Papers › Multi-Label ECG Classification Using Convolutional Neural Networks in a Classifier Chain
Multi-Label ECG Classification Using Convolutional Neural Networks in a Classifier Chain
Bjørn-Jostein Singstad, Eraraya Morenzo Muten, Pål Haugar Brekke
Over the last decade, AI has shown its feasibility in classifying heart-related diagnoses from ECGs. Earlier studies have mainly focused on 12 and 2-lead ECGs, but we aim to classify 26 different diagnoses based on 12, 6, 4, 3, and 2-lead ECGs in this study. We trained a supervised model on a dataset containing 88 253 ECGs with 26 different diagnoses used as ground truth. The training and classification steps can be separated into three parts. (1) Pan Tompkins algorithm was used to find peaks and calculate the average heart rate. (2) The average heart rate and the Fourier transformed ECG signal was used to train convolutional neural networks (CNN) system that classified the ECGs with regular or irregular rhythms. 9 out of 26 classes were classified in this step. (3) Finally, CNN models in a classifier chain were trained to classify the remaining 17 diagnoses. The classification results from step 2 and the raw ECG signal were used as input to the classifier chain in step 3. Our team, CardiOUS, achieved a PhysioNet Challenge score of −0.63 for all sets of leads on the hidden test set. Based on the test score, our team placed at 38th out of 39 teams in the official ranking.
Code
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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| ECG Classification | PhysioNet Challenge 2021 | Classifier Chain (6-lead) | PhysioNet Challenge score 2021 | -0.63 | #2 of 5 | Archive leaderboard | report |
| ECG Classification | PhysioNet Challenge 2021 | Classifier Chain (4-lead) | PhysioNet Challenge score 2021 | -0.63 | #3 of 5 | Archive leaderboard | report |
| ECG Classification | PhysioNet Challenge 2021 | Classifier Chain (3-lead) | PhysioNet Challenge score 2021 | -0.60 | #4 of 5 | Archive leaderboard | report |
| ECG Classification | PhysioNet Challenge 2021 | Classifier Chain (2-lead) | PhysioNet Challenge score 2021 | -0.63 | #5 of 5 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
Methods
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