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The primary risk factors for patients with Knee Osteoarthritis (KOA) were determined in this study, and a predictive model was developed using the data found. In order to comprehend the body of information regarding musculoskeletal-related diseases, a thorough study of relevant literature was conducted. One ailment that falls within the musculoskeletal category is knee osteoarthritis, and the risk factors were extracted and confirmed by medical professionals. clinical data encompassing characteristics tracked during KOA patients' treatment were gathered from Ile-Ife, Osun State, Nigeria at the OAU Teaching Hospital Complex (OAUTHC), , as well as from a few other people Utilizing questionnaires, . For this investigation, the entire dataset comprising data on 83 patients was used. WEKA software was used to compare four supervised machine learning techniques so as to create the model. The accuracy of the was 97.59% when examining the 36 originally identified attributes without selecting any featue. The outcomes additionally demonstrated The minimal amount of variables pertinent to the osteoarthritis condition of the knee. Subsequent findings demonstrated the relevance of each feature found in order to create a prognosis model for knee osteoarthritis that is both effective and efficient. Age is the most important factor for KOA, according to the study's findings, and all 36 characteristics were found to be useful in forecasting the likelihood of Knee Osteoarthritis..
Oladejo et al. (Tue,) studied this question.