Missing Value Estimation Methods for Classification of Arrhythmia using Deep Learning: Review Study
This paper discusses the various learning approaches for automatically distinguishing different types of heartbeats. According to reported studies, the CNN model is the best option for classifying arrhythmia. An ensemble of DSC neural networks achieves the highest classification accuracy, 99.88%.
