Predicting Parkinson’s Disease Using Analytical Algorithm: A Review

Parkinson's disease is a chronic condition that impacts both the nervous system as well as the body parts that are under the regulation of the nervous system. Parkinson's disease normally occurs in patients with bradykinesia, rigidity, hypokinesia, and tremor. Aside from a number of common symptoms, every individual will feel and show the condition in own unique way. ML and deep learning-oriented techniques is used to distinguish among individuals without Parkinson's disease and individuals with Parkinson's disease. This paper provides a detailed analysis of methods that use ML and deep learning for Parkinson's disease prediction. Additionally, a summary of the findings from various studies on the prediction of Parkinson's disease using ML and deep learning is presented in the literature review section of this paper. In this paper, we are presenting a new ML-based model that is Age Prediction in Parkinson's using the ML (APPML) Model to predict the next age category of people who will be affected by Parkinson's disease.