Machine learning of clinical phenotypes facilitates autism screening and identifies novel subgroups with distinct transcriptomic profiles

Machine learning of clinical phenotypes facilitates autism screening and identifies novel subgroups with distinct transcriptomic profiles

Abstract Autism spectrum disorder (ASD) presents significant challenges in diagnosis and intervention due to its diverse clinical manifestations and underlying biological complexity. This study explored machine learning approaches to enhance ASD screening accuracy and identify meaningful subtypes us...

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Main Authors: Wasana Yuwattana, Thanit Saeliw, Marlieke Lisanne van Erp, Chayanit Poolcharoen, Songphon Kanlayaprasit, Pon Trairatvorakul, Weerasak Chonchaiya, Valerie W. Hu, Tewarit Sarachana
Format: Article
Language:English
Published: Nature Portfolio 2025-04-01
Series:Scientific Reports
Subjects:
Autism spectrum disorder
Artificial intelligence
Machine learning
Screening
Subgrouping
Autism diagnostic interview-revised
Online Access:https://doi.org/10.1038/s41598-025-95291-5
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https://doi.org/10.1038/s41598-025-95291-5

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