Resources


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

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

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

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 Credentialed Access

GOSSIS-1-eICU, the eICU-CRD subset of the Global Open Source Severity of Illness Score (GOSSIS-1) dataset

Jesse Raffa, Alistair Johnson, Tom Pollard, et al.

GOSSIS-1 is an in-hospital mortality prediction algorithm for critical care patients. GOSSIS-1 was trained using data from three countries. This dataset corresponds with the USA subset of the GOSSIS-1 dataset for the 2022 publication below.

icu critical care severity of illness global gossis apache mortality prediction benchmarking

Published: July 20, 2022. Version: 1.0.0

Model Credentialed Access

What's in a Note? Unpacking Predictive Value in Clinical Note Representations

Tristan Naumann, William Boag

Word vectors corresponding to the AMIA 2018 Informatics Summit paper of the same name.

Published: Jan. 7, 2018. Version: 0.1

Database Credentialed Access

GOSSIS-1-eICU, the eICU-CRD subset of the Global Open Source Severity of Illness Score (GOSSIS-1) dataset

Jesse Raffa, Alistair Johnson, Tom Pollard, et al.

GOSSIS-1 is an in-hospital mortality prediction algorithm for critical care patients. GOSSIS-1 was trained using data from three countries. This dataset corresponds with the USA subset of the GOSSIS-1 dataset for the 2022 publication below.

icu critical care severity of illness global gossis apache mortality prediction benchmarking

Published: July 20, 2022. Version: 1.0.0

Challenge Open Access

Classification of 12-lead ECGs: The PhysioNet/Computing in Cardiology Challenge 2020

Erick Andres Perez Alday, Annie Gu, Amit Shah, et al.

The goal of the 2020 PhysioNet - Computing in Cardiology Challenge is to design and implement a working, open-source algorithm that can automatically identify cardiac abnormalities in 12-lead ECG recordings.

Published: July 29, 2022. Version: 1.0.2

Visualize waveforms

Database Credentialed Access

MIMIC-III and eICU-CRD: Feature Representation by FIDDLE Preprocessing

Shengpu Tang, Parmida Davarmanesh, Yanmeng Song, et al.

Features and labels from MIMIC-III and eICU-CRD produced by FIDDLE, an EHR preprocessing pipeline.

preprocessing electronic health record machine learning

Published: April 28, 2021. Version: 1.0.0

Database Credentialed Access

MIMIC-III - SequenceExamples for TensorFlow modeling

Jonas Kemp, Kun Zhang, Andrew Dai

MIMIC-III data converted into TensorFlow SequenceExample format, for use in modeling pipelines.

tensorflow sequence modeling machine learning deep learning

Published: Sept. 29, 2020. Version: 1.0.0