Study looks at better prediction for epileptic seizures through adaptive learning approach

UT Arlington assistant professor uses EEG readingsA UT Arlington assistant engineering professor has developed a computational model that can more accurately predict when an epileptic seizure will occur next based on the patient’s personalized medical information. The research conducted by Shouyi Wang, an assistant professor in the Department of Industrial and Manufacturing Systems Engineering , has been in the paper “Online Seizure Prediction Using an Adaptive Learning Approach” in IEEE Transactions on Knowledge and Data Engineering