Development of a Novel Telemedicine Tool to Reduce Disparities Related to the Identification of Preschool Children with Autism
Author:
Funder
NIMH
Publisher
Springer Science and Business Media LLC
Subject
Developmental and Educational Psychology
Link
https://link.springer.com/content/pdf/10.1007/s10803-023-06176-3.pdf
Reference39 articles.
1. Bishop, C. M. (2006). Pattern recognition and machine learning, Springer.
2. Bishop-Fitzpatrick, L., & Kind, A. J. H. (2017). A Scoping review of health disparities in autism spectrum disorder. Journal of Autism and Developmental Disorders, 47(11), 3380–3391. https://doi.org/10.1007/s10803-017-3251-9
3. Bone, D., Goodwin, M. S., Black, M. P., Lee, C. C., Audhkhasi, K., & Narayanan, S. (2015). Applying machine learning to facilitate autism diagnostics: Pitfalls and promises. Journal of Autism and Developmental Disorders, 45(5), 1121–1136. https://doi.org/10.1007/s10803-014-2268-6
4. Chlebowski, C., Robins, D. L., Barton, M. L., & Fein, D. (2013). Large-scale use of the modified checklist for autism in low-risk toddlers. Pediatrics, 131(4), e1121–e1127. https://doi.org/10.1542/peds.2012-1525
5. Chunara, R., Zhao, Y., Chen, J., Lawrence, K., Testa, P. A., Nov, O., & Mann, D. M. (2021). Telemedicine and healthcare disparities: A cohort study in a large healthcare system in New York City during COVID-19. Journal of the American Medical Informatics Association: JAMIA, 28(1), 33–41. https://doi.org/10.1093/jamia/ocaa217
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