A Comprehensive Study on Machine Learning Algorithms for detection and Classification of Parkinson’s disease

Abstract: In recent years, significant progress has been made in developing more accurate and efficient machine learning algorithms for detection of medical images. This study highlights the imperative role of machine learning & deep learning algorithms in enabling efficient and accurate detection in the field of medical imaging. It focuses on several key studies pertaining to the application of machine learning methods to the Parkinson’s disease. PD is a neurodegenerative disorder that affects voluntary movements. The movement difficulty is due to lack of a chemical called dopamine produced by doparninergic neurons in brain. Henceforth the study is based on the classical machine learning algorithms such as supervised, unsupervised and reinforcement algorithms. In addition, several problems and research objectives which is related to the Parkinson’s disease are probed.

Keywords: Parkinson’s disease, Machine learning, Deep learning.