Parkinson’s Disease Progression using the Deep Structured Algorithm

Abstract

Parkinson's disease is a degenerative brain illness that results in movements that are uncontrollable, coordination, balance problems, and stiffness. Early identification and treatment are critical since the illness proceeds in three phases. The aim of the project is to develop an application that uses a Convolutional Neural Network, a Deep Learning method, to analyse and predict if a patient has Parkinson's disease and at what stage of the illness they are infected. Using publicly accessible DaTScan datasets, we report a successful CNN Inception V3 model for properly recognizing and forecasting Parkinson's disease and its development.