Summary, originally published by The Lancet
Researchers have demonstrated that deep learning models can help neurologists interpret epileptic episodes during and between seizures from relatively few scalp electroencephalography (EEG) readings.
The best of the models proved out the concept under review: an automated annotation tool needing 142 times less EEG data than human experts would need to comb through—and epilepsy patients would need to log—using digital disease diaries.
The researchers, from IBM in collaboration with Temple University and other academic centers, worked with 87 scientists and software engineers from 14 research centers around the world to develop the models.