Myocardial infarction detection on PTB dataset, ECG lead II

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Accuracy

Rank	Model	Accuracy	Paper	Code	Year
1	ConvNetQuake	99.43%	Deep Learning for Cardiologist-level Myocardial Infarction Detection in Electrocardiograms	arjung128/mi_detection	2019
2	Deep residual CNN	95.9%	ECG Heartbeat Classification: A Deep Transferable Representation	CVxTz/ECG_Heartbeat_Classification · dave-fernandes/ECGClassifier · mmontana/ECG-heartbeat-classification · +10	2018
3	T-wave + Total Integral	94.7%	A New Pattern Recognition Method for Detection and Localization of Myocardial Infarction Using T-Wave Integral and Total Integral as Extracted Features from One Cycle of ECG Signal		2014
4	CNN	93.5%	Application of deep convolutional neural network for automated detection of myocardial infarction using ecg signals		2017
5	ConvNetQuake	99.43%	Deep Learning for Cardiologist-level Myocardial Infarction Detection in Electrocardiograms	arjung128/mi_detection	2019
6	Deep residual CNN	95.9%	ECG Heartbeat Classification: A Deep Transferable Representation	CVxTz/ECG_Heartbeat_Classification · dave-fernandes/ECGClassifier · mmontana/ECG-heartbeat-classification · +10	2018
7	T-wave + Total Integral	94.7%	A New Pattern Recognition Method for Detection and Localization of Myocardial Infarction Using T-Wave Integral and Total Integral as Extracted Features from One Cycle of ECG Signal		2014
8	CNN	93.5%	Application of deep convolutional neural network for automated detection of myocardial infarction using ecg signals		2017