Research progress on the application of machine learning in predictive modeling of venous thrombo-embolism risk in orthopedics

VernacularTitle:机器学习在骨科静脉血栓栓塞症风险预测模型中的应用研究进展
Author: Ruiting LIU ¹ ; Suli XIE ; Weiwei FENG ; Li SONG ; Yi LI ; Mengshuang LYU ; Xican ZHENG
Author Information

1. 新乡医学院护理学院,河南新乡 453003
Keywords: machine learning; venous thromboembolism; risk model
From: Journal of Xinxiang Medical College 2024;41(6):590-595
CountryChina
Language:Chinese
Abstract: Venous thromboembolism(VTE)is a prevalent complication in orthopedics.In recent years,machine learning has been widely applied in orthopedics.The essence of machine learning lies in utilizing algorithms to analyze vast amounts of data and construct risk prediction models that can accurately forecast unknown clinical outcomes.By integrating high-risk factors,machine learning aids medical professionals in precisely identifying and screening individuals with a high risk of VTE and offering them timely individualized interventions.This article reviews the concept and classification of machine learning,the advantages of machine learning in enhancing model prediction ability,and the current application status of machine learning in constructing risk prediction models for patients with VTE.