Atrial Fibrillation Detection During Sepsis: Study on MIMIC III ICU Data

• Published in: IEEE journal of biomedical and health informatics Vol. 24; no. 11; pp. 3124 - 3135
• Main Authors: Bashar, Syed Khairul, Hossain, Md Billal, Ding, Eric, Walkey, Allan J., McManus, David D., Chon, Ki H.
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.11.2020; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Annotations; Atrial fibrillation; Atrial Fibrillation - diagnosis; Automation; Cardiac arrhythmia; Detection algorithms; EKG; Electrocardiography; Entropy; Entropy (Information theory); Feature extraction; Fibrillation; Heart Atria; Heart rate; Heart rate variability; Humans; ICU; Intensive care; Intensive Care Units; Learning algorithms; Machine learning; MIMICs; Morbidity; P waves; P-wave; Poincaré plot; Premature beat; Segments; Sepsis; Sepsis - diagnosis; Ventricle

Sepsis is defined by life-threatening organ dysfunction during infection and is one of the leading causes of critical illness. During sepsis, there is high risk that new-onset of atrial fibrillation (AF) can occur, which is associated with significant morbidity and mortality. As a result, computer a...