The Prediction of Venous Thromboembolism Using Artificial Intelligence and Machine Learning in Lower Extremity Arthroplasty: A Systematic Review

Abstract

AI and machine learning models, particularly extreme gradient boosting, exhibit significant potential in predicting VTE after lower extremity arthroplasty, outperforming traditional clinical prediction tools. Yet, the need for external validation and high-quality, generalizable datasets remains critical before these models can be widely implemented in clinical practice. The study underscores the role of AI in preoperative planning to enhance patient outcomes in orthopaedic surgery.

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