@article{380f649234374ac4a62307769b58e0f5,
title = "Seizure forecasting using minimally invasive, ultra-long-term subcutaneous EEG: Generalizable cross-patient models",
keywords = "LSTM neural networks, deep neural networks, epilepsy, machine learning, seizure forecasting, subcutaneous EEG",
author = "\{Pal Attia\}, Tal and Viana, \{Pedro F.\} and Mona Nasseri and Jonas Duun-Henriksen and Andrea Biondi and Winston, \{Joel S.\} and \{P. Martins\}, Isabel and Nurse, \{Ewan S.\} and Matthias D{\"u}mpelmann and Worrell, \{Gregory A.\} and Andreas Schulze-Bonhage and Freestone, \{Dean R.\} and Kjaer, \{Troels W.\} and Brinkmann, \{Benjamin H.\} and Richardson, \{Mark P.\}",
note = "Publisher Copyright: {\textcopyright} 2022 International League Against Epilepsy.",
year = "2023",
month = dec,
doi = "10.1111/epi.17265",
language = "English",
volume = "64",
pages = "S114--S123",
number = "S4",
}