A clinical prediction model based on interpretable machine learning algorithms for prolonged hospital stay in acute ischemic stroke patients: a real-world study

A clinical prediction model based on interpretable machine learning algorithms for prolonged hospital stay in acute ischemic stroke patients: a real-world study

ObjectiveAcute ischemic stroke (AIS) brings an increasingly heavier economic burden nowadays. Prolonged length of stay (LOS) is a vital factor in healthcare expenditures. The aim of this study was to predict prolonged LOS in AIS patients based on an interpretable machine learning algorithm.MethodsWe...

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Bibliographic Details
Main Authors: Kai Wang, Qianmei Jiang, Murong Gao, Xiu’e Wei, Chan Xu, Chengliang Yin, Haiyan Liu, Renjun Gu, Haosheng Wang, Wenle Li, Liangqun Rong
Format: Article
Language:English
Published: Frontiers Media S.A. 2023-11-01
Series:Frontiers in Endocrinology
Subjects:
prolonged hospital stay
stroke
machine learning
prediction model
SHAP (SHapley Additive exPlanations)
Online Access:https://www.frontiersin.org/articles/10.3389/fendo.2023.1165178/full

Internet

https://www.frontiersin.org/articles/10.3389/fendo.2023.1165178/full

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