Abstrait

Parkinson Diagnosis using Neural Network: a Survey

Sanjivani Bhande , Dr. Ranjan Raut

Clinical decisions lead to unwanted biases, errors and excessive medical costs which affect the quality of services provided to patients. Accurate detection is highly essential for treatment planning which can minimize the fatal results. Accurate results can be obtained through Artificial Neural Network. Besides being accurate, these techniques must converge quickly in order to apply them for real time applications. Parkinson’s disease (PD) is a common disease of central nervous system among the elderly & its complex symptoms bring up some difficulties for the clinical diagnosis. PD is a progressive neurological disorder characterized by tremor, rigidity & slowness of movements. It is associated with progressive neuronal loss in the substantia nigra & other brain structures. This situation leads towards the need to develop a Decision Support System for PD. This paper presents a comparative analysis to illustrate merits of various available research techniques. The aim of the survey is to introduce for those new to the field, an overview for those working in the field & a reference for those searching for literature on a specific application.