George B. Moody PhysioNet Challenges

For the past 26 years, PhysioNet and Computing in Cardiology have co-hosted a series of annual challenges, now called the George B. Moody PhysioNet Challenges, to tackle clinically interesting but unsolved questions.

The George B. Moody PhysioNet Challenge 2025 invites teams to develop algorithms for detecting Chagas disease from electrocardiograms (ECGs). Chagas disease is a parasitic disease in Central and South America that affects an estimated 6.5 million people and causes nearly 10,000 deaths annually. Timely treatment may prevent or slow damage to the cardiovascular system, but serological testing capacity is limited, so detection through ECGs can help to identify Chagas patients for testing and treatment. We ask participants to design and implement working, open-source algorithms that, based only on the provided ECGs, prioritize patients for testing. The teams with the best scores for these tasks on the hidden test set win the Challenge.

Please check the below links for information about current and past Challenges, including important details about scoring and test data for previous Challenges.

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Current Challenge

Past Challenges

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

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