Deep-learning-based seizure detection and prediction from electroencephalography signals.
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| Title: | Deep-learning-based seizure detection and prediction from electroencephalography signals. |
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| Authors: | Ibrahim FE; Department of Electronics and Electrical Communications Engineering, Faculty of Electronic Engineering, Menoufia University, Menouf, Egypt., Emara HM; Department of Electronics and Electrical Communications Engineering, Faculty of Electronic Engineering, Menoufia University, Menouf, Egypt., El-Shafai W; Department of Electronics and Electrical Communications Engineering, Faculty of Electronic Engineering, Menoufia University, Menouf, Egypt.; Security Engineering Lab, Computer Science Department, Prince Sultan University, Riyadh, Saudi Arabia., Elwekeil M; Department of Electronics and Electrical Communications Engineering, Faculty of Electronic Engineering, Menoufia University, Menouf, Egypt.; Department of Electrical and Information Engineering (DIEI), University of Cassino and Southern Lazio, Cassino, 03043, Italy., Rihan M; Department of Electronics and Electrical Communications Engineering, Faculty of Electronic Engineering, Menoufia University, Menouf, Egypt.; Department of Electrical and Information Engineering (DIEI), University of Cassino and Southern Lazio, Cassino, 03043, Italy., Eldokany IM; Department of Electronics and Electrical Communications Engineering, Faculty of Electronic Engineering, Menoufia University, Menouf, Egypt., Taha TE; Department of Electronics and Electrical Communications Engineering, Faculty of Electronic Engineering, Menoufia University, Menouf, Egypt., El-Fishawy AS; Department of Electronics and Electrical Communications Engineering, Faculty of Electronic Engineering, Menoufia University, Menouf, Egypt., El-Rabaie EM; Department of Electronics and Electrical Communications Engineering, Faculty of Electronic Engineering, Menoufia University, Menouf, Egypt., Abdellatef E; Delta Higher Institute for Engineering and Technology (DHIET), Mansoura, Egypt., Abd El-Samie FE; Department of Electronics and Electrical Communications Engineering, Faculty of Electronic Engineering, Menoufia University, Menouf, Egypt.; Department of Information Technology, College of Computer and Information sciences, Princess Nourah Bint Abdulrahman University, Riyadh, Saudi Arabia. |
| Source: | International journal for numerical methods in biomedical engineering [Int J Numer Method Biomed Eng] 2022 Jun; Vol. 38 (6), pp. e3573. Date of Electronic Publication: 2022 May 13. |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Wiley Country of Publication: England NLM ID: 101530293 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 2040-7947 (Electronic) Linking ISSN: 20407939 NLM ISO Abbreviation: Int J Numer Method Biomed Eng Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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| ISSN: | 2040-7947 |
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| DOI: | 10.1002/cnm.3573 |
