An epileptic seizures diagnosis system using feature selection, fuzzy temporal naive Bayes and T-CNN-Reference-Cited by-同舟云学术

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An epileptic seizures diagnosis system using feature selection, fuzzy temporal naive Bayes and T-CNN

Published:2023-03-14 Issue:22 Volume:82 Page:34075-34094
ISSN:1380-7501
Container-title:Multimedia Tools and Applications
language:en
Short-container-title:Multimed Tools Appl

Author:

Srihari P.,Santosh V.,Ganapathy Sannasi

Publisher

Springer Science and Business Media LLC

Subject

Computer Networks and Communications,Hardware and Architecture,Media Technology,Software

Link

https://link.springer.com/content/pdf/10.1007/s11042-023-14928-7.pdf

Reference27 articles.

1. Abdellatif A (2015) A new method for predicting epilepsy seizure. In: 2015 IEEE 4th Portuguese Meeting on Bioengineering (ENBENG), Porto, pp 1–4

2. Almustafa KM (2020) Classification of epileptic seizure dataset using different machine learning algorithms. Inform Med Unlocked 21, Article No.100444:1–7

3. Antoniades A, Spyrou L, Took CC, Sanei S (2016) Deep learning for epileptic intracranial EEG data. In: 2016 IEEE 26th International Workshop on Machine Learning for Signal Processing (MLSP), Vietrisul Mare, pp 1–6

4. Anugraha A, Vinotha E, Anusha R, Giridhar S, Narasimhan K (2017) A machine learning application for epileptic seizure detection. In: 2017 International Conference on Computational Intelligence in Data Science (ICCIDS), Chennai, pp 1–4

5. Cao Y, Guo Y, Yu H, Yu X (2017) Epileptic seizure auto-detection using deep learning method. In: 2017 4th International Conference on Systems and Informatics (ICSAI), Hangzhou, pp 1076–1081

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