Leveraging Machine Learning for Personalized Knee Replacement Surgery: Predictive Models and Outcomes

Abstract

The knee plays vital role in human body movement. Therefore, it is very important that once these damage in knee starts, the early detection should be done for proper treatment or knee replacement. This work tries its best to identify the most vital aspects in more accurate manner for detection of knee condition for the replacement or treatment. The paper use advanced models such as CatBoost, KNN and XGBoost. The CatBoost is able to achieve for getting accuracy of 97.78 %.