Resources


Database Open Access

PAF Prediction Challenge Database

ECG recordings created for use in the Computers in Cardiology Challenge 2001, a competition with the goal of developing automated methods for predicting paroxysmal atrial fibrillation.

challenge ecg

Published: March 1, 2001. Version: 1.0.0

Visualize waveforms

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…

challenge atrial fibrillation ecg

Published: March 1, 2001. Version: 1.0.0

Database Open Access

MIMIC Database

The MIMIC Database includes data recorded from over 90 ICU patients. The data in each case include signals and periodic measurements obtained from a bedside monitor as well as clinical data obtained from the patient's medical record. The recordi…

health record ehr icu critical care mimic

Published: March 15, 2000. Version: 1.0.0

Visualize waveforms

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…

apnea challenge ecg

Published: Feb. 10, 2000. Version: 1.0.0

Database Restricted Access

EchoNext: A Dataset for Detecting Echocardiogram-Confirmed Structural Heart Disease from ECGs

Pierre Elias, Joshua Finer

EchoNext is a curated dataset of electrocardiograms (ECGs) paired with echocardiogram-confirmed structural heart disease labels, designed to support the development and validation of machine learning models.

heart failure clinical decision support artificial intelligence health equity ecg deep learning machine learning electrocardiogram aortic stenosis cardiovascular screening valvular heart disease digital health ai model deployment left ventricular dysfunction ai in healthcare population health transthoracic echocardiogram structural heart disease

Published: Sept. 16, 2025. Version: 1.1.0

Database Contributor Review

Salzburg Intensive Care database (SICdb), a freely accessible intensive care database

Niklas Rodemund, Andreas Kokoefer, Bernhard Wernly, Crispiana Cozowicz

The SICdb dataset, version 1.0.8 contains 27350 admissions to an ICU in an Austrian tertiary care institution.

clinical intensive care critical care open data machine learning

Published: Sept. 10, 2024. Version: 1.0.8

Challenge Credentialed Access

BioNLP Workshop 2023 Shared Task 1A: Problem List Summarization

Yanjun Gao, Dmitriy Dligach, Timothy Miller, Majid Afshar

This is the data storage for BioNLP Workshop Shared Task 1A: Problem List Summarization.

bionlp clinical natural language processing electronic health record summarization

Published: Nov. 12, 2023. Version: 2.0.0

Software Open Access

Lightweight 12-lead ECG viewer for MATLAB

Erick Andres Perez Alday, Larisa Tereshchenko

Clinical Viewer of raw digital 12-lead ECG file (ECG file in .txt format).

clinical 12-lead ecg routine clinical ecg viewer electrocardiogram

Published: Aug. 30, 2021. Version: 1.0.0

Database Contributor Review

HiRID, a high time-resolution ICU dataset

Martin Faltys, Marc Zimmermann, Xinrui Lyu, Matthias Hüser, Stephanie Hyland, Gunnar Rätsch, Tobias Merz

The HiRID database contains a large selection of all routinely collected data relating to patient admissions to the Department of Intensive Care Medicine of the Bern University Hospital, Switzerland (ICU).

icu clinical intensive care high resolution critical care machine learning

Published: Feb. 18, 2021. Version: 1.1.1

Database Restricted Access

EchoNext: A Dataset for Detecting Echocardiogram-Confirmed Structural Heart Disease from ECGs

Pierre Elias, Joshua Finer

EchoNext is a curated dataset of electrocardiograms (ECGs) paired with echocardiogram-confirmed structural heart disease labels, designed to support the development and validation of machine learning models.

heart failure clinical decision support artificial intelligence health equity ecg deep learning machine learning electrocardiogram aortic stenosis cardiovascular screening valvular heart disease digital health ai model deployment left ventricular dysfunction ai in healthcare population health transthoracic echocardiogram structural heart disease

Published: Sept. 16, 2025. Version: 1.1.0