Development of Machine Learning Model for VO_2max Estimation Using a Patch-Type Single-Lead ECG Monitoring Device in Lung Resection Candidates.

ABSTRACT: A cardiopulmonary exercise test (CPET) is essential for lung resection. However, performing a CPET can be challenging. This study aimed to develop a machine learning model to estimate maximal oxygen consumption (VO_2max) using data collected through a patch-type single-lead electrocardiogram (ECG) monitoring device in candidates for lung resection. This prospective, single-center study included 42 patients who underwent a CPET at a tertiary teaching hospital from October 2021 to July 2022. During the CPET, a single-lead ECG monitoring device was applied to all patients, and the results obtained from the machine-learning algorithm using the information extracted from the ECG patch were compared with the CPET results. According to the Bland-Altman plot of measured and estimated VO<

SUBMITTER: Lee HA 

PROVIDER: S-EPMC10648477 | biostudies-literature | 2023 Oct

REPOSITORIES: biostudies-literature