An In-Hospital Mortality Risk Model for Elderly Patients Undergoing Cardiac Valvular Surgery Based on LASSO-Logistic Regression and Machine Learning

An In-Hospital Mortality Risk Model for Elderly Patients Undergoing Cardiac Valvular Surgery Based on LASSO-Logistic Regression and Machine Learning

Background: To preferably evaluate and predict the risk for in-hospital mortality in elderly patients receiving cardiac valvular surgery, we developed a new prediction model using least absolute shrinkage and selection operator (LASSO)-logistic regression and machine learning (ML) algorithms. Method...

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Bibliographic Details
Main Authors: Kun Zhu, Hongyuan Lin, Xichun Yang, Jiamiao Gong, Kang An, Zhe Zheng, Jianfeng Hou
Format: Article
Language:English
Published: MDPI AG 2023-02-01
Series:Journal of Cardiovascular Development and Disease
Subjects:
valvular heart disease
mortality risk
prediction models
LASSO-logistic regression
machine learning
Online Access:https://www.mdpi.com/2308-3425/10/2/87

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https://www.mdpi.com/2308-3425/10/2/87

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