학술논문
Development of deep-learning models for real-time anaerobic threshold and peak VO2prediction during cardiopulmonary exercise testing
Document Type
Article
Author
Source
European Journal of Preventive Cardiology; March 2024, Vol. 31 Issue: 4 p448-457, 10p
Subject
Language
ISSN
20474873; 20474881
Abstract
Cardiopulmonary exercise testing can be used to evaluate the condition of patients with heart failure during exercise.Developed deep-learning models can accurately predict a patient’s anaerobic threshold in real time and peak oxygen uptake.The models can be used by clinicians for more objective and accurate assessments in real time, expanding the utility of cardiopulmonary exercise testing.Graphical Abstract