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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Detalles Bibliográficos
Autores principales: Zhu, Kun, Lin, Hongyuan, Yang, Xichun, Gong, Jiamiao, An, Kang, Zheng, Zhe, Hou, Jianfeng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9963974/
https://www.ncbi.nlm.nih.gov/pubmed/36826583
http://dx.doi.org/10.3390/jcdd10020087

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9963974/
https://www.ncbi.nlm.nih.gov/pubmed/36826583
http://dx.doi.org/10.3390/jcdd10020087

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