Published on in Vol 5, No 1 (2021): Jan-Jun

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/18840, first published .
Development and Validation of an Automated Algorithm to Detect Atrial Fibrillation Within Stored Intensive Care Unit Continuous Electrocardiographic Data: Observational Study

Development and Validation of an Automated Algorithm to Detect Atrial Fibrillation Within Stored Intensive Care Unit Continuous Electrocardiographic Data: Observational Study

Development and Validation of an Automated Algorithm to Detect Atrial Fibrillation Within Stored Intensive Care Unit Continuous Electrocardiographic Data: Observational Study

Journals

  1. Chen B, Maslove D, Curran J, Hamilton A, Laird P, Mousavi P, Sibley S. A deep learning model for the classification of atrial fibrillation in critically ill patients. Intensive Care Medicine Experimental 2023;11(1) View
  2. Moghaddasi H, Hendriks R, van der Veen A, de Groot N, Hunyadi B. Classification of De novo post-operative and persistent atrial fibrillation using multi-channel ECG recordings. Computers in Biology and Medicine 2022;143:105270 View

Books/Policy Documents

  1. Dong Han , Fahimeh Mohagheghian , Ki H. Chon . Encyclopedia of Sensors and Biosensors. View