Role of AI/ML in the Study of Autism Spectrum Disorders: A Bibliometric Analysis
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Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s41347-024-00397-8.pdf
Reference54 articles.
1. Alex, M., Pagnozzi, E., Conti, S., Calderoni, J. F., Stephen, E., & Rose. (2018). A systematic review of structural MRI biomarkers in autism spectrum disorder: A machine learning perspective. International Journal of Developmental Neuroscience, 71, 68–82. https://doi.org/10.1016/j.ijdevneu.2018.08.010
2. American Psychiatric Association. (2013). Diagnostic and Statistical Manual of Mental Disorders (5th ed.). American Psychiatric Association.
3. Aria, M., & Cuccurullo, C. (2017). Bibliometrix: An R-tool for comprehensive science mapping analysis. Journal of Informetrics, 11(4), 959–975. https://doi.org/10.1016/j.joi.2017.08.007
4. Baio, J., Wiggins, L., & Christensen, D. L. (2018). Prevalence of Autism Spectrum Disorder Among Children Aged 8 Years — Autism and Developmental Disabilities Monitoring Network, 11 Sites, United States, 2014. MMWR Surveillance Summaries, 67(No. SS-6), 1–23. https://doi.org/10.15585/mmwr.ss6706a1
5. Black, M. H., Kuzminski, R., Wang, J., et al. (2022). Experiences of friendships for individuals on the Autism Spectrum: A scoping review. Review Journal of Autism and Developmental Disorders. https://doi.org/10.1007/s40489-022-00332-8
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