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Featured 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: Dec. 19, 2023. Version: 1.0.0

Database Open Access

VitalDB, a high-fidelity multi-parameter vital signs database in surgical patients

Hyung-Chul Lee, Chul-Woo Jung

VitalDB, a high-fidelity multi-parameter vital signs database in surgical patients

waveform anesthesia vitaldb intraoperative biosignal ecg

Published: Sept. 21, 2022. Version: 1.0.0

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

critical care intensive care unit machine learning mimic

Published: Jan. 6, 2023. Version: 2.2

Database Credentialed Access

MIMIC-CXR Database

Alistair Johnson, Tom Pollard, Roger Mark, Seth Berkowitz, Steven Horng

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

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

Published: Sept. 19, 2019. Version: 2.0.0

Database Credentialed Access

BRAX, a Brazilian labeled chest X-ray dataset

Eduardo Pontes Reis, Joselisa Paiva, Maria Carolina Bueno da Silva, Guilherme Alberto Sousa Ribeiro, Victor Fornasiero Paiva, Lucas Bulgarelli, Henrique Lee, Paulo Victor dos Santos, vanessa brito, Lucas Amaral, Gabriel Beraldo, Jorge Nebhan Haidar Filho, Gustavo Teles, Gilberto Szarf, Tom Pollard, Alistair Johnson, Leo Anthony Celi, Edson Amaro

BRAX contains 24,959 chest radiography exams and 40,967 images acquired in a large general Brazilian hospital. All images have been read by trained radiologists and 14 labels were derived from Brazilian Portuguese reports using NLP.

chest x-ray dataset artificial intelligence

Published: June 17, 2022. Version: 1.1.0

Database Credentialed Access

eICU Collaborative Research Database

Tom Pollard, Alistair Johnson, Jesse Raffa, Leo Anthony Celi, Omar Badawi, Roger Mark

Multi-center database comprising deidentified health data associated with over 200,000 admissions to ICUs across the United States between 2014-2015.

telemedicine icu critical care

Published: April 15, 2019. Version: 2.0

Latest Resources

Database Credentialed Access

CovIdentify Dataset

Peter Cho, Md Mobashir Hasan Shandhi, Ali Roghanizad, Jessilyn Dunn

This contains wearable device data from Fitbit, Garmin, and Apple Watch users. The data is from April 2nd, 2020 to March 21st, 2021 and has been date-shifted. An appropriate amount has also shifted test dates for each user.

Published: Nov. 25, 2024. Version: 1.0.0

Database Credentialed Access

Northwestern ICU (NWICU) database

Dana Moukheiber, William Temps, Bhadrappa Molgi, Yikuan Li, Alice Lu, Prasanth Nannapaneni, Abdulrahman Chahin, Sicheng Hao, Felipe Torres Fabregas, Leo Anthony Celi, Adrian Wong, Maxwell Lloyd, Xavier Borrat Frigola, Hyung-Chul Lee, Daniel Schneider, Tom Pollard, Yuan Luo, Abel Kho, Roger Mark

A freely available COVID-rich ICU database comprising de-identified health-related data from Northwestern Memorial Health Center (NHMC).

Published: Nov. 19, 2024. Version: 0.1.0

Database Credentialed Access

MS-CXR: Making the Most of Text Semantics to Improve Biomedical Vision-Language Processing

Benedikt Boecking, Naoto Usuyama, Shruthi Bannur, Daniel Coelho de Castro, Anton Schwaighofer, Stephanie Hyland, Harshita Sharma, Maria Teodora Wetscherek, Tristan Naumann, Aditya Nori, Javier Alvarez Valle, Hoifung Poon, Ozan Oktay

MS-CXR is a new dataset containing 1162 chest X-ray bounding box labels paired with radiology text descriptions, annotated and verified by two board-certified radiologists.

vision-language processing localization phrase grounding chest x-ray

Published: Nov. 15, 2024. Version: 1.1.0

Database Credentialed Access

MIMIC-IV on FHIR

Alex Bennett, Joshua Wiedekopf, Hannes Ulrich, Philip van Damme, Piotr Szul, John Grimes, Alistair Johnson

