Resources

34 results for "cardiology"

Challenge Open Access

The First Five Challenges Revisited: The PhysioNet/Computing in Cardiology Challenge 2005

Our popular series of challenges presented in cooperation with Computers in Cardiology continues this year in a new mode. Participants are invited to choose one of the five previous challenges as a topic for a follow-up study: Detecting sleep apn…
Published: May 2, 2005. Version: 1.0.0
Challenge Open Access

Predicting Paroxysmal Atrial Fibrillation/Flutter: The PhysioNet/Computing in Cardiology Challenge 2001

Following the success of the first Computers in Cardiology Challenge, we are pleased to offer a new challenge from PhysioNet and Computers in Cardiology 2001. The challenge is to develop a fully automated method to predict the onset of paroxysmal at…
Published: March 1, 2001. Version: 1.0.0
Challenge Open Access

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

Matthew Reyna, Nadi Sadr, Annie Gu, et al.

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 EC…
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, et al.

The electrocardiogram (ECG) is a non-invasive representation of the electrical activity of the heart from electrodes placed on the surface of the torso. The standard 12-lead ECG has been widely used to diagnose a variety of cardiac abnormalities suc…
Published: July 29, 2022. Version: 1.0.2 | Visualize waveforms
Database Open Access

NInFEA: Non-Invasive Multimodal Foetal ECG-Doppler Dataset for Antenatal Cardiology Research

Danilo Pani, Eleonora Sulas, Monica Urru, et al.

The development of algorithms for the extraction of the foetal ECG (fECG) from non-invasive recordings is hampered by the lack of publicly-available reference datasets, which could be used to benchmark different algorithms while providing a ground t…
Published: Nov. 12, 2020. Version: 1.0.0 | Visualize waveforms
Challenge Open Access

Early Prediction of Sepsis from Clinical Data: The PhysioNet/Computing in Cardiology Challenge 2019

Matthew Reyna, Chris Josef, Russell Jeter, et al.

Sepsis is a life-threatening condition that occurs when the body's response to infection causes tissue damage, organ failure, or death (Singer et al., 2016). In the U.S., nearly 1.7 million people develop sepsis and 270,000 people die from sepsis ea…
Published: Aug. 5, 2019. Version: 1.0.0
Challenge Open Access

Noninvasive Fetal ECG: The PhysioNet/Computing in Cardiology Challenge 2013

The aim of this year's PhysioNet/Computing in Cardiology Challenge is to encourage development of accurate algorithms for locating QRS complexes and estimating the QT interval in noninvasive FECG signals.
Published: Feb. 21, 2013. Version: 1.0.0
Challenge Open Access

Improving the Quality of ECGs Collected using Mobile Phones: The PhysioNet/Computing in Cardiology Challenge 2011

The aim of the PhysioNet/Computing in Cardiology Challenge 2011 is to develop an efficient algorithm able to run in near real-time within a mobile phone, that can provide useful feedback to a layperson in the process of acquiring a diagnostically us…
Published: April 19, 2011. Version: 1.0.0
Challenge Open Access

Predicting Acute Hypotensive Episodes: The PhysioNet/Computing in Cardiology Challenge 2009

This year's challenge is the tenth in the annual series of open challenges hosted by PhysioNet in cooperation with Computers in Cardiology. The goal of the challenge is to predict which patients in the challenge dataset will experience an acute hypo…
Published: Jan. 27, 2009. Version: 1.0.0
Challenge Open Access

Detecting and Quantifying T-Wave Alternans: The PhysioNet/Computing in Cardiology Challenge 2008

The ninth annual PhysioNet/Computers in Cardiology Challenge aims to improve understanding of methods for identification and analysis of T-wave alternans in the ECG.
Published: March 17, 2008. Version: 1.0.0