Resources


Challenge Open Access

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

Matthew Reyna, Nadi Sadr, Annie Gu, Erick Andres Perez Alday, Chengyu Liu, Salman Seyedi, Amit Shah, Gari Clifford

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

challenge cardiac abnormalities multilead ecgs classification competition

Published: July 29, 2022. Version: 1.0.3

Visualize waveforms

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

The goal of the 2020 PhysioNet - Computing in Cardiology Challenge is to design and implement a working, open-source algorithm that can automatically identify cardiac abnormalities in 12-lead ECG recordings.

Published: July 29, 2022. Version: 1.0.2

Visualize waveforms

Challenge 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

CPSC2021 for paroxysmal atrial fibrillation events detection.

event detection paroxysmal atrial fibrillation

Published: June 21, 2021. Version: 1.0.0

Visualize waveforms

Challenge Restricted Access

WiDS (Women in Data Science) Datathon 2020: ICU Mortality Prediction

Meredith Lee, Jesse Raffa, Marzyeh Ghassemi, Tom Pollard, Sharada Kalanidhi, Omar Badawi, Karen Matthys, Leo Anthony Celi

WiDS (Women in Data Science) Datathon 2020: ICU Mortality Prediction focuses on patient health. Join a team, explore the data, and share your insights: http://bit.ly/WiDSdatathon2020

mortality risk data science kaggle icu challenge predictive analytics women in data science

Published: Jan. 22, 2020. Version: 1.0.0

Challenge 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

The 2019 PhysioNet Computing in Cardiology Challenge invites participants to predict sepsis in clinical data

prediction sepsis challenge

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

2018 IEEE BHI and BSN Data Challenge

Tom Pollard, Alistair Johnson, Jesse Raffa

A challenge to explore real clinical questions in critically ill patients using the MIMIC. A collaboration with the IEEE Conference on Biomedical and Health Informatics 2018 and the IEEE Conference on Body Sensor Networks.

weekend effect ieee mimic challenge

Published: Feb. 5, 2018. Version: 1.0

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…

atrial fibrillation challenge 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…

heart sound challenge phonocardiogram

Published: March 4, 2016. Version: 1.0.0

Challenge Open Access

Reducing False Arrhythmia Alarms in the ICU: The PhysioNet/Computing in Cardiology Challenge 2015

The 2015 PhysioNet/CinC Challenge aims to encourage the development of algorithms to reduce the incidence of false alarms in the Intensive Care Unit (ICU).

false alarm arrhythmia multiparameter icu challenge critical care tachycardia

Published: Feb. 15, 2015. Version: 1.0.0