Machine Learning Model Based on Transthoracic Bioimpedance and Heart Rate Variability for Lung Fluid Accumulation Detection: Prospective Clinical Study

• Published in: JMIR medical informatics Vol. 8; no. 8; p. e18715
• Main Authors: Reljin, Natasa, Posada-Quintero, Hugo F, Eaton-Robb, Caitlin, Binici, Sophia, Ensom, Emily, Ding, Eric, Hayes, Anna, Riistama, Jarno, Darling, Chad, McManus, David, Chon, Ki H
• Format: Journal Article
• Language: English
• Published: Toronto JMIR Publications 01.08.2020
• Subjects: Algorithms; Biomarkers; Carbon black; Cellular telephones; Edema; Electric currents; Electrodes; Heart failure; Heart rate; Machine learning; Original Paper; Pacemakers; Skin

Background: Accumulation of excess body fluid and autonomic dysregulation are clinically important characteristics of acute decompensated heart failure. We hypothesized that transthoracic bioimpedance, a noninvasive, simple method for measuring fluid retention in lungs, and heart rate variability, a...