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Comparative analysis of supervised machine learning models for predicting surgeon fixation choice in total knee
Hyunkyu Ko1, Brook I Martin2, Christopher E Pelt2
1Department of Orthopaedics, University of Utah, University Orthopaedic Center, 590 Wakara Way, Salt Lake City, UT, 84108, USA. hyunkyu.ko@utah.edu.
BMC Medical Informatics and Decision Making
|February 12, 2026
Summary
No abstract available in PubMed .
Keywords:
Cemented TKAExtreme gradient boosting (XGBoost)Least absolute shrinkage and selection Operator (LASSO)Pulmonary embolism prevention after hip and knee replacement trial (PEPPER)Random Forest (RF)Shapley additive explanations (SHAP)Supervised machine learning (SML)Support vector machines (SVM)Related Concept Videos
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