PhysioNet

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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 Open Access

PTB-XL, a large publicly available electrocardiography dataset

Patrick Wagner, Nils Strodthoff, Ralf-Dieter Bousseljot, Wojciech Samek, Tobias Schaeffter

The PTB-XL ECG dataset is a large dataset of 21801 clinical 12-lead ECGs from 18869 patients of 10 second length. The raw signal data has been annotated by up to two cardiologists with 71 different ECG statements and is supplemented by rich metadata.

electrocardiography ptb-xl ptb ecg

Published: Nov. 9, 2022. Version: 1.0.3

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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

MIMIC-CXR Database

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

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

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

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 artificial intelligence dataset

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

CAD-Chest: Comprehensive Annotation of Diseases based on MIMIC-CXR Radiology Report

Mengliang Zhang, Xinyue Hu, Lin Gu, Tatsuya Harada, Kazuma Kobayashi, Ronald Summers, Yingying Zhu

The CAD-Chest dataset provides comprehensive annotations of disease, including disease severity, uncertainty, and location based on the MIMIC-CXR radiologist reports.

chesr x-ray disease label

Published: Dec. 8, 2023. Version: 1.0

Database Credentialed Access

Annotation dataset of social determinants of health from MIMIC-III Clinical Care Database

Marco Guevara, Shan Chen, Spencer Thomas, Danielle Bitterman

Annotation dataset of social determinants of health from MIMC-III Clinical Care Database notes.

natural language processing social determinants of health

Published: Nov. 24, 2023. Version: 1.0.0

Database Open Access

Simulated Obstructive Disease Respiratory Pressure and Flow

Jaimey Anne Clifton, Ella Frances Sophia Guy, Trudy Caljé-van der Klei, Jennifer Knopp, James Geoffrey Chase

Outlined is a pressure, flow, and volume dataset using a using a modular device to simulate the effects of obstructive pulmonary disease in healthy people. 20 healthy subjects were included in this dataset.

Published: Nov. 13, 2023. Version: 1.0.0

Database Open Access

ScientISST MOVE: Annotated Wearable Multimodal Biosignals recorded during Everyday Life Activities in Naturalistic Environments

João Areias Saraiva, Mariana Abreu, Ana Sofia Carmo, Hugo Plácido da Silva, Ana Fred

Multimodal (ECG, EMG, EDA, PPG, TEMP, ACC) biosignal dataset of everyday activities. Created with 3 wearable devices based on ScientISST Sense and Empatica E4.

multimodal wearable run uncontrolled environments jump greet lift walk gesticulate

Published: Nov. 13, 2023. Version: 1.0.0

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Challenge Credentialed Access

BioNLP Workshop 2023 Shared Task 1A: Problem List Summarization

Yanjun Gao, Dmitriy Dligach, Timothy Miller, Majid Afshar

This is the data storage for BioNLP Workshop Shared Task 1A: Problem List Summarization.

bionlp clinical natural language processing electronic health record summarization

Published: Nov. 12, 2023. Version: 2.0.0

Database Open Access

Respiratory dataset from PEEP study with expiratory occlusion

Ella Frances Sophia Guy, Jaimey Anne Clifton, Trudy Caljé-van der Klei, Rongqing Chen, Jennifer Knopp, Knut Moeller, James Geoffrey Chase

Outlined is a pressure, flow, volume, dynamic circumference, and EIT assessed aeration dataset from resting breathing with REO at increasing CPAP PEEP settings. Vapers, asthmatics, smokers, and otherwise healthy people were included in the trial.

Published: Nov. 10, 2023. Version: 1.0.0

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News

DARPA Triage Challenge: Qualification extended through Nov 27

Nov. 6, 2023

Qualification for the DARPA Triage Challenge has been extended through November 27, 2023 at 23:59. We encourage you to join the challenge as a self-funded team for the Systems, Virtual and Data Competitions. You may compete in one or more challenge tracks, where qualification must be entered for each track individually.

To register, please visit the Team Qualification Portal at: https://events.sa-meetings.com/DTCTeamPortal/.

For more information on the challenge, see: https://triagechallenge.darpa.mil/ or contact TriageChallenge@darpa.mil.

Join the DARPA Triage Challenge! Deadline for registration: Monday 13 November, 2023

Oct. 18, 2023

The Defense Advanced Research Projects Agency (DARPA), a research and development agency within the Department of Defense, is seeking competitors for a new medical response challenge. The DARPA Triage Challenge aims to drive breakthrough innovations that improve medical response time during mass casualty incidents in complex military and civilian settings, especially when medical resources are limited relative to the need.

The challenge includes a series of technical challenge events to drive breakthrough innovations in the identification of physiological features (signatures) of injury, and help medical responders perform scalable, timely, and accurate triage. The challenge has two primary triage competitions – Systems and Virtual – and a secondary triage Data competition. The Systems and Virtual competitions focus on stand-off sensing of physiological data using autonomous platforms – uncrewed aerial and ground vehicles – during primary triage. Competitors will conduct real-time sensor data analysis to identify casualties for urgent hands-on evaluation by medical personnel.

Relevant to the PhysioNet community, the Data competition seeks to identify physiological signatures of injury derived from data captured by non-invasive sensors (contact-based or stand-off). Such advances could accelerate responders’ anticipatory decisions and prioritization for medical care during secondary triage. Competitors will attempt to develop algorithms that detect signatures in these data streams to provide decision support appropriate for austere and complex pre-hospital settings. Of particular interest are early signatures indicating a need for life-saving interventions against conditions that medics are trained and equipped to treat during secondary triage, such as hemorrhage and airway injuries.

The Data competition will use DARPA-provided de-identified, multi-modal physiological data from trauma patients across diverse settings and cohorts provided by the DARPA Research Infrastructure for Trauma with Medical Observations effort. Data types include, but are not limited, to: photoplethysmography (PPG) waveforms, medical procedures, imaging results and video footage during prehospital helicopter transport and in the trauma bay.

Prizes for year one:

Systems Competition: Up to $200K Prize pool
Virtual Competition: Up to $100K Prize pool
Data Competition: Up to $200K Prize pool

Total Prizes $7M over three challenges

DARPA is currently seeking self-funded competitors. Join us by registering on the Qualification Portal, now through Nov. 13, 2023.

For more information visit the DARPA Triage Challenge website.

Call for partners interested in synthetic patient data

Sept. 27, 2023

The Google Research team is looking for partners to understand the needs and requirements for synthetic data. They have capabilities to generate both structured and unstructured patient data as well as images for infrastructure testing and medical research. Please contact us if you are interested in the partnership.

MIMIC-IV-ECG module released

News from: MIMIC-IV-ECG: Diagnostic Electrocardiogram Matched Subset v1.0.

Sept. 15, 2023

The MIMIC-IV-ECG module is now available. This module contains approximately 800,000 diagnostic electrocardiograms across nearly 160,000 unique patients. The vast majority of ECGs for patients who appear in the MIMIC-IV Clinical Database are included. The patients in MIMIC-IV-ECG have been matched against the MIMIC-IV Clinical Database, making it possible to link to information across the MIMIC-IV modules. When a cardiologist report is available for a given ECG, we provide information for linking to it.

FFA-IR dataset is unavailable until further notice

News from: FFA-IR: Towards an Explainable and Reliable Medical Report Generation Benchmark v1.0.0.

Sept. 6, 2023

The authors of the FFA-IR dataset have asked for downloads to be disabled until further notice to adhere with local policy changes. We apologize for the inconvenience and hope to make the files available again in the future.

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