… This study will serve as a basis for prospective clinical trials to … people with epilepsy might
benefit from seizure forecasting over … We developed and validated statistical models to forecast …

… study pursues the second stage of testing of a new quantitative tool for seizure risk evaluation
(Epilepsy Seizure … was commonly compatible with EpiSAT predictions (Figure 4BC). Real …

… to develop a prediction model for risk of seizure recurrence following a first seizure or diagnosis
of epilepsy… Time-to-event data was modelled via Cox's proportional hazards regression. …

… We hypothesized that a multivariate model of clinical features could predict whether an …
whether the seizure type categorizations used in this study may be a proxy for age at onset of …

… of seizure freedom postsurgery. The aim of this study was to develop and validate a
supervised … learning (ML) model for predicting seizure freedom after pediatric epilepsy surgery. …

… antiepileptic drug (AED) withdrawal in adult epilepsy patients include the prediction model …
, our study represents the first adult sample validating prediction models of seizure recurrence …

… study with retrospectively identified cases, a support vector machine classifier was able to
predict seizure … More recently, a study developed both traditional models (ie, linear models and …

… 78%, using this nomogram in the current study to predict PTE risk adds more benefit than the
… for the nomogram to predict PTE risk at 5 year after TBI. PTE = posttraumatic epilepsy, TBI = …

… ML in predicting PSE is still not well understood. The purpose of this study was to develop
prediction … The prediction of post-stroke seizures using ML technology is still in the preliminary …

… The present study constructed an easy-to-use nomogram model to predict the individualized
probabilities of NAME/S. We believe this study is the first attempt to provide a nomogram-…