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Will Two Do? Varying Dimensions in Electrocardiography: The PhysioNet/Computing in Cardiology Challenge 2021

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DataCite Commons2022-01-20 更新2025-04-16 收录
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https://physionet.org/content/challenge-2021/1.0.0/
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The electrocardiogram (ECG) is a non-invasive representation of the electrical activity of the heart. Although the twelve-lead ECG is the standard diagnostic screening system for many cardiological issues, the limited accessibility of twelve-lead ECG devices provides a rationale for smaller, lower-cost, and easier to use devices. While single-lead ECGs are limiting, reduced-lead ECG systems hold promise, with evidence that subsets of the standard twelve leads can capture useful information and can even be comparable to twelve-lead ECGs in some limited contexts. In 2017 we challenged the public to classify AF from a single-lead ECG, and in 2020 we challenged the public to diagnose a much larger number of cardiac problems using twelve-lead recordings. However, there is limited evidence to demonstrate the utility of reduced-lead ECGs for capturing a wide range of diagnostic information. In this year's Challenge, we ask the following question: 'Will two do?' This year's Challenge builds on last year's Challenge, which asked participants to classify cardiac abnormalities from twelve-lead ECGs. We are asking you to build an algorithm that can classify cardiac abnormalities from either twelve- lead, six-lead, and two-lead ECGs. We will test each algorithm on databases of twelve-lead, six-lead and two-lead ECGs, and the differences in performances of the algorithms on these databases will reveal the utility of two-lead or six-lead ECGs in comparison to standard twelve-lead EGCs.
提供机构:
PhysioNet
创建时间:
2020-12-24
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