Development and validation of a practical machine learning model to predict sepsis after liver transplantation

Development and validation of a practical machine learning model to predict sepsis after liver transplantation

AbstractBackground Postoperative sepsis is one of the main causes of mortality after liver transplantation (LT). Our study aimed to develop and validate a predictive model for postoperative sepsis within 7 d in LT recipients using machine learning (ML) technology.Methods Data of 786 patients receive...

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Bibliographic Details
Main Authors: Chaojin Chen, Bingcheng Chen, Jing Yang, Xiaoyue Li, Xiaorong Peng, Yawei Feng, Rongchang Guo, Fengyuan Zou, Shaoli Zhou, Ziqing Hei
Format: Article
Language:English
Published: Taylor & Francis Group 2023-12-01
Series:Annals of Medicine
Subjects:
Postoperative sepsis
liver transplantation
machine learning
early intervention
decision-making
Online Access:https://www.tandfonline.com/doi/10.1080/07853890.2023.2179104

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https://www.tandfonline.com/doi/10.1080/07853890.2023.2179104

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