Resources


Model Credentialed Access

RadVLM model

Nicolas Deperrois, Hidetoshi Matsuo, Samuel Ruiperez-Campillo, et al.

RadVLM is a 7B-parameter vision-language model fine-tuned on public chest-X-ray data that drafts reports, lists abnormalities, grounds findings, and chats about a CXR through a single image-to-text interface.

Published: Oct. 8, 2025. Version: 1.0.0


Database Credentialed Access

Multimodal Clinical Monitoring in the Emergency Department (MC-MED)

Aman Kansal, Emma Chen, Tom Jin, et al.

A multimodal dataset of deidentified clinical and physiological data from emergency department visits, supporting research on patient outcomes, care processes, and the effects of continuous monitoring during and after the COVID-19 pandemic.

Published: Sept. 25, 2025. Version: 1.0.1


Database Open Access

ReXErr-v1: Clinically Meaningful Chest X-Ray Report Errors Derived from MIMIC-CXR

Vishwanatha Rao, Serena Zhang, Julian Acosta, et al.

Chest X-Ray reports containing synthetic errors based upon the MIMIC-CXR database. Errors were injected using LLMs and sampled across common human and AI model errors.

Published: March 19, 2025. Version: 1.0.0


Database Credentialed Access

LLaVA-Rad MIMIC-CXR Annotations

Juan Manuel Zambrano Chaves, Shih-Cheng Huang, Yanbo Xu, et al.

This dataset provides GPT-4 extracted sections of radiology reports from MIMIC-CXR, complementing rule-based section extractions with additional reports with findings, and removing references to priors from findings.

Published: Jan. 24, 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


Database Contributor Review

Chest Computed Tomography for patients with sepsis in the Emergency Department

Senjun Jin, Zhongheng Zhang

The database is intended to support a wide array of research studies involving radiomics in sepsis patients, helping to reduce barriers to the reproducibility of clinical research.

sepsis

Published: Oct. 28, 2024. Version: 1.0.0


Database Contributor Review

COVID Data for Shared Learning (CDSL): A comprehensive, multimodal COVID-19 dataset from HM Hospitales

Álvaro Ritoré, Andreea M Oprescu, Alberto Estirado Bronchalo, et al.

COVID Data for Shared Learning (CDSL) is a multimodal database comprising de-identified structured health data and radiological images from 4,479 patients with COVID-19, as a comprehensive toolkit for developing predictive models.

covid-19 multimodal database radiological images open data healthcare data machine learning and ai

Published: Oct. 25, 2024. Version: 1.0.0


Database Open Access

Radiology Report Generation Models Evaluation Dataset For Chest X-rays (RadEvalX)

Amos Rubin Calamida, Farhad Nooralahzadeh, Morteza Rohanian, et al.

The RadEvalX is a publicly available dataset developed similarly to the ReXVal dataset. RedEvalX focuses on radiologist evaluations of errors found in automatically generated radiology reports.

Published: June 18, 2024. Version: 1.0.0


Database Open Access

Kiel Cardio Database

Erik Engelhardt, Norbert Frey, Gerhard Schmidt

The Kiel Cardio Database (KCD) contains one-minute 8-lead magnetocardiographic (MCG) measurements from seven subjects. Each subject underwent 25 consecutive measurements using a sensor array comprising four QuSpin QZFMs.

opically pumped magnetometer opm mcg magnetocardiography

Published: Dec. 15, 2023. Version: 1.0.0

Visualize waveforms

Database Credentialed Access

CAD-Chest: Comprehensive Annotation of Diseases based on MIMIC-CXR Radiology Report

Mengliang Zhang, Xinyue Hu, Lin Gu, et al.

The CAD-Chest dataset provides comprehensive annotations of disease, including disease severity, uncertainty, and location based on the MIMIC-CXR radiologist reports.

chesr x-ray disease label

Published: Dec. 8, 2023. Version: 1.0