Abstract
This research provides a comprehensive comparison of different machine learning (k-means clustering) algorithms as applied to datasets derived from Anterior Cruciate Ligament Reconstruction (ACLR) patients. The study aimed to find optimal clustering methodologies for ACLR patients’ data, focusing on knee measurements and their association with demographic factors such as age and physical activities. The researchers gathered data from 20 ACLR patients and 20 normal participants in Saudi Arabia’s eastern region. The researchers used machine learning algorithms (K-means clustering) for MATLAB programs.
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