Exploring the Applicability of Transfer Learning and Feature Engineering in Epilepsy Prediction Using Hybrid Transformer Model
Author:
Affiliation:
1. Center for Biomedical Engineering, School of Information Science and Technology, Fudan University, Shanghai, China
2. Xinghua City People’s Hospital, Jiangsu, China
Funder
Shanghai Municipal Science and Technology
Shanghai Science and Technology
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Biomedical Engineering,General Neuroscience,Internal Medicine,Rehabilitation
Link
http://xplorestaging.ieee.org/ielx7/7333/10031624/10046136.pdf?arnumber=10046136
Reference39 articles.
1. Deep learning;lecun;Nature,2015
2. A Hybrid Transformer Model for Obstructive Sleep Apnea Detection Based on Self-Attention Mechanism Using Single-Lead ECG
3. Predicting Epileptic Seizures in Scalp EEG Based on a Variational Bayesian Gaussian Mixture Model of Zero-Crossing Intervals
4. Seizure prediction in patients with focal hippocampal epilepsy
5. Seizure Prediction Using Directed Transfer Function and Convolution Neural Network on Intracranial EEG
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