Resources


Challenge Credentialed Access

SNOMED CT Entity Linking Challenge

Will Hardman, Mark Banks, Rory Davidson, Donna Truran, Nindya Widita Ayuningtyas, Hoa Ngo, Alistair Johnson, Tom Pollard

272 discharge notes from the MIMIC-IV-Note dataset annotated with SNOMED CT concepts.

snomed entity linking clinical annotation

Published: July 22, 2025. Version: 1.1.0

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 Credentialed Access

MIMIC-IV-Ext Cardiac Disease

Jiawei Cao, Sendong Zhao

The subset of the MIMIC-IV dataset includes the examination results and diagnostic information of 4,761 cardiac disease patients. The examination results for each patient are listed separately as evidence for the final diagnosis.

Published: May 6, 2025. Version: 1.0.0

Database Credentialed Access

MeDiSumQA: Patient-Oriented Question-Answer Generation from Discharge Letters

Amin Dada, Osman Alperen Koras, Marie Bauer, Amanda Butler, Kaleb Smith, Jens Kleesiek, Julian Friedrich

MeDiSumQA is a dataset of patient-oriented QA pairs from MIMIC-IV discharge summaries, designed to evaluate LLMs in generating safe, patient-friendly medical responses for clinical QA and healthcare communication.

Published: May 5, 2025. Version: 1.0.0

Database Credentialed Access

Medical Expert Annotations of Unsupported Facts in Doctor-Written and LLM-Generated Patient Summaries

Stefan Hegselmann, Shannon Shen, Florian Gierse, Monica Agrawal, David Sontag, Xiaoyi Jiang

Annotations for unsupported facts in 100 original MIMIC patient summaries (discharge instructions) and hallucinations in 100 Large Language Model (LLM) generated patient summaries labeled by two medical experts.

Published: April 30, 2025. Version: 1.0.1

Database Credentialed Access

MIMIC-III-Ext-tPatchGNN

Chenlong Yin, Weijia Zhang

The processed MIMIC-III dataset for the benchmark of Irregular Multivariate Time Series Forecasting: A Transformable Patching Graph Neural Networks Approach.

Published: April 9, 2025. Version: 1.0.0

Database Open Access

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

Vishwanatha Rao, Serena Zhang, Julian Acosta, Subathra Adithan, Pranav Rajpurkar

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

MIMIC-IV-Ext Triage Instruction Corpus

Qingyang Shen, Quan Guo

MIMIC-IV-Ext Triage Instruction Corpus includes 9,629 ED triage cases organized by the five-level ESI, enabling LLMs to improve triage accuracy. It provides CSV data, generation prompts, expert validation samples, and SQL QC scripts.

nlp clinical decision support large language models machine learning emergency severity index emergency triage

Published: March 4, 2025. Version: 1.0.0

Database Credentialed Access

MIMIC-IV-Ext-BHC: Labeled Clinical Notes Dataset for Hospital Course Summarization

Asad Aali, Dave Van Veen, Yamin Arefeen, Jason Hom, Christian Bluethgen, Eduardo Pontes Reis, Sergios Gatidis, Namuun Clifford, Joseph Daws, Arash Tehrani, Jangwon Kim, Akshay Chaudhari

This dataset presents a collection of preprocessed and labeled clinical notes derived from "MIMIC-IV-Note", and aims to facilitate the development of ML models focused on summarizing brief hospital courses (BHC) from clinical notes.

natural language processing clinical notes brief hospital course text summarization machine learning

Published: Feb. 3, 2025. Version: 1.2.0

Database Credentialed Access

Symile-MIMIC: a multimodal clinical dataset of chest X-rays, electrocardiograms, and blood labs from MIMIC-IV

Adriel Saporta, Aahlad Manas Puli, Mark Goldstein, Rajesh Ranganath

A multimodal clinical dataset consisting of CXRs, ECGs, and blood labs, designed to evaluate Symile, a simple contrastive loss that accommodates any number of modalities and allows any model to produce representations for each modality.

database cxr ecg chest x-ray mimic contrastive learning model multimodal electrocardiogram

Published: Jan. 28, 2025. Version: 1.0.0