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...

Full description

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

Similar Items

Similar Items