Resources


Database Restricted Access

KURIAS-ECG: a 12-lead electrocardiogram database with standardized diagnosis ontology

Hakje Yoo, Yunjin Yum, Soowan Park, Jeong Moon Lee, Moonjoung Jang, Yoojoong Kim, Jong-Ho Kim, Hyun-Joon Park, Kap Su Han, Jae Hyoung Park, Hyung Joon Joo

The KURIAS-ECG database is a high-quality 12-lead ECG DB including standard vocabulary (SNOMED CT, OMOP-CDM), and ECG diagnoses of our DB are grouped into 10 diagnoses by applying the minnesota code.

snomed minnesota 12-lead ecg

Published: Nov. 8, 2021. Version: 1.0

Database Open Access

Hillel Yaffe Glaucoma Dataset (HYGD): A Gold-Standard Annotated Fundus Dataset for Glaucoma Detection

Or Abramovich, Hadas Pizem, Jonathan Fhima, Eran Berkowitz, Ben Gofrit, Jan Van Eijgen, Eytan Blumenthal, Joachim Behar

HYGD is a rigorously annotated fundus image dataset with gold-standard clinical labels designed to improve and benchmark deep learning models for accurate glaucoma detection.

ophthalmology retina dfi gold-standard gon fundus glaucoma

Published: June 3, 2025. Version: 1.0.0

Database Open Access

Hillel Yaffe Glaucoma Dataset (HYGD): A Gold-Standard Annotated Fundus Dataset for Glaucoma Detection

Or Abramovich, Hadas Pizem, Jonathan Fhima, Eran Berkowitz, Ben Gofrit, Jan Van Eijgen, Eytan Blumenthal, Joachim Behar

HYGD is a rigorously annotated fundus image dataset with gold-standard clinical labels designed to improve and benchmark deep learning models for accurate glaucoma detection.

ophthalmology retina dfi gold-standard gon fundus glaucoma

Published: June 3, 2025. 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.

chest x-rays heart failure early detection cardiac structural abnormalties deep learning

Published: March 20, 2024. 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, 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

Database Credentialed Access

Deidentified Medical Text

Margaret Douglass, Bill Long, George Moody, Peter Szolovits, Li-wei Lehman, Roger Mark, Gari D. Clifford

Gold standard corpus of 2,434 deidentified nursing notes

medical text nursing notes hipaa de-identification

Published: Dec. 18, 2007. Version: 1.0

Database Open Access

Noise Enhancement of Sensorimotor Function

Postural sway measurements for 27 healthy young and elderly volunteers.

noise gait

Published: Oct. 29, 2004. Version: 1.0.0

Database Open Access

bigP3BCI: An Open, Diverse and Machine Learning Ready P300-based Brain-Computer Interface Dataset

Boyla Mainsah, Chance Fleeting, Thomas Balmat, Eric Sellers, Leslie Collins

A collection of data from P300-based brain-computer interface studies.

brain-computer interface electroencephalography ieee p2731 working group standard amyotrophic lateral sclerosis p300 speller p300 event related potential oddball paradigm error-related potential

Published: May 19, 2025. Version: 1.0.0

Database Open Access

MIMIC-IV Clinical Database Demo on FHIR

Alex Bennett, Hannes Ulrich, Joshua Wiedekopf, Piotr Szul, John Grimes, Alistair Johnson

The MIMIC-IV Clinical Database Demo on FHIR is a 100 patient subset of the MIMIC-IV v2.2 and MIMIC-IV-ED v2.2 clinical databases converted into the Fast Healthcare Interoperability Resources (FHIR) format.

fhir electronic health records mimic

Published: Aug. 27, 2025. Version: 2.1.0

Database Credentialed Access

CXR-Align: A Benchmark for CXR-Report Alignment with Negations

Hanbin Ko

CXR-Align is a benchmark dataset created to evaluate vision-language models' capability to interpret negations in chest X-ray (CXR) reports, featuring systematically modified reports from MIMIC-CXR.

Published: Aug. 21, 2025. Version: 1.0.0