Resources


Database Credentialed Access

CXR-PRO: MIMIC-CXR with Prior References Omitted

Vignav Ramesh, Nathan Chi, Pranav Rajpurkar

CXR-PRO is an adaptation of the MIMIC-CXR dataset (consisting of chest radiographs and their associated free-text radiology reports) with references to non-existent priors removed.

generation free-text radiology reports references to priors retrieval large language models

Published: Nov. 23, 2022. Version: 1.0.0

Database Credentialed Access

CLIP: A Dataset for Extracting Action Items for Physicians from Hospital Discharge Notes

James Mullenbach, Yada Pruksachatkun, Sean Adler, et al.

Clinical action items annotated over MIMIC-III. 718 discharge summaries are labeled at a sentence- and character-level with multiple action labels including Appointment, Lab, Procedure, Medication, Imaging, Patient Instructions, and Other.

Published: June 21, 2021. Version: 1.0.0

Database Credentialed Access

MIMIC-III Clinical Database

Alistair Johnson, Tom Pollard, Roger Mark

MIMIC-III is a large, freely-available database comprising deidentified health-related data associated with over forty thousand patients who stayed in critical care units of the Beth Israel Deaconess Medical Center between 2001 and 2012. The databas…

clinical intensive care critical care natural language processing machine learning

Published: Sept. 4, 2016. Version: 1.4

Database Credentialed Access

MIMIC-CXR-Ext-ILS: Lesion Segmentation Masks and Instruction-Answer Pairs for Chest X-rays

Geon Choi, Hangyul Yoon, Hyunju Shin, et al.

Instruction-guided lesion segmentation data for chest X-rays, including 1.1M instruction-answer pairs and 91K segmentation masks covering seven major lesion types.

chest x-ray segmentation text-guided segmentation lesion segmentation

Published: March 25, 2026. Version: 1.0.0

Database Restricted Access

LATTE-CXR: Locally Aligned TexT and imagE, Explainable dataset for Chest X-Rays

Elham Ghelichkhan, Tolga Tasdizen

This dataset includes bounding box-statement pairs for chest X-ray images, derived from radiologists’ eye-tracking data (for explainability) and annotations, for local visual-language models.

eye-tracking chest x-ray dataset automatically generated dataset caption-guided object detection image captioning with region-level description grounded radiology report generation phrase grounding xai multi-modal learning local visual-language models localization

Published: Feb. 4, 2025. Version: 1.0.0

Database Restricted Access

HYAMD High-Resolution Fundus Image Dataset for age related macular degeneration (AMD) Diagnosis

Meishar Meisel, Benjamin Alfred Cohen, Meital Baskin, et al.

The HYAMD dataset comprises 1,560 high-resolution fundus images from 325 patients, aimed at validating machine learning models for age-related macular degeneration (AMD) diagnosis.

Published: Sept. 9, 2025. Version: 1.0.0

Database Credentialed Access

MIMIC-CXR Database

Alistair Johnson, Tom Pollard, Roger Mark, et al.

Chest radiographs in DICOM format with associated free-text reports.

chest x-rays computer vision natural language processing machine learning radiology mimic

Published: July 23, 2024. Version: 2.1.0

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

Database Credentialed Access

MedVH: Towards Systematic Evaluation of Hallucination for Large Vision Language Models in the Medical Context

Zishan Gu, Jiayuan Chen, Fenglin Liu, et al.

MedVH provides a visual hallucination evaluation benchmark for large language models in the medical context. It formulates tests using chest X-ray images, including multi-choice question answering and long-text generation tasks.

Published: Dec. 10, 2025. Version: 1.0.1

Database Credentialed Access

A Brazilian Multilabel Ophthalmological Dataset (BRSET)

Luis Filipe Nakayama, Mariana Goncalves, Lucas Zago Ribeiro, et al.

This is the first Brazilian Multilabel Ophthalmological Dataset with demographic information and retinal photos labeled images according to anatomical parameters, quality control, and presumed diagnosis.

dataset ophthalmology retina

Published: Aug. 14, 2024. Version: 1.0.1