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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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January 9, 2025: The NIH-funded George B. Moody PhysioNet Challenge 2025 is now open! Please read this website for details and share questions and comments on Challenge forum. This year's Challenge is generously sponsored by MathWorks.
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September 20, 2024: We have released (and updated) the results of the 2024 Challenge. Congratulations to the winners! Please see the announcement for more details.
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... see previous news articles here.
- 2024: Digitization and Classification of ECG Images: The George B. Moody PhysioNet Challenge 2024
Paper and contributed software collection ongoing - 2023: Predicting Neurological Recovery from Coma After Cardiac Arrest
Paper and contributed software collection ongoing - 2022: Heart Murmur Detection from Phonocardiogram Recordings
44+ papers and 77 contributed software - 2021: Will Two Do? Varying Dimensions in Electrocardiography
60+ papers and 58 contributed software - 2020: Classification of 12-lead ECGs
62+ papers and 70 contributed software - 2019: Early Prediction of Sepsis from Clinical Data
55+ papers and 91 contributed software - 2018: You Snooze, You Win
23 papers and 19 contributed software - 2017: AF Classification from a Short Single Lead ECG Recording
57 papers and 64 contributed software - 2016: Classification of Normal/Abnormal Heart Sound Recordings
11 papers and 48 contributed software - 2015: Reducing False Arrhythmia Alarms in the ICU
20 papers and 28 contributed software - 2014: Robust Detection of Heart Beats in Multimodal Data
15 papers and 35 contributed software - 2013: Noninvasive Fetal ECG
29 papers and 17 contributed software - 2012: Predicting Mortality of ICU Patients
17 papers and 58 contributed software - 2011: Improving the Quality of ECGs Collected using Mobile Phones
17 papers and 7 contributed software - 2010: Mind the Gap
13 papers and 5 contributed software - 2009: Predicting Acute Hypotensive Episodes
11 papers and 4 contributed software - 2008: Detecting and Quantifying T-Wave Alternans
19 papers and 5 + 1 contributed software - 2007: Electrocardiographic Imaging of Myocardial Infarction
6 papers - 2006: QT Interval Measurement
20 papers and 6 contributed software - 2005: The First Five Challenges Revisited
5 papers - 2004: Spontaneous Termination of Atrial Fibrillation
12 papers and 1 contributed software - 2003: Distinguishing Ischemic from Non-Ischemic ST Changes 3 papers and 1 contributed software
- 2002: RR Interval Time Series Modeling
12 papers and 10 contributed software - 2001: Predicting Paroxysmal Atrial Fibrillation
9 papers - 2000: Detecting Sleep Apnea from the ECG
13 papers and 1 contributed software