Machine learning: an aid in detection of neurodegenerative disease Parkinson

Abstract

Parkinson is the most common neurodegenerative disease among the elderly people older than 65 years. An appropriate computer-assisted decision support system is the need in diagnosis and evaluation of the progression of Parkinson (PD). It is vital to early diagnose the disease. Machine Learning can assist to classify a normal and patient with Parkinson disease and also in optimising the treatment of the disease. It can be used to determine the various stages of the disease by categorising the symptoms including motor and non-motor symptoms. In this study, we assess the potential of Machine Learning for determining the progression of Parkinson disease and detecting it.