XGBoost-based machine learning test improves the accuracy of hemorrhage prediction among geriatric patients with long-term administration of rivaroxaban

XGBoost-based machine learning test improves the accuracy of hemorrhage prediction among geriatric patients with long-term administration of rivaroxaban

Abstract Background Hemorrhage is a potential and serious adverse drug reaction, especially for geriatric patients with long-term administration of rivaroxaban. It is essential to establish an effective model for predicting bleeding events, which could improve the safety of rivaroxaban use in clinic...

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Bibliographic Details
Main Authors: Cheng Chen, Chun Yin, Yanhu Wang, Jing Zeng, Shuili Wang, Yurong Bao, Yixuan Xu, Tongbo Liu, Jiao Fan, Xian Liu
Format: Article
Language:English
Published: BMC 2023-07-01
Series:BMC Geriatrics
Subjects:
Direct oral anticoagulants
Rivaroxaban
Hemorrhage
Risk factor analysis
XGBoost
Online Access:https://doi.org/10.1186/s12877-023-04049-z

Internet

https://doi.org/10.1186/s12877-023-04049-z

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