Machine Learning Prediction of Autism Spectrum Disorder from a Minimal Set of Medical and Background Information
Importance: Early identification of the likelihood of autism spectrum disorder (ASD) using minimal information is crucial for early diagnosis and intervention, which can affect developmental outcomes. Objective: To develop and validate a machine learning (ML) model for predicting ASD using a minimal set of features from background and medical information and to evaluate the predictors and the util
