Resources


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.

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Published: Sept. 16, 2025. Version: 1.1.0

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 machine learning deep 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

Challenge Open Access

Heart Murmur Detection from Phonocardiogram Recordings: The George B. Moody PhysioNet Challenge 2022

Matthew Reyna, Yashar Kiarashi, Andoni Elola, Jorge Oliveira, Francesco Renna, Annie Gu, Erick Andres Perez Alday, Nadi Sadr, Sandra Mattos, Miguel Coimbra, Reza Sameni, Ali Bahrami Rad, Zuzana Koscova, Gari Clifford

2022 Physionet Challenge is devoted to detecting the presence or absence of murmurs from multiple heart sound recordings from multiple auscultation locations, as well as detecting the clinical outcomes.

challenge competition cardiac auscultation congenital heart diseases

Published: Sept. 28, 2023. Version: 1.0.0

Challenge Open Access

Heart Murmur Detection from Phonocardiogram Recordings: The George B. Moody PhysioNet Challenge 2022

Matthew Reyna, Yashar Kiarashi, Andoni Elola, Jorge Oliveira, Francesco Renna, Annie Gu, Erick Andres Perez Alday, Nadi Sadr, Sandra Mattos, Miguel Coimbra, Reza Sameni, Ali Bahrami Rad, Zuzana Koscova, Gari Clifford

2022 Physionet Challenge is devoted to detecting the presence or absence of murmurs from multiple heart sound recordings from multiple auscultation locations, as well as detecting the clinical outcomes.

challenge competition cardiac auscultation congenital heart diseases

Published: Sept. 28, 2023. Version: 1.0.0

Database Restricted Access

CheXchoNet: A Chest Radiograph Dataset with Gold Standard Echocardiography Labels

Pierre Elias, Shreyas Bhave

Early detection of heart failure is vital for improving outcomes. The dataset contains 71,589 CXRs paired with gold standard labels from echocardiograms to enable the training of models to detect pathologies indicative of early stage heart failure.

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Published: March 20, 2024. Version: 1.0.0

Database Restricted Access

Pulmonary Edema Severity Grades Based on MIMIC-CXR

Ruizhi Liao, Geeticka Chauhan, Polina Golland, Seth Berkowitz, Steven Horng

Pulmonary edema metadata and labels for MIMIC-CXR

Published: Feb. 9, 2021. Version: 1.0.1