A new risk assessment model of venous thromboembolism by considering fuzzy population

A new risk assessment model of venous thromboembolism by considering fuzzy population

Abstract Background Inpatients with high risk of venous thromboembolism (VTE) usually face serious threats to their health and economic conditions. Many studies using machine learning (ML) models to predict VTE risk overlook the impact of class-imbalance problem due to the low incidence rate of VTE,...

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Bibliographic Details
Main Authors: Xin Wang, Yu-Qing Yang, Xin-Yu Hong, Si-Hua Liu, Jian-Chu Li, Ting Chen, Ju-Hong Shi
Format: Article
Language:English
Published: BMC 2024-12-01
Series:BMC Medical Informatics and Decision Making
Subjects:
Venous thromboembolism
Risk assessment
Machine learning
Fuzzy population
Online Access:https://doi.org/10.1186/s12911-024-02834-3
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https://doi.org/10.1186/s12911-024-02834-3

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