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This is a Deep Learning model to predict whether the person has Parkinson's disease or not. This project won the "best AI and Data Science project" at the Equinox hackathon.

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What is Parkinson's Disease?

Parkinson's disease is a brain disorder that leads to shaking, stiffness, and difficulty with walking, balance, and coordination. Parkinson's symptoms usually begin gradually and get worse over time. As the disease progresses, people may have difficulty walking and talking.

What was the approach?

Considering the COVID scenario we wanted to make the diagnosis simple were to detect the presence of Parkinson's disease, the person is supposed to upload two images where he or she had drawn a wave and a spiral based on which the detection occurs. These are some of the example images on which the model is being trained and tested.

Spiral-Healthy

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Spiral-Parkinson Affected

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Waves-Healthy

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Waves-Parkinson Affected

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Tree structure

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CNN model

For the detection we had used CNN architecture which can be summarised as:

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Accuracy

The following was the accuracy vs epoch graph obtained for spiral, and wave respectively:

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Why do you need to use this application?

Considering the pandemic situation it is necessary to maintain social distancing and also avoid unnecessary visits to the hospital. The perk of this application is you ask the person to draw just two images where one is spiral and the other is a wave and based on this the output is combined from their respective neural network. This is easy to use and access.

Download the trained Model:

Go to Google Drive

About

This is a Deep Learning model to predict whether the person has Parkinson's disease or not. This project won the "best AI and Data Science project" at the Equinox hackathon.

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