Autism screening: an unsupervised machine learning approach-Reference-Cited by-同舟云学术

Autism screening: an unsupervised machine learning approach

Published:2022-09-08 Issue:1 Volume:10 Page:
ISSN:2047-2501
Container-title:Health Information Science and Systems
language:en
Short-container-title:Health Inf Sci Syst

Author:

Thabtah Fadi^ORCID,Spencer Robinson,Abdelhamid Neda,Kamalov Firuz,Wentzel Carl,Ye Yongsheng,Dayara Thanu

Publisher

Springer Science and Business Media LLC

Subject

General Medicine

Link

https://link.springer.com/content/pdf/10.1007/s13755-022-00191-x.pdf

Reference53 articles.

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2. Alahmari F. A comparison of resampling techniques for medical data using machine learning. J Inform Knowl Manag. 2020;19(1):2040016. https://doi.org/10.1142/S021964922040016X.

3. Allaire, J. RStudio: Integrated development environment for R 2012. http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.651.1157&rep=rep1&type=pdf#page=14

4. Allison C, Auyeung B, Baron-Cohen S. Toward brief “red flags” for autism screening: The short autism spectrum quotient and the short quantitative checklist in 1,000 cases and 3,000 controls. J Am Acad Child Adolesc Psychiatry. 2012;51(2):202–12. https://doi.org/10.1016/j.jaac.2011.11.003.

5. Allison C, Baron-Cohen S, Wheelwright S, Charman R, Pasco J, Brayne G. The Q-CHAT (Quantitative Checklist for Autism in Toddlers): A normally distributed quantitative measure of autistic traits at 18–24 months of age: Preliminary report. J Autism Dev Disord. 2008;38(8):1414–25. https://doi.org/10.1007/s10803-007-0509-7.

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