Prediction of Parkinson's Disorder: A Machine Learning Approach

Parkinson's Disease (PD) is a neurodegenerative disorder that affects the dopamine neurons. The study aimed at predicting the risk of developing Parkinson's Disease in individuals with REM sleep Behavior Disorder (RBD) and Early untreated Parkinson's Disease. Data was obtained from Charles University in Prague which consisted of 30 individuals with early untreated Parkinson's Disease, 50 individuals with REM sleep behavior disorder (RBD) and 50 healthy controls. Logit model was used to analyze the data. Further a Machine learning model was used to predict the risk of developing Parkinson's Disease. It is concluded that Logit models and Machine learning successfully predict the risk of Parkinson's Disease development.