Resources


Database Credentialed Access

MIMIC-IV

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

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

mimic critical care machine learning intensive care unit

Published: Jan. 6, 2023. Version: 2.2

Database Credentialed Access

EHRNoteQA: A Patient-Specific Question Answering Benchmark for Evaluating Large Language Models in Clinical Settings

Sunjun Kweon, Jiyoun Kim, Heeyoung Kwak, Dongchul Cha, Hangyul Yoon, Kwang Hyun Kim, Seunghyun Won, Edward Choi

A patient-specific question answering benchmark tailored for evaluating Large Language Models (LLMs) in clinical environments

Published: April 3, 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.

mimic emergency department ed emergency mimic-iv electronic health record

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…

intensive care clinical critical care machine learning natural language processing

Published: Sept. 4, 2016. Version: 1.4

Database Contributor Review

CARMEN-I: A resource of anonymized electronic health records in Spanish and Catalan for training and testing NLP tools

Eulalia Farre Maduell, Salvador Lima-Lopez, Santiago Andres Frid, Artur Conesa, Elisa Asensio, Antonio Lopez-Rueda, Helena Arino, Elena Calvo, Maria Jesús Bertran, Maria Angeles Marcos, Montserrat Nofre Maiz, Laura Tañá Velasco, Antonia Marti, Ricardo Farreres, Xavier Pastor, Xavier Borrat Frigola, Martin Krallinger

CARMEN-I is a Spanish corpus of 2,000 clinical records from Hospital Clínic, Barcelona. It covers COVID-19 patients and comorbidities, serving as a resource for training clinical NLP models and researchers in NLP applied to clinical documents.

de-identification clinical ner anonymization

Published: April 20, 2024. Version: 1.0.1

Challenge Credentialed Access

CXR-LT: Multi-Label Long-Tailed Classification on Chest X-Rays

Gregory Holste, Song Wang, Ajay Jaiswal, Yuzhe Yang, Mingquan Lin, Yifan Peng, Atlas Wang

CXR-LT 2023 was a challenge for long-tailed, multi-label thorax disease classification on chest X-rays, held in conjunction with the ICCV 2023 workshop, CVAMD. This page contains extended long-tailed versions of the MIMIC-CXR-JPG v2.0.0 dataset.

Published: Sept. 28, 2023. Version: 1.1.0

Database Open Access

MIMIC-IV Clinical Database Demo

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

An openly available subset of patients in the MIMIC-IV database.

mimic critical care electronic health record

Published: Jan. 31, 2023. Version: 2.2

Database Credentialed Access

Learning to Ask Like a Physician: a Discharge Summary Clinical Questions (DiSCQ) Dataset

Eric Lehman

Dataset of questions asked by medical experts about patients. Medical experts will read a discharge summary line-by-line and (1) ask any question that they may have and (2) record what in the text "triggered" them to ask their question.

machine learning question generation question answering

Published: July 28, 2022. Version: 1.0