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Automated detection of shockable ECG signals: A review
journal contribution
posted on 2021-01-01, 00:00 authored by M Hammad, R N V P S Kandala, A Abdelatey, Moloud Abdar, M Zomorodi‐Moghadam, R S Tan, U R Acharya, J Pławiak, R Tadeusiewicz, V Makarenkov, N Sarrafzadegan, Abbas KhosraviAbbas Khosravi, Saeid Nahavandi, A A A EL-Latif, P PławiakAutomated detection of shockable ECG signals: A review
History
Journal
Information SciencesVolume
571Pagination
580 - 604Publisher
ElsevierLocation
Amsterdam, The NetherlandsPublisher DOI
ISSN
0020-0255eISSN
1872-6291Language
EnglishPublication classification
C1 Refereed article in a scholarly journalUsage metrics
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No categories selectedKeywords
ALGORITHMArrhythmiaATRIAL-FIBRILLATIONCLASSIFICATIONComputer ScienceComputer Science, Information SystemsComputer-aided arrhythmia classification (CAAC)CONVOLUTION NEURAL-NETWORKDeep learningDEEP LEARNING APPROACHDIAGNOSISElectrocardiogram (ECG)Ensemble learningFeature extractionFeature selectionMachine learningMODELOptimizationREAL-TIME DETECTIONRECURRENCE PLOTSScience & TechnologySignal processingTechnologyTHREATENING VENTRICULAR-ARRHYTHMIAS
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