An interpretable machine learning approach for predicting drug-resistant epilepsy in children with tuberous sclerosis complex

An interpretable machine learning approach for predicting drug-resistant epilepsy in children with tuberous sclerosis complex

BackgroundThis study developed and validated an interpretable machine learning (ML) algorithm for predicting the risk of drug-resistant epilepsy (DRE) in children with Tuberous sclerosis (TSC).MethodsTo estimate the risk of DRE in pediatric TSC patients, an interpretable ML model was developed and v...

Full description

Saved in:
Bibliographic Details
Main Authors: Jie Fu, Genfu Zhang, Zhixian Yang, Jiong Qin
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-08-01
Series:Frontiers in Neurology
Subjects:
machine learning
model interpretability
predictive model
tuberous sclerosis complex
drug-resistant epilepsy
Online Access:https://www.frontiersin.org/articles/10.3389/fneur.2025.1623212/full
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://www.frontiersin.org/articles/10.3389/fneur.2025.1623212/full

Similar Items