Knee osteoarthritis classification using support vector machine AdaBoost and decision tree AdaBoost

Abstract

Osteoarthritis is a chronic joint disease of cartilage that often occurs in elderly people. One of the joints that can be infected this disease is in the knee. Older people often underestimate painful feeling around their joint or do not realize that they have been affected by knee osteoarthritis, so the knee osteoarthritis disease becomes more chronic. According to some studies, preventive measurements from early stage are very crucial to overcome the disease. One of the preventive measurements to overcome knee osteoarthritis is to detect the current stage of the disease, so the knee osteoarthritis patient can have the right treatment. Knee osteoarthritis was detected by classify the stage of knee osteoarthritis patients by using SVMAdaBoost and DTAdaBoost. The objective in this research is to compare SVMAdaBoost and DTAdaBoost based on classification accuracy from both methods. The results showed that the classification accuracy given SVMAdaBoost is 85.714 % and DTAdaBoost is 75 %.