Machine learning models in heart failure with mildly reduced ejection fraction patients

Machine learning models in heart failure with mildly reduced ejection fraction patients

ObjectiveHeart failure with mildly reduced ejection fraction (HFmrEF) has been recently recognized as a unique phenotype of heart failure (HF) in current practical guideline. However, risk stratification models for mortality and HF re-hospitalization are still lacking. This study aimed to develop an...

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Bibliographic Details
Main Authors: Hengli Zhao, Peixin Li, Guoheng Zhong, Kaiji Xie, Haobin Zhou, Yunshan Ning, Dingli Xu, Qingchun Zeng
Format: Article
Language:English
Published: Frontiers Media S.A. 2022-11-01
Series:Frontiers in Cardiovascular Medicine
Subjects:
heart failure
machine learning (ML)
heart failure with mildly reduced ejection fraction
random forest (RF)
LASSO Cox regression analysis
Online Access:https://www.frontiersin.org/articles/10.3389/fcvm.2022.1042139/full

Internet

https://www.frontiersin.org/articles/10.3389/fcvm.2022.1042139/full

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