Challenge Open Access

Will Two Do? Varying Dimensions in Electrocardiography: the PhysioNet - Computing in Cardiology Challenge 2021

Matthew Reyna, Nadi Sadr, Erick Andres Perez Alday, Chengyu Liu, Salman Seyedi, Gari D Clifford

Will Two Do? Varying Dimensions in Electrocardiography: the PhysioNet/Computing in Cardiology Challenge 2021

challenge cardiac abnormalities competition classification multilead ecgs

Published: Dec. 24, 2020. Version: 1.0.0

Database Credentialed Access

Maternal fat ultrasound measurement and nutritional assessment during pregnancy: A dataset centered in gestational outcomes

Alexandre da Silva Rocha, Juliana Rombaldi Bernardi, Alice Schoffel, Daniela Kretzer, Salete Matos, José Antônio Magalhães, Marcelo Goldani

Dataset collected as part of a prospective study in which abdominal maternal fat tissue measurements were compared with outcomes during hospitalization for labor and delivery.

pregnancy ultrasound abdominal

Published: Dec. 4, 2020. Version: 1.0.0

Database Restricted Access

Smartphone-Captured Chest X-Ray Photographs

Po-Chih Kuo, ChengChe Tsai, Diego M Lopez, Alexandros Karargyris, Tom Pollard, Alistair Johnson, Leo Anthony Celi

Smartphone-captured CXR images including photographs taken from MIMIC-CXR and CheXpert, photographs taken by resident doctors, and photographs taken with different devices.

smartphone photograph cxr

Published: Sept. 27, 2020. 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, Chengyu Liu, Ashish Sharma, Salman Seyedi, Ali Bahrami Rad, Matthew Reyna, Gari Clifford

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: April 23, 2020. Version: 1.0.1