Resources


Database Contributor Review

HiRID, a high time-resolution ICU dataset

Martin Faltys, Marc Zimmermann, Xinrui Lyu, et al.

The HiRID database contains a large selection of all routinely collected data relating to patient admissions to the Department of Intensive Care Medicine of the Bern University Hospital, Switzerland (ICU).

icu clinical intensive care high resolution critical care machine learning

Published: Feb. 18, 2021. Version: 1.1.1

Database Contributor Review

HiRID, a high time-resolution ICU dataset

Martin Faltys, Marc Zimmermann, Xinrui Lyu, et al.

The HiRID database contains a large selection of all routinely collected data relating to patient admissions to the Department of Intensive Care Medicine of the Bern University Hospital, Switzerland (ICU).

icu clinical intensive care high resolution critical care machine learning

Published: Feb. 18, 2021. Version: 1.1.1

Challenge Restricted Access

WiDS (Women in Data Science) Datathon 2020: ICU Mortality Prediction

Meredith Lee, Jesse Raffa, Marzyeh Ghassemi, et al.

WiDS (Women in Data Science) Datathon 2020: ICU Mortality Prediction focuses on patient health. Join a team, explore the data, and share your insights: http://bit.ly/WiDSdatathon2020

mortality risk data science kaggle icu challenge predictive analytics women in data science

Published: Jan. 22, 2020. Version: 1.0.0

Challenge Open Access

Reducing False Arrhythmia Alarms in the ICU: The PhysioNet/Computing in Cardiology Challenge 2015

The 2015 PhysioNet/CinC Challenge aims to encourage the development of algorithms to reduce the incidence of false alarms in the Intensive Care Unit (ICU).

false alarm multiparameter icu challenge arrhythmia critical care tachycardia

Published: Feb. 15, 2015. Version: 1.0.0

Database Credentialed Access

Northwestern ICU (NWICU) database

Dana Moukheiber, William Temps, Bhadrappa Molgi, et al.

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

Challenge Restricted Access

WiDS (Women in Data Science) Datathon 2020: ICU Mortality Prediction

Meredith Lee, Jesse Raffa, Marzyeh Ghassemi, et al.

WiDS (Women in Data Science) Datathon 2020: ICU Mortality Prediction focuses on patient health. Join a team, explore the data, and share your insights: http://bit.ly/WiDSdatathon2020

mortality risk data science kaggle icu challenge predictive analytics women in data science

Published: Jan. 22, 2020. Version: 1.0.0

Challenge Open Access

Reducing False Arrhythmia Alarms in the ICU: The PhysioNet/Computing in Cardiology Challenge 2015

The 2015 PhysioNet/CinC Challenge aims to encourage the development of algorithms to reduce the incidence of false alarms in the Intensive Care Unit (ICU).

false alarm multiparameter icu challenge arrhythmia critical care tachycardia

Published: Feb. 15, 2015. Version: 1.0.0

Challenge Open Access

Predicting Mortality of ICU Patients: The PhysioNet/Computing in Cardiology Challenge 2012

The focus of the PhysioNet/CinC Challenge 2012 is to develop methods for patient-specific prediction of in-hospital mortality. Participants will use information collected during the first two days of an ICU stay to predict which patients survive the…

mortality prediction challenge ehr mimic

Published: Jan. 20, 2012. Version: 1.0.0

Database Open Access

VTaC: A Benchmark Dataset of Ventricular Tachycardia Alarms from ICU Monitors

Li-wei Lehman, Benjamin Moody, Lucas McCullum, et al.

VTaC is an annotated ventricular tachycardia (VT) arrhythmia alarm database containing over 5,000 waveform recordings with VT alarms from ICU monitors, with each alarm labeled as either true or false by at least two human expert annotators.

arrhythmia machine learning icu false alarms benchmark dataset ventricular tachycardia

Published: Oct. 1, 2024. Version: 1.0

Visualize waveforms

Database Open Access

VTaC: A Benchmark Dataset of Ventricular Tachycardia Alarms from ICU Monitors

Li-wei Lehman, Benjamin Moody, Lucas McCullum, et al.

VTaC is an annotated ventricular tachycardia (VT) arrhythmia alarm database containing over 5,000 waveform recordings with VT alarms from ICU monitors, with each alarm labeled as either true or false by at least two human expert annotators.

arrhythmia machine learning icu false alarms benchmark dataset ventricular tachycardia

Published: Oct. 1, 2024. Version: 1.0

Visualize waveforms