Machine learning applications for electroencephalograph signals in epilepsy:a quick review  被引量:1

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作  者:Yang Si 

机构地区:[1]Department of neurology,Sichuan Academy of Medical Science and Sichuan Provincial People’s Hospital,University of Electronic Science and Technology of China,Chengdu 611731,China

出  处:《Acta Epileptologica》2020年第1期32-38,共7页癫痫学报(英文)

基  金:the National Natural Science Foundation of China(NSFC)(NO.81701269).

摘  要:Machine learning(ML)is a fundamental concept in the field of state-of-the-art artificial intelligence(AI).Over the past two decades,it has evolved rapidly and been employed wildly in many fields.In medicine the widespread usage of ML has been observed in recent years.The present review examines various ML approaches for electroencephalograph(EEG)signal procession in epilepsy research,highlighting applications in the aspect of automated seizure detection,prediction and orientation.The present review also presents advantage,challenge and future direction of ML techniques in the analysis of EEG signals in epilepsy.

关 键 词:Machine learning ELECTROENCEPHALOGRAPH EPILEPSY SEIZURE 

分 类 号:R74[医药卫生—神经病学与精神病学]

 

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