Profiles of autism characteristics in thirteen genetic syndromes: a machine learning approach
Bozhilova, Natali
Background Phenotypic studies have identified distinct patterns of autistic characteristics in genetic syndromes associated with intellectual disability (ID), leading to diagnostic uncertainty and compromised access to autism-related support. Previous research has tended to include small samples and diverse measures, which limits the generalisability of findings. In this study, we generated detailed profiles of autistic characteristics in a large sample of > 1500 individuals with rare genetic syndromes.
Additional Details
Publisher: Springer Nature
Contributors: Welham, Alice & Adams, Dawn & Bissell, Stacey & Bruining, Hilgo & Crawford, Hayley & Eden, Kate & Nelson, Lisa & Oliver, Chris & Powis, Laurie & Richards, Caroline & Waite, Jane & Watson, Peter & Rhys, Hefin & Wilde, Lucy & Woodcock, Kate & Moss, Joanna
Date: January 10, 2025
Identifier: 9a216ad4-4eb2-4cf5-8b2c-cec09e53bb92
Date: January 10, 2025
Text EnglishAdditional Information
Relation: 2040-2392
Rights: The Author(s) 2023. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License. https://www.researchgate.net/deref/https%3A%2F%2Fcreativecommons.org%2Flicenses%2Fby%2F4.0%2F
Bibliographic Citation: Bozhilova, Natali and Welham, Alice & Adams, Dawn & Bissell, Stacey & Bruining, Hilgo & Crawford, Hayley & Eden, Kate & Nelson, Lisa & Oliver, Chris & Powis, Laurie & Richards, Caroline & Waite, Jane & Watson, Peter & Rhys, Hefin & Wilde, Lucy & Woodcock, Kate & Moss, Joanna. (2023). Profiles of autism characteristics in thirteen genetic syndromes: a machine learning approach. Molecular Autism. 14. 10.1186/s13229-022-00530-5.
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