Importance of methodological choices in data manipulation for validating epileptic seizure detection models-Reference-Cited by-同舟云学术

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Importance of methodological choices in data manipulation for validating epileptic seizure detection models

Published:2023-07-24 Issue: Volume: Page:
ISSN:
Container-title:2023 45th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)
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Author:

Pale Una¹,Teijeiro Tomas¹,Atienza David¹

Affiliation:

1. Ecole Polytechnique Federale de Lausanne (EPFL),Embedded Systems Laboratory (ESL),Switzerland

Funder

National Science Foundation

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10339936/10339939/10340493.pdf?arnumber=10340493

Reference26 articles.

1. EEG-Based Epileptic Seizure Detection via Machine/Deep Learning Approaches: A Systematic Review;ahmad;Computational Intelligence and Neuroscience,2022

2. A review of epileptic seizure detection using machine learning classifiers

3. Standards for testing and clinical validation of seizure detection devices;beniczky;Epilepsia,2018

4. Epileptic Seizures Detection Using Deep Learning Techniques: A Review;shoeibi;International Journal of Environmental Research and Public Health,2021

5. Personalizing Heart Rate-Based Seizure Detection Using Supervised SVM Transfer Learning

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. Epileptic seizure detection using CHB-MIT dataset: The overlooked perspectives;Royal Society Open Science;2024-05

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