) in the screening of ASD has emerged as a prominent solution. We conducted a bibliometric analysis on AI-powered ASD screening research with a unit of 2090 publications retrieved from Scopus database in the period 2010-2021. Our findings show, among other things, that the annual growth rate of publications was 33.05% and scientific production drastically increased 23-fold from 22 in 2010 to 509 in 2021 with nearly two thirds (1307; 62,54%) of the retrieved documents being published between 2019-2021. The USA was the global leader in terms of scientific output with 730 publications followed by China (255), and India (251). Stanford university, the scientific journal NeuroImage, and Dennis P. Wall were the most globally prolific institution, publication source, and author, respectively. Using VOSviewer's clustering algorithms, keyword and topic analysis identified neuroimaging techniques and genetic research as hot and emerging research trends. Interestingly, three of the top ten prolific authors were women, indicating a significant milestone for gender rebalancing efforts in the AI workforce. The findings will help both experienced and aspiring scientists better understand the structure and current state of knowledge, uncover patterns of collaboration, and identify emerging trends in ASD research using AI.