Resources


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 Open Access

MIMIC-IV demo data in the Medical Event Data Standard (MEDS)

Robin Philippus van de Water, Ethan Steinberg, Michael Wornow, et al.

MIMIC-IV Clinical Database Demo in MEDS (Medical Event Data Standard) format.

ehr critical care electronic health record machine learning mimic meds medical event data standard

Published: Sept. 29, 2025. Version: 0.0.1

Database Credentialed Access

MIMIC-IV-Ext-Instr: A Dataset of 450K+ EHR-Grounded Instruction-Following Examples

Zhenbang Wu, Anant Dadu, Mike Nalls, et al.

This dataset contains 450K open-ended instruction-following examples generated using GPT-3.5 based on the MIMIC-IV EHR database.

large language models medical question answering instruction tuning

Published: Sept. 9, 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 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

MIMIC-III-Ext-VeriFact-BHC: Labeled Propositions From Brief Hospital Course Summaries for Long-form Clinical Text Evaluation

Philip Chung, Akshay Swaminathan, Alex Goodell, et al.

A clinician-labeled dataset for fact-checking long-form clinical text against patient EHRs. The dataset contains LLM-written and human-written Brief Hospital Course summaries decomposed to atomic claim and sentence propositions with annotations.

artificial intelligence natural language processing clinical notes electronic health records large language models brief hospital course long-form text chart review text reranking atomic claim hybrid retrieval clinical informatics clinical medicine fact verification retrieval-augmented generation logical atomism text embedding formal logic llm-as-a-judge llm evaluation

Published: April 9, 2025. Version: 1.0.0

Database Credentialed Access

EHRCon: Dataset for Checking Consistency between Unstructured Notes and Structured Tables in Electronic Health Records

Yeonsu Kwon, Jiho Kim, Gyubok Lee, et al.

Dataset for Checking Consistency between Unstructured Notes and Structured Tables in Electronic Health Records

Published: March 19, 2025. Version: 1.0.1

Database Restricted Access

OpenOximetry Repository

Nicholas Fong, Michael Lipnick, Philip Bickler, et al.

A repository of matched arterial oxygen and pulse oximeter readings obtained under controlled conditions, with high-frequency physiologic waveforms and skin color measurements.

Published: Feb. 28, 2025. Version: 1.1.1

Database Credentialed Access

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

Asad Aali, Dave Van Veen, Yamin Arefeen, et al.

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 machine learning brief hospital course text summarization

Published: Feb. 3, 2025. Version: 1.2.0

Database Open Access

CGMacros: a scientific dataset for personalized nutrition and diet monitoring

Ricardo Gutierrez-Osuna, David Kerr, Bobak Mortazavi, et al.

CGMacros contains information from two continuous glucose monitors (CGM), food macronutrients, food photographs, physical activity, and anonymized participant demographics, anthropometric measurements and health parameters.

diabetes machine learning continuous glucose monitors obesity postprandial glucose response food macronutrients metabolic models food photographs personalized nutrition

Published: Jan. 28, 2025. Version: 1.0.0