MIMIC-IV and MIMIC-IV-ED data mapped into FHIR resources.

mimic-iv fhir electronic health record us core mimic fast healthcare interoperability resources

Published: Nov. 12, 2024. Version: 2.1

Database Contributor Review

Chest Computed Tomography for patients with sepsis in the Emergency Department

Senjun Jin, Zhongheng Zhang

The database is intended to support a wide array of research studies involving radiomics in sepsis patients, helping to reduce barriers to the reproducibility of clinical research.

sepsis

Published: Oct. 28, 2024. Version: 1.0.0

Database Contributor Review

COVID Data for Shared Learning (CDSL): A comprehensive, multimodal COVID-19 dataset from HM Hospitales

Álvaro Ritoré, Andreea M Oprescu, Alberto Estirado Bronchalo, Miguel Ángel Armengol de la Hoz

COVID Data for Shared Learning (CDSL) is a multimodal database comprising de-identified structured health data and radiological images from 4,479 patients with COVID-19, as a comprehensive toolkit for developing predictive models.

covid-19 multimodal database radiological images open data healthcare data machine learning and ai

Published: Oct. 25, 2024. Version: 1.0.0

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News

MIMIC-IV v3.1 is now available on BigQuery

News from: MIMIC-IV v3.1.

Nov. 12, 2024

MIMIC-IV v3.1 is now available on BigQuery. Users may request access via PhysioNet. Currently, MIMIC-IV v3.1 is available on the mimiciv_v3_1_hosp and mimiciv_v3_1_icu schemas. MIMIC-IV v2.2 is available on the mimiciv_v2_2_hosp and mimiciv_v2_2_icu datasets as well as the mimiciv_hosp and mimiciv_icu datasets. On November 25th 2024, we will replace the data on mimiciv_hosp and mimiciv_icu with MIMIC-IV v3.1.

Upgrading MIMIC-IV on BigQuery

News from: MIMIC-IV v3.0.

Sept. 28, 2024

MIMIC-IV v3.0 is currently unavailable on BigQuery. Currently, the mimiciv_hosp and mimiciv_icu datasets on BigQuery contain MIMIC-IV v2.2, and access to these datasets is still available via PhysioNet by navigating to the v2.2 page. We plan to upgrade these BigQuery datasets in the near future, and will notify users when we do so.

Delays in reviewing applications for credentialed access

June 17, 2024

As a result of staffing changes in our research group, applications for credentialed access are likely to be subject to significant delays. We are doing our best to deal with the waitlist quickly, handling applications in the order in which they are received. To help ensure that your application is successful, please remember to:

Include a copy of your CITI training report (not the certificate).
Remind your reference to reply promptly when contacted.
Check your application details are correct before submitting.
Add an institutional or educational email address as your primary email.

We apologize for the inconvenience. Please bear with us during this busy time!

George B. Moody PhysioNet Challenge 2024 is teaming up with Data Science Africa

May 18, 2024

The George B. Moody PhysioNet Challenge 2024 is teaming up with Data Science Africa (DSA) to innovate cardiac care through signal processing & machine learning at Nyeri, Kenya, for DSA's 10 year anniversary in June 2024.

DSA aims to create a hub in the network of data science researchers across Africa and strengthen the African data science community. #DSA2024Nyeri https://www.datascienceafrica.org/dsa2024nyeri/blog/summer-school

Guidelines for creating datasets and models from MIMIC

News from: MIMIC-IV v2.2.

April 24, 2024

We recognize that there is value in creating datasets or models that are either derived from MIMIC or which augment MIMIC in some way (for example, by adding annotations). Here are some guidelines on creating these datasets and models:

Any derived datasets or models should be treated as containing sensitive information. If you wish to share these resources, they should be shared on PhysioNet under the same agreement as the source data.
If you would like to use the MIMIC acronym in your project name, please include the letters “Ext” (for example, MIMIC-IV-Ext-YOUR-DATASET"). Ext may either indicate “extracted” (e.g. a derived subset) or “extended” (e.g. annotations), depending on your use case.

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