Resources
Challenge Open Access
Spontaneous Termination of Atrial Fibrillation: The PhysioNet/Computing in Cardiology Challenge 2004
The fifth annual PhysioNet/Computers in Cardiology Challenge focusses on this question: Is it possible to predict if (or when) an episode of atrial fibrillation will end spontaneously?
challenge atrial fibrillation ecg
Published: Oct. 8, 2004. Version: 1.0.0
Database Open Access
AF Termination Challenge Database
challenge atrial fibrillation ecg
Published: April 11, 2004. Version: 1.0.0
Visualize waveformsChallenge Open Access
Distinguishing Ischemic from Non-Ischemic ST Changes: The PhysioNet/Computing in Cardiology Challenge 2003
For the fourth annual PhysioNet/Computers in Cardiology Challenge, we propose a provocative question of considerable clinical interest: Is it possible to tell the difference between transient ST changes in the ECG that are due to myocardial ischemia…
Published: March 6, 2003. Version: 1.0.0
Challenge Open Access
Detecting and Quantifying Apnea Based on the ECG: The PhysioNet/Computing in Cardiology Challenge 2000
Obstructive sleep apnea (intermittent cessation of breathing) is a common problem with major health implications, ranging from excessive daytime drowsiness to serious cardiac arrhythmias. Obstructive sleep apnea is associated with increased risks of…
Published: Feb. 10, 2000. Version: 1.0.0
Challenge Open Access
Classification of 12-lead ECGs: The PhysioNet/Computing in Cardiology Challenge 2020
Erick Andres Perez Alday, Annie Gu, Amit Shah, Chengyu Liu, Ashish Sharma, Salman Seyedi, Ali Bahrami Rad, Matthew Reyna, Gari Clifford
Published: July 29, 2022. Version: 1.0.2
Visualize waveformsChallenge Open Access
Paroxysmal Atrial Fibrillation Events Detection from Dynamic ECG Recordings: The 4th China Physiological Signal Challenge 2021
Xingyao Wang, Caiyun Ma, Xiangyu Zhang, Hongxiang Gao, Gari D. Clifford, Chengyu Liu
event detection paroxysmal atrial fibrillation
Published: June 21, 2021. Version: 1.0.0
Visualize waveformsChallenge Open Access
Early Prediction of Sepsis from Clinical Data: The PhysioNet/Computing in Cardiology Challenge 2019
Matthew Reyna, Chris Josef, Russell Jeter, Supreeth Shashikumar, Benjamin Moody, M. Brandon Westover, Ashish Sharma, Shamim Nemati, Gari D. Clifford
Published: Aug. 5, 2019. Version: 1.0.0
Challenge Open Access
You Snooze You Win: The PhysioNet/Computing in Cardiology Challenge 2018
The goal of the challenge is use information from the available signals to correctly classify target arousal regions.
apnea circadian sleep challenge polysomnography
Published: Feb. 21, 2018. Version: 1.0.0
Challenge Open Access
AF Classification from a Short Single Lead ECG Recording: The PhysioNet/Computing in Cardiology Challenge 2017
The 2017 PhysioNet/CinC Challenge aims to encourage the development of algorithms to classify, from a single short ECG lead recording (between 30 s and 60 s in length), whether the recording shows normal sinus rhythm, atrial fibrillation (AF), an al…
challenge atrial fibrillation ecg
Published: Feb. 1, 2017. Version: 1.0.0
Challenge Open Access
Classification of Heart Sound Recordings: The PhysioNet/Computing in Cardiology Challenge 2016
The 2016 PhysioNet/CinC Challenge aims to encourage the development of algorithms to classify heart sound recordings collected from a variety of clinical or nonclinical (such as in-home visits) environments. The aim is to identify, from a single sho…
sound heart challenge phonocardiogram
Published: March 4, 2016. Version: 1.0.0