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.

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

Published: Aug. 5, 2025. Version: 1.0.0

Database Restricted Access

MIMIC-III-Ext-Synthetic-Clinical-Trial-Questions

Elizabeth Woo, Michael Craig Burkhart, Emily Alsentzer, Brett Beaulieu-Jones

In our recent study, we used Llama-3.1-70B-Instruct to generate synthetic training examples resembling clinical trial eligibility criteria. We manually reviewed 1000 of these examples and release them here.

large language models synthetic data distillation clinical trial eligibility

Published: April 22, 2025. 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.

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

Published: Aug. 5, 2025. Version: 1.0.0

Database Restricted Access

MIMIC-III-Ext-Synthetic-Clinical-Trial-Questions

Elizabeth Woo, Michael Craig Burkhart, Emily Alsentzer, Brett Beaulieu-Jones

In our recent study, we used Llama-3.1-70B-Instruct to generate synthetic training examples resembling clinical trial eligibility criteria. We manually reviewed 1000 of these examples and release them here.

large language models synthetic data distillation clinical trial eligibility

Published: April 22, 2025. Version: 1.0.0

Database Restricted Access

CXRGraph: Using Information Extraction to Normalize the Training Data for Automatic Radiology Report Generation

Yuxiang Liao, Hoisang Heung, Hantao Liu, Irena Spasic

CXRGraph is a structured radiology report dataset built upon RadGraph and tailored for the Automatic Radiology Report Generation task. It can identify more task-relevant information such as abnormalities and hallucinated prior references.

relation extraction information extraction natural language processing named entity recognition structured radiology report

Published: Feb. 3, 2025. Version: 1.0.0

Database Credentialed Access

Tasks 1 and 3 from Progress Note Understanding Suite of Tasks: SOAP Note Tagging and Problem List Summarization

Yanjun Gao, John Caskey, Timothy Miller, Brihat Sharma, Matthew Churpek, Dmitriy Dligach, Majid Afshar

We introduce a hierarchical annotation suite of tasks addressing clinical text understanding, reasoning and abstraction over evidence, and diagnosis summarization. One task is section tagging major section and the other task is diagnosis generation.

Published: Sept. 30, 2022. Version: 1.0.0

Software Open Access

Logistic Regression-HSMM-based Heart Sound Segmentation

David Springer

Heart sound segmentation code, based on a duration-dependent hidden Markov model, extended with the use of logistic regression for emission probability estimation and an enhanced Viterbi algorithm.

Published: July 29, 2019. Version: 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

Database Restricted Access

Dataset for Segmentation and Classification of Cardiac Implantable Electronic Devices in Chest X-Rays

Keno Bressem, Felix Busch, Andrei Zhukov, Lisa Adams

This dataset comprises 11,094 converted DICOM and smartphone images of Cardiac Implantable Electronic Devices (CIEDs), collected from 897 patients. It aims to facilitate the development of algorithms for CIED detection and classification.

chest x-ray radiology medical imaging cardiac implantable electronic devices

Published: March 4, 2025. Version: 1.0.0

Database Restricted Access

Application of Med-PaLM 2 in the refinement of MIMIC-CXR labels

Kendall Park, Rory Sayres, Andrew Sellergren, Tom Pollard, Fayaz Jamil, Timo Kohlberger, Charles Lau, Atilla Kiraly

This work further refines the labels associated with CheXpert in MIMIC-CXR-JPG 2.0.0 by filtering with Med-PaLM 2 followed by verification by manual review by three US board-certified radiologists.

mimic-cxr labels

Published: Feb. 4, 2025. Version: 1.0.0