Resources


Database Restricted Access

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

Yuxiang Liao, Hoisang Heung, Hantao Liu, et al.

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, et al.

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 Open Access

HeartCycle: A comprehensive dataset of synchronized impedance cardiography and echocardiography for accurate hemodynamic predictions

Eduardo Illueca Fernandez, Ricardo Couceiro, Farhad Abtahi, et al.

Impedance cardiography dataset (ICG) which combines the ICG signals and other methodologies with the golden standard echocardiographys (ECG). Researchers can use this dataset to compare the ICG points with the real hemodynamic events.

machine learning echocardiography cardiovascular physiology electrophysiological study impedance cardiography

Published: Nov. 2, 2025. Version: 1.0.0

Database Credentialed Access

MIMIC-IV-ECHO-Ext-MIMICEchoQA: A Benchmark Dataset for Echocardiogram-Based Visual Question Answering

Rahul Thapa, Andrew Li, Qingyang Wu, et al.

We present MIMICEchoQA, a benchmark dataset for echocardiogram-based question answering, built from the publicly available MIMIC-IV-ECHO database.

Published: Oct. 7, 2025. Version: 1.0.0

Database Credentialed Access

RadGraph-XL: A Large-Scale Expert-Annotated Dataset for Entity and Relation Extraction from Radiology Reports

Jean-Benoit Delbrouck

RadGraph-XL is a large, expert-annotated dataset of 2,300 radiology reports covering multiple modalities and anatomies. It enables accurate extraction of clinical entities and relations for downstream medical AI tasks.

Published: Sept. 12, 2025. Version: 1.0.0

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, et al.

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 cardiac implantable electronic devices medical imaging

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, et al.

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

Database Restricted Access

Endoscapes2023, A Critical View of Safety and Surgical Scene Segmentation Dataset for Laparoscopic Cholecystectomy

Pietro Mascagni, Deepak Alapatt, Aditya Murali, et al.

Endoscapes2023 enables the development of models for object detection, semantic and instance segmentation, and Critical View of Safety (CVS) prediction, contributing to safe laparoscopic cholecystectomy.

surgical safety computer assisted interventions semantic segmentation surgical data science medical imaging analysis

Published: Dec. 11, 2024. Version: 1.0.0