PhysioNet/CinC Challenge 2020 Results

This page contains the final scores for the 2020 PhysioNet/CinC Challenge:

1. The official scores
2. The unofficial scores
3. The metrics per database of the official entries
4. The per-class scoring metrics of the official entries on the validation data

We introduced a new scoring metric for this Challenge. We used this scoring metric to evaluate and rank the Challenge entries. We included several other metrics for reference. The area under the receiver operating characteristic (AUROC), area under the precision recall curve (AUPRC), and F-measure scores are the macro-average of the scores across all classes. The accuracy metric is the fraction of correctly diagnosed recordings, i.e., all classes for the recording are correct. These metrics were computed by the evaluate_12ECG_score.py script. Please see the script for more details of these scores.

We included the scores on the following datasets:

1. Validation Set: Includes recordings from the hidden CPSC and G12EC sets.
2. Hidden CPSC Set: Split between the validation and test sets.
3. Hidden G12EC Set: Split between the validation and test sets.
4. Hidden Undisclosed Set: All recordings were part of the test sets.
5. Test Set: Includes recordings from the hidden CPSC, G12EC, and undisclosed test sets.

To refer to these tables in a publication, please cite Perez Alday EA, Gu A, Shah AJ, Robichaux C, Wong AI, Liu C, Liu F, Rad AB, Elola A, Seyedi S, Li Q, Sharma A, Clifford GD^*, Reyna MA^*. Classification of 12-lead ECGs: the PhysioNet/Computing in Cardiology Challenge 2020. Physiol Meas. 41 (2020). doi: 10.1088/1361-6579/abc960.

In these tables, you can find the following information:

1. Official entries that were scored on the validation and test data and ranked in the Challenge: physionet_2020_official_scores.csv
2. Unofficial entries that were scored on the validation and test data but unranked because they did not satisfy all of the rules or were unsuccessful on one or more of the test sets: physionet_2020_unofficial_scores.csv
3. Challenge and other scoring metrics on all official entries broken with scores for each database in the validation and test data: physionet_2020_metrics_perDatabase_official_entries.csv
4. Per-class scoring metrics on the validation data: physionet_2020_validation_metrics_by_class_official_entries.csv

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Supported by the National Institute of Biomedical Imaging and Bioengineering (NIBIB) under NIH grant number R01EB030362.

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