A Self-Interpretable Deep Learning Model for Seizure Prediction Using a Multi-Scale Prototypical Part Network

A Self-Interpretable Deep Learning Model for Seizure Prediction Using a Multi-Scale Prototypical Part Network

The epileptic seizure prediction (ESP) method aims to timely forecast the occurrence of seizures, which is crucial to improving patients’ quality of life. Many deep learning-based methods have been developed to tackle this issue and achieve significant progress in recent years. However, t...

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Bibliographic Details
Main Authors: Yikai Gao, Aiping Liu, Lanlan Wang, Ruobing Qian, Xun Chen
Format: Article
Language:English
Published: IEEE 2023-01-01
Series:IEEE Transactions on Neural Systems and Rehabilitation Engineering
Subjects:
Deep learning
interpretability
signal processing
seizure prediction
electroencephalography
Online Access:https://ieeexplore.ieee.org/document/10078917/

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