ABSTRACT
This chapter is a comprehensive literature review as a comparative study of machine learning algorithms in Parkinson’s disease diagnosis. The recent studies in the literature that are conducted on different datasets containing both handwriting and voice datasets of Parkinson’s disease are analyzed. The fact that Parkinson data are mostly suitable for machine learning analysis, this situation triggers the authors’ tendency to research this area. The Parkinson detection literature inclines through deep learning algorithms due to the automatic anomaly detection aspect. The recent studies go toward an automated disease detection and classification system. Therefore, this chapter also aims to include papers that are using deep learning methods for Parkinson’s disease diagnosis. The authors strongly believe that it will be a handbook for researchers who are eager to accomplish research on this subject and it will be very beneficial.
