Abstract
Parkinson disease is a common mass measurement problem in public health. Machine-based learning is used to differentiate between the stable and Parkinson's disease people. This paper provides a comprehensive review of the Parkinson disease buying estimate using machine-based learning approaches. A brief introduction is given to various methods of artificial intelligence, focused on strategies used to predict Parkinson disease. This paper also offers a study of the results obtained by using MRMR feature selection algorithms with four classifications for Parkinson’s disease detection using python
Highlights
Parkinson disease is a developingirregularity of the nervous system which affects movement.It is a condition which affects the brain that controls how your body moves
Primary Parkinson: Most patients diagnosed with Parkinson disease have what is termed primary parkinsonism or Parkinson idiopathic disease
The reason of the condition is known in these cases, and even though differentiating the secondary parkinsonism and parkinson disease is very difficult, a main difference is that patients who are affected by the secondary parkinsonism didn’t react good to dopaminergic drugs like as levodopa
Summary
Parkinson disease is a developingirregularity of the nervous system which affects movement.It is a condition which affects the brain that controls how your body moves. It can get on so slowly that you don't even notice that first. After some time,it starts with bit of hand shakiness that can have an impact on how you talk, walk, think and sleep.When you are 60 and older you are more likely to get it. It may begin when you are younger, but it doesn’t occur often.Parkinson disease is not cured but it canbe treated and get support tomanage the Parkinson disease symptoms
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