Nomogram and Machine Learning Models Predict 1-Year Mortality Risk in Patients With Sepsis-Induced Cardiorenal Syndrome

OBJECTIVE: Early prediction of long-term outcomes in patients with sepsis-induced cardiorenal syndrome (CRS) remains a great challenge in clinical practice. Herein, we aimed to construct a nomogram and machine learning model for predicting the 1-year mortality risk in patients with sepsis-induced CR...

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Detalles Bibliográficos
Autores principales: Liu, Yiguo, Zhang, Yingying, Zhang, Xiaoqin, Liu, Xi, Zhou, Yanfang, Jin, Yun, Yu, Chen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Medicine
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9099150/
https://www.ncbi.nlm.nih.gov/pubmed/35573024
http://dx.doi.org/10.3389/fmed.2022.792238

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9099150/
https://www.ncbi.nlm.nih.gov/pubmed/35573024
http://dx.doi.org/10.3389/fmed.2022.792238

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