Novel genetic ensembles of classifiers applied to myocardium dysfunction recognition based on ECG signals

The best genetic ensemble of classifiers optimized by sets, obtained a classification sensitivity of 17 heart disorders (classes) at a level of 91.40% (64 errors per 744 classifications, accuracy = 98.99%, specificity = 99.46%, time for classification of one sample = 0.0186 [s]). Against the background of the current scientific literature, these results represent some of the best results obtained.