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.
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