Predicting autism spectrum disorder severity in children based on specific language milestones: a random forest model approach.

ABSTRACT:

Background

Language impairments are among the most prevalent co-occurring conditions in children with autism spectrum disorder (ASD), and delayed language milestones often serve as early developmental warning signs. However, it remains unclear whether specific language milestones can reliably predict the severity of ASD symptoms, particularly in regions where there is a long delay between initial screening and formal diagnosis.

Methods

This study included 574 children diagnosed with ASD, stratified into two age groups: under 4 years (n = 288) and 4 years or above (n = 286). A total of 33 language milestone items covering receptive, expressive, and pragmatic aspects were evaluated. The Boruta algorithm was applied to identify significant predictors of symptom severity, and ra

SUBMITTER: Xiong H 

PROVIDER: S-EPMC12625304 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature