Parkinson's Disease Analysis Using Logistic Regression

Parkinson's disease is a neurological condition that worsens with time, recognized by symptoms like tremor, rigidity, postural impairment, speech changes and writing changes. At a clinical onset, the victims of this disease will lose extensive amounts of dopaminergic neurons. This paper proposes a method to search records in a huge dataset for indications of Parkinson's disease. The aim of the proposed work is to Import a large data, cleaning the data, Splitting the data into testing and training, Applying Logical Regression to analyze this data and predicting the chances of having the disease.