A Survey on Machine Learning Techniques for Parkinson's Disease Diagnosis and Classification

摘要

Disease diagnosis and prediction using data mining techniques are emerging as a research area with different tools and techniques. Parkinson's disease is one of the main disorders of the central nervous system. Disease diagnosis and classification from the digital data is becoming one of the major concerns of health care data mining. Researches use many technologies like machine learning, image analysis, signal analysis and device based techniques to examine the disease data from various sources. There is a need to analyze the unstructured large data using data mining. There are several tools and techniques to achieve this. This survey focuses on the various tools and techniques used for Parkinson's data analysis and classification, and finally provide an outline to overcome the problems of those techniques.