Health Psychology Research / HPR / Volume 12 / Issue 1 / DOI: 10.52965/​001c.125844
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Advances in Autism: a bibliometric analysis

Mehereen Chowdhury1 Murdoc Gould2
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1 University of Central Florida, University of Central Florida
2 Birkbeck, University of London
Submitted: 12 September 2024 | Accepted: 4 October 2024 | Published: 22 November 2024
© 2024 by the Author(s). Licensee Health Psychology Research, USA. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution -Noncommercial 4.0 International License (CC BY-NC 4.0) ( https://creativecommons.org/licenses/by-nc/4.0/ )
Abstract

This paper provides a comprehensive overview of AI treatment research for Autism Spectrum Disorder (ASD) from 2007 to 2023, focusing on global contributions across countries, institutions, authors, and keywords. The United States leads with 164 documents and 4988 citations, highlighting its central role in advancing AI technologies for ASD therapies, followed by significant contributions from China (90 documents, 1190 citations) and India (65 documents, 564 citations). Institutions like Stanford University and McGill University demonstrate substantial research output, while authors such as Dennis Wall are prominent with contributions that make diagnosing Autism much more efficient with the use of AI. Keywords like “Machine learning”, “Autism spectrum disorder”, and “Children” dominate, reflecting ongoing efforts to leverage technology for ASD interventions. Overall, this analysis underscores a dynamic global effort to enhance ASD treatment methodologies through collaborative research and technological innovations.

Keywords
Autism
Bibliometric analysis
References

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Conflict of interest
None of the authors have any conflicts of interest.
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Health Psychology Research, Electronic ISSN: 2420-8124 Published by Health Psychology Research