A Self-Interpretable Deep Learning Model for Seizure Prediction Using a Multi-Scale Prototypical Part Network-Reference-Cited by-同舟云学术

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

Published:2023 Issue: Volume:31 Page:1847-1856
ISSN:1534-4320
Container-title:IEEE Transactions on Neural Systems and Rehabilitation Engineering
language:
Short-container-title:IEEE Trans. Neural Syst. Rehabil. Eng.

Author:

Gao Yikai¹^ORCID,Liu Aiping¹^ORCID,Wang Lanlan²,Qian Ruobing²,Chen Xun³^ORCID

Affiliation:

1. School of Information Science and Technology, University of Science and Technology of China (USTC), Hefei, China

2. Department of Neurosurgery, Epilepsy Center, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Anhui, Hefei, China

3. Department of Neurosurgery, Department of Electronic Engineering and Information Science, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China

Funder

National Natural Science Foundation of China

Research Project of Health Commission of Anhui Province

Fundamental Research Funds for the Central Universities

University Synergy Innovation Program of Anhui Province

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Biomedical Engineering,General Neuroscience,Internal Medicine,Rehabilitation

Link

http://xplorestaging.ieee.org/ielx7/7333/10031624/10078917.pdf?arnumber=10078917

Reference38 articles.