Myocardial Infarction Detection On Ptb
Metriken
Accuracy
Ergebnisse
Leistungsergebnisse verschiedener Modelle zu diesem Benchmark
Modellname | Accuracy | Paper Title | Repository |
|---|---|---|---|
| CNN | 93.5% | Application of deep convolutional neural network for automated detection of myocardial infarction using ecg signals | - |
| Deep residual CNN | 95.9% | ECG Heartbeat Classification: A Deep Transferable Representation | |
| ConvNetQuake | 99.43% | Deep Learning for Cardiologist-level Myocardial Infarction Detection in Electrocardiograms | |
| 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 | - |
0 of 4 row(s) selected.