Multimodal machine learning for surgical decision support in epilepsy: Current evidence and translational gaps

ML shows promise for outcome prediction and presurgical decision support in DRE, particularly when integrating multimodal data. Translation is currently constrained by limited external and prospective validation, inconsistent outcome frameworks, and insufficient interpretability. Future research should prioritize harmonized endpoints, multicenter external validation (including federated approaches), and explainable models capable of informing both patient selection and surgical strategy.