The Current Research Landscape on the Machine Learning Application in Autism Spectrum Disorder: A Bibliometric Analysis From 2012 to 2022 (Preprint)

Abstract

Language deficits, restricted and repetitive interests, and social difficulties are among the characteristics of autism spectrum disorder (ASD). Machine learning and neuroimaging have also been combined to examine ASD. Utilizing bibliometric analysis, this study examines the current state and hot topics in machine learning for ASD. In 2012 to 2022, the Web of Science Core Collection (WoSCC) was searched for publications relating to machine learning and ASD. Authors, articles, journals, institutions, and countries were characterized using Microsoft Excel 2021 and VOSviewer. Analysis of knowledge networks, collaborative maps, hotspots, and trends was conducted using VOSviewer and CiteSpace. A total of 660 papers were identified between 2012 and 2022. There was a slow growth in publications until 2016; then, between 2017 and 2021, a sharp increase was recorded. Among the most important contributors to this field were the United States, China, and England. Among the top major research institutions with numerous publications were Stanford University, Harvard Medical School, University of Pennsylvania, and King's College London. Wall, Dennis P. was the most productive author. Merico, Daniele, and Scherer, Stephen W. were the highest-cited authors. Scientific Reports, Plos One, and Translational Psychiatry were the three productive journals. "Autism", "machine learning", "Children", "classification" and "adolescent" are the central topics in this period. Cooperation and communication between countries/regions need to be enhanced in future research. A shift is taking place in the research hotspot from “Alzheimer's Disease”, “schizophrenia”, “Mild Cognitive Impairment” and “cortex” to “artificial intelligence”, “deep learning”, “machine learning”, “facial expression”, “functional magnetic resonance”, “young-children”. Machine learning applications for ASD diagnosis should be the future development direction.