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EpilepsyNet: Novel automated detection of epilepsy using transformer model with EEG signals from 121 patient population.

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第一作者： Oh Shu,Lih

第一单位： Cogninet Australia, Sydney, NSW, 2010, Australia.

作者： Oh Shu,Lih ^[1] ; V,Jahmunah ^[2] ; Elizabeth Emma,Palmer ^[3] ; Prabal D,Barua ^[4] ; Sengul,Dogan ^[5] ; Turker,Tuncer ^[5] ; Salvador,García ^[6] ; Filippo,Molinari ^[7] ; U Rajendra,Acharya ^[8]

作者单位： Cogninet Australia, Sydney, NSW, 2010, Australia. ^[1] School of Engineering, Nanyang Polytechnic, Singapore. ^[2] Centre of Clinical Genetics, Sydney Children's Hospitals Network, Randwick, 2031, Australia; School of Women's and Children's Health, University of New South Wales, Randwick, 2031, Australia. ^[3] School of Business (Information System), University of Southern Queensland, Australia. ^[4] Department of Digital Forensics Engineering, Technology Faculty, Firat University, Elazig, Turkey. ^[5] Andalusian Institute of Data Science and Computational Intelligence, Department of Computer Science and Artificial Intelligence, University of Granada, Spain. ^[6] Biolab, PolitoBIOMedLab, Department of Electronics and Telecommunications, Politecnico di Torino, Turin, Italy. ^[7] School of Mathematics, Physics and Computing, University of Southern Queensland, Springfield, Australia. Electronic address: rajendra.acharya@usq.edu.au. ^[8]

关键词 Automated diagnosis Epilepsy Pearson correlation coefficient Positional encoding Transformer deep model

医学主题词人类(Humans);生活质量(Quality of Life);癫痫(Epilepsy);数据库, 事实型(Databases, Factual);脑电描记术(Electroencephalography)

DOI 10.1016/j.compbiomed.2023.107312

PMID 37597408

发布时间 2023-09-11

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