Artificial Intelligence and Machine Learning in Autism Detection: From Common to Rare Disorders
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Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-97-2550-2_38
Reference31 articles.
1. Jashar DT, Brennan LA, Barton ML, Fein D (2016) Cognitive and adaptive skills in toddlers who meet criteria for Autism in DSM-IV but not DSM-5. J Autism Dev Disord 46(12):3667–3677. https://doi.org/10.1007/s10803-016-2901-7
2. Doernberg E, Hollander E (2016) Neurodevelopmental disorders (ASD and ADHD): DSM-5, ICD-10, and ICD-11. CNS Spectr 21(4):295–299. https://doi.org/10.1017/S1092852916000262
3. Margaret M, Marc T (2016) Severity of Autism spectrum disorders: current conceptualization, and transition to DSM-5. J Autism and Developm Disorders 46. https://doi.org/10.1007/s10803-016-2731-7
4. Omri M, Mor P, Steven B, Stephen G, Edwin C, Russ A (2015) An ontology for Autism spectrum disorder (ASD) to infer ASD phenotypes from Autism diagnostic interview-revised data. J Biomed Informat 56. https://doi.org/10.1016/j.jbi.2015.06.026
5. Mazurek MO, Dovgan K, Neumeyer AM, Malow BA (2019) Course and predictors of sleep and co-occurring problems in children with autism spectrum disorder. J Autism Dev Disord 49(5):2101–2115. https://doi.org/10.1007/s10803-019-03894-5. PMID: 30684086
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