Utilizing Circadian Heart Rate Variability Features and Machine Learning for Estimating Left Ventricular Ejection Fraction Levels in Hypertensive Patients: A Composite Multiscale Entropy Analysis

Utilizing Circadian Heart Rate Variability Features and Machine Learning for Estimating Left Ventricular Ejection Fraction Levels in Hypertensive Patients: A Composite Multiscale Entropy Analysis

Background: Early identification of left ventricular ejection fraction (LVEF) levels during the progression of hypertension is essential to prevent cardiac deterioration. However, achieving a non-invasive, cost-effective, and definitive assessment is challenging. It has prompted us to develop a comp...

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Bibliographic Details
Main Authors: Nanxiang Zhang, Qi Pan, Shuo Yang, Leen Huang, Jianan Yin, Hai Lin, Xiang Huang, Chonglong Ding, Xinyan Zou, Yongjun Zheng, Jinxin Zhang
Format: Article
Language:English
Published: MDPI AG 2025-07-01
Series:Biosensors
Subjects:
heart rate variability
electrocardiography
machine learning
composite multiscale entropy
Online Access:https://www.mdpi.com/2079-6374/15/7/442
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