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机译:使用基于规则的分类器通过脑电图检测癫痫
Hong Kong Polytech Univ, Sch Nursing, Hong Kong, Hong Kong, Peoples R China|Hong Kong Polytech Univ, Sch Nursing, Ctr Smart Hlth, Hong Kong, Hong Kong, Peoples R China;
Jiangnan Univ, Sch Digital Media, Wuxi, Jiangsu, Peoples R China;
Hong Kong Polytech Univ, Sch Nursing, Hong Kong, Hong Kong, Peoples R China|Hong Kong Polytech Univ, Sch Nursing, Ctr Smart Hlth, Hong Kong, Hong Kong, Peoples R China|Hong Kong Polytech Univ, Interdisciplinary Div Biomed Engn, Hong Kong, Hong Kong, Peoples R China;
Seizure detection; EEG; Random forest; SVM; Ensemble learning approach;
机译:使用BAT-SVM分类器进行分类脑电图(EEG)信号进行检测癫痫
机译:使用来自脑电图信号的修改稀疏表示分类器和朴素贝叶斯分类器的癫痫分类框架
机译:高效的自动癫痫发作检测算法,可使用某些后期分类器根据脑电信号对癫痫病进行分类
机译:使用小波变换和K近邻法对癫痫和正常脑电图(EEG)信号进行分类
机译:无症状的癫痫患者亲属中异常脑电图的频率:系统评价和荟萃分析
机译:Ciruvis:基于规则的分类器的基于Web的规则网络和交互检测工具
机译:使用基于规则的分类器通过脑电图检测癫痫