Predicting response to neuromodulation therapies in drug-resistant epilepsy using machine learning models: a meta-analysis and systematic review (opens in new tab)
This meta-analysis and systematic review aimed to identify and analyze all relevant literature regarding the use of machine learning to predict response to neuromodulation therapies in patients with drug-resistant epilepsy. A total of 4,451 studies were identified after the initial search, from which only 12 papers were included in the final analysis. The study suggests that multimodal ML approaches show promising performance in predicting response to neuromodulation strategies in patients with drug-resistant epilepsy. However, the limited number of studies, scarcity of external validation, and small cohorts highlight the need for larger, high-quality prospective investigations to confirm findings and improve generalizability of ML-based prediction models.