Machine Learning Predicts Epileptogenic Activity from High-Frequency Oscillation Rates
In an innovative study, researchers from HSE University, RAN Institute of Linguistics, and the National Medical and Surgical Centre named after N.I. Pirogov measured and analysed high-frequency oscillations (HFO) in different regions of the brain. An automated detector predicted seizure outcomes based on HFO rates with an accuracy rate of 85%, and by applying machine learning, made it possible to distinguish between epileptogenic and non-epileptogenic HFO. The study’s findings are published in Frontiers in Human Neurosciences.
14 November
2022