Parkinsons-Detector
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Detect the onset of possible risk of Parkinson's disease with the help of clinical data using Machine Learning Models.
Parkinson's Disease Predictor
Problem :
Parkinson's disease is a progressive disorder that affects the nervous system and the parts of the body controlled by the nerves. Symptoms start slowly. The first symptom may be a barely noticeable tremor in just one hand. Tremors are common, but the disorder may also cause stiffness or slowing of movement.
Solution:
This Web app will help you to predict whether a person has chances of cardiac arrest or is prone to get it in future by analysing the values of several features using the Decision Tree Classifier.
Idea:
Building an application that can predict the occurrence of a cardiac arrest or the possible causes of it by indicating the highly relevant factors.
Layout
├───images
├───Tabs
│ └───__pycache__
| └─── home.py
| └─── data.py
| └─── predict.py
| └─── visualize.py
└───__pycache__
└─── main.py
└─── Parkinson.csv
└─── web_functions.py
└─── requirements.txt
└─── Procfile
└─── setup.sh
Note:
Incase the application demo doesn't start real quick, you can get an idea about how it looks like from the screenshots