Seizure Forecasting from Subcutaneous EEG Using Long Short Term Memory Neural Networks: Algorithm Development and Optimization
Author:
Funder
Epilepsy Foundation
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9669261/9669139/09669843.pdf?arnumber=9669843
Reference26 articles.
1. Seizure Diaries and Forecasting With Wearables: Epilepsy Monitoring Outside the Clinic
2. Under-sampling in epilepsy: Limitations of conventional EEG;baud;Clin Neurophysiol Pract,2020
3. A new era in electroencephalographic monitoring? Subscalp devices for ultra–long?term recordings;duun?henriksen;Epilepsia,2020
4. 230 days of ultra long?term subcutaneous EEG: seizure cycle analysis and comparison to patient diary;viana;Annals of Clinical and Translational Neurology,2021
5. Forecasting seizure risk in adults with focal epilepsy: a development and validation study
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1. Automated algorithms for seizure forecast: a systematic review and meta-analysis;Journal of Neurology;2024-09-06
2. A Long Short-Term Memory Network Using Resting-State Electroencephalogram to Predict Outcomes Following Moderate Traumatic Brain Injury;Computers;2023-02-20
3. Shallow Sparse Autoencoder Based Epileptic Seizure Prediction;2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM);2022-12-06
4. Seizure forecasting using minimally invasive, ultra‐long‐term subcutaneous electroencephalography: Individualized intrapatient models;Epilepsia;2022-04-16
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