Parkinson’s disease occurs because of the decrease and insufficiency of dopamine cells over the time. Studies on computer-aided diagnosis systems that will help experts in making decisions for the early diagnosis of the disease remain up to date. Success has been achieved with computer aided diagnosis systems in a certain rate. The success rate varies according to the methods used, the data set and the optimization of the methods. In this study, parameter optimization of SVM classifier was performed to support the early diagnosis of Parkinson’s disease. The effect of different optimization methods that are current in the literature were compared on two different Parkinson’s disease data set. According to the results obtained, the highest accuracy rates vary according to the data set and optimization method. While Improved Chaotic Particle Swarm Optimization achieved high success in the first data set, Bat Algorithm achieved higher success in the other data set. While the success results obtained are better than some studies in the literature, they are at a level that can compete with some studies.

As in all fields, technological developments have started to be used in the field of medical diagnosis, and computer-aided diagnosis systems have started to assist physicians in their diagnosis. The success of computer-aided diagnosis methods depends on the method used; dataset, pre-processing, post-processing, etc. differ according to the processes. In this study, parameter optimization of support vector machines was performed with four different methods currently used in the literature to assist the physician in diagnosis. The success of each method was tested on two different Parkinson’s datasets and the results were compared within themselves and with the literature. According to the results obtained, the highest accuracy rates vary depending on the dataset and optimization method. While Improved Chaotic Particle Swarm Optimization achieved high success in the first dataset, Bat Algorithm achieved higher success in the other dataset. While the successful results obtained are better than some studies in the literature, they are at a level that can compete with some studies.