An interpretable machine learning model for predicting febrile seizures following enterovirus infection in children.
发表日期: 2026-12-01
Annals of medicine
Medical Digest 收录日: 2026-07-11
This study developed an interpretable machine learning model using the XGBoost algorithm to predict the risk of febrile seizures (FS) in children with enterovirus infections. In a cohort of 446 hospitalized children, the model achieved a training set AUC of 0.972 and an internal validation AUC of...
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