Supervised machine learning algorithms to predict the duration and risk of long-term hospitalization in HIV-infected individuals: a retrospective study

Supervised machine learning algorithms to predict the duration and risk of long-term hospitalization in HIV-infected individuals: a retrospective study

ObjectiveThe study aimed to use supervised machine learning models to predict the length and risk of prolonged hospitalization in PLWHs to help physicians timely clinical intervention and avoid waste of health resources.MethodsRegression models were established based on RF, KNN, SVM, and XGB to pred...

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Bibliografiske detaljer
Main Authors: Jialu Li, Yiwei Hao, Ying Liu, Liang Wu, Hongyuan Liang, Liang Ni, Fang Wang, Sa Wang, Yujiao Duan, Qiuhua Xu, Jinjing Xiao, Di Yang, Guiju Gao, Yi Ding, Chengyu Gao, Jiang Xiao, Hongxin Zhao
Format: Article
Sprog:English
Udgivet: Frontiers Media S.A. 2024-01-01
Serier:Frontiers in Public Health
Fag:
HIV
AIDS
machine learning
length of stay
risk factors
calibration curves
Online adgang:https://www.frontiersin.org/articles/10.3389/fpubh.2023.1282324/full

Internet

https://www.frontiersin.org/articles/10.3389/fpubh.2023.1282324/full

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