Dear Challengers,
We are pleased to announce the start of the official phase of the PhysioNet/Computing in Cardiology Challenge 2021: “Will Two Do? Varying Dimensions in Electrocardiography”.
During the unofficial phase, we were heartfelt to receive some very useful public and private comments, and offers of help, which have helped improve the Challenge.
The official phase of this year’s Challenge brings many additions, including new lead combinations, an additional training set with approximately 45,000 twelve-lead ECGs (most of which have never been released before), new test data, updated MATLAB and Python code, and a slightly updated scoring function with additional classes. Due to these many changes, we expect to make several updates or clarifications over the next few days.
New lead combinationsTo better understand the differential utility of reduced-lead ECGs, we have changed our two-lead ECGs and added four-lead ECGs.
Twelve leads: I, II, III, aVR, aVL, aVF, V1, V2, V3, V4, V5, V6
Six leads: I, II, III, aVR, aVL, aVF
Four leads: I, II, III, V2
Three leads: I, II, V2
Two leads: I, II
Please see the
Objective section of the Challenge website for more details.
Thank you to Andrew Walsh, Kim Barnett, Joel Xue and Dave Albert for useful input on this issue.
Expanded training setJianwei Zheng and colleagues generously shared approximately 45,000 twelve-lead ECG recordings from Shaoxing University. A description of these new data can be found in Zheng et al. [1, 2].
With their support, we have added these recordings as an additional training set for this year’s Challenge. These recordings more than double the size of our training set to over 88,000 recordings.
Please see the
Data Sources section of the Challenge website for more details.
Updated MATLAB and Python codeWe have updated our example training and test code in both MATLAB and Python to address your feedback and our observations from the unofficial phase. Most of these changes are minor, but due to the change in lead combinations, we recommend that you download the updated code and test your models using it before submitting your code again.
Please see the
Algorithms section of the Challenge website for more details, including the
MATLAB and
Python code repositories.
Updated scoringWe are updating our scoring function to incorporate the new training data and lead combinations. We plan to release it in the next several days, and we plan to start scoring your submissions again afterwards.
Please see the
Scoring section of the website for more details, including the scoring code
repository.
CinC abstractsYour abstracts are under review, and we expect for you to receive decisions on your abstracts by 1 June 2021. If you do not receive a decision on this date, then please wait or check the
CinC 2021 webpage for updates -- the abstract submission deadline extension may push this date back.
CinC 2021Like last year’s conference,
CinC 2021 will be a hybrid conference with in-person and remote attendance options. Both in-person and remote attendees are eligible to compete in the Challenge, and we look forward to a strong official phase.
Best,
Gari, Matt, Nadi, Erick, and the rest of the Challenge team
https://PhysioNetChallenges.org/https://PhysioNet.org/Please post questions and comments in the forum. However, if your question reveals information about your entry, then please email challenge at
physionet.org. We may post parts of our reply publicly if we feel that all Challengers should benefit from it. We will not answer emails about the Challenge to any other address. This email is maintained by a group. Please do not email us individually.
References [1] Zheng, J., Zhang, J., Danioko, S. et al. A 12-lead electrocardiogram database for arrhythmia research covering more than 10,000 patients. Sci Data 7, 48 (2020).
https://doi.org/10.1038/s41597-020-0386-x(This describes the first 10,000 ECGs in the new data. )
[2] Zheng, J., Chu, H., Struppa, D. et al. Optimal Multi-Stage Arrhythmia Classification Approach. Sci Rep 10, 2898 (2020).
https://doi.org/10.1038/s41598-020-59821-7(This describes an analysis of the data in [1] by the same authors.)