Resources


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

MIMIC-IV

Alistair Johnson, Lucas Bulgarelli, Tom Pollard, Brian Gow, Benjamin Moody, Steven Horng, Leo Anthony Celi, Roger Mark

Large database of de-identified health information from patients admitted to Beth Israel Deaconess Medical Center

critical care intensive care unit mimic machine learning

Published: Oct. 11, 2024. Version: 3.1

Database Credentialed Access

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

Aman Kansal, Emma Chen, Tom Jin, Pranav Rajpurkar, David Kim

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 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

AIPatient KG: MIMIC-III and CORAL Electronic Health Records based Patient Knowledge Graph

Lizhou Fan, Huizi Yu

This project integrates MIMIC-III and CORAL electronic health records into knowledge graphs to improve medical analysis and enhance decision-making capabilities. Resources include two knowledge graph snapshots and two question-and-answering datasets.

Published: April 15, 2025. Version: 1.0.0

Database Credentialed Access

EHRXQA: A Multi-Modal Question Answering Dataset for Electronic Health Records with Chest X-ray Images

Seongsu Bae, Daeun Kyung, Jaehee Ryu, Eunbyeol Cho, Gyubok Lee, Sunjun Kweon, Jungwoo Oh, Lei JI, Eric Chang, Tackeun Kim, Edward Choi

We present EHRXQA, the first multi-modal EHR QA dataset combining structured patient records with aligned chest X-ray images. EHRXQA contains a comprehensive set of QA pairs covering image-related, table-related, and image+table-related questions.

question answering chest x-ray electronic health records multi-modal question answering ehr question answering semantic parsing machine learning deep learning evaluation visual question answering benchmark

Published: July 23, 2024. Version: 1.0.0

Database Credentialed Access

MIMIC-IV-ED

Alistair Johnson, Lucas Bulgarelli, Tom Pollard, Leo Anthony Celi, Roger Mark, Steven Horng

A large database of emergency department admissions.

emergency department ed emergency mimic-iv electronic health record mimic

Published: Jan. 5, 2023. Version: 2.2

Database Credentialed Access

RuMedNLI: A Russian Natural Language Inference Dataset For The Clinical Domain

Pavel Blinov, Aleksandr Nesterov, Galina Zubkova, Arina Reshetnikova, Vladimir Kokh, Chaitanya Shivade

RuMedNLI is the full counterpart dataset of MedNLI in Russian language.

natural language inference recognizing textual entailment russian language

Published: April 1, 2022. Version: 1.0.0

Database Credentialed Access

National Institutes of Health Stroke Scale (NIHSS) Annotations for the MIMIC-III Database

Jiayang Wang, Xiaoshuo Huang, Lin Yang, Jiao Li

A dataset of annotated NIHSS scale items and corresponding scores from stroke patients discharge summaries in MIMIC-III.

Published: Jan. 25, 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