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Detect the onset of possible risk of Parkinson's disease with the help of clinical data using Machine Learning Models.

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Parkinson's Disease Predictor

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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

image image image image image image

Made with 💙 by:

maker

MAINAK CHAUDHURI