Deep learning based automatic seizure prediction with EEG time-frequency representation-Reference-Cited by-同舟云学术

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Deep learning based automatic seizure prediction with EEG time-frequency representation

Published:2024-09 Issue: Volume:95 Page:106447
ISSN:1746-8094
Container-title:Biomedical Signal Processing and Control
language:en
Short-container-title:Biomedical Signal Processing and Control

Author:

Dong Xingchen,He Landi,Li Haotian,Liu Zhen,Shang Wei,Zhou Weidong

Funder

Shenzhen Science and Technology Innovation Committee

National Natural Science Foundation of China

Shandong Province Natural Science Foundation

Publisher

Elsevier BV

Reference69 articles.

1. Machine learning seizure prediction: one problematic but accepted practice;West;J. Neural Eng.,2023

2. Seizure prediction - ready for a new era;Kuhlmann;Nat. Rev. Neurol.,2018

3. Patient-specific seizure prediction via adder network and supervised contrastive learning;Zhao;IEEE Trans. Neural Syst. Rehabil. Eng.,2022

4. A new epileptic seizure prediction model based on maximal overlap discrete wavelet packet transform, homogeneity index, and machine learning using ECG signals;Perez-Sanchez;Biomed. Signal Process. Control,2024

5. Automated seizure detection systems and their effectiveness for each type of seizure;Ulate-Campos;Seizure,2016

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. EEG-Based Seizure Prediction Using Hybrid DenseNet–ViT Network with Attention Fusion;Brain Sciences;2024-08-21

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