Parkinson disease prediction: “A machine learning approach”

Abstract

Dopamine-producing neurons are predominantly affected in a certain area of the brain, while neurodegenerative disorder happen in the human body, which calls Parkinson's disease (PD)

The person who is affected by this disease can realize very hardly the hard stage of this disease as its syndromes usually develop gradually over years. Different person phage the different stage of it as its symptom’s progression vary from person to person. People who go through this disease may feel some problems like:

Vibration, mainly it happens during the resting periods in the hands. Other problems also can happen like the slowness of movements, limb raggedy, gait and balance problems, etc. That is why we need a proper process based on all these things where it will give us the right accuracy. And to help us out there is no better option than using machine learning.

We have Created the data table based on the information taken from 31 individuals.23 of people carrying Parkinson's disease (PD) were included among the 31 people in that measure in each column.195 voice recordings were taken from these 31 people. These recordings can be found in each of the rows. There is a certain purpose of that survey. We can individualize the PD patients from the other people who are not carrying the disease. There is another column situated in the table according to medical status. 0 is the set for healthy and 1 is for PD people in the column.

We can predict that the people are rather healthy or carrying the disease. Which is our primary intention.