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This web app helps to predict the Parkinson disease status of a patient. It can be helpful for any test center who can upload there patient details and easily get a prediction.

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Mahima-Rabbi-Mohi/Parkinson-Detection-Web-App

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Parkinson Detection (Web-App)

In order to enhance the standard of patient care, machine learning is being leveraged in this project to evaluate and manipulate healthcare data. In the backend, advanced ML algorithms have been used to diagnose Parkinson's disease. Then, a good amount of advanced features were included in the front end to make this web application simple to use. Simply, This web app helps to predict the Parkinson's disease (status) of a patient. It can be used in any medical test center to fast-track there report generator.

To know more about Parkinson's Disease visit https://www.nhs.uk/conditions/parkinsons-disease/

  • Only by uploading an input CSV containing all the required reports, a detailed updated CSV file including the patient status can be generated easily.

WorkFlow

  • Collected Dataset from Kaggle
  • Pre-Processed Dataset (Scaling)
  • Applied Support Vector Machine (SVM) Algorithm
  • Created Web-App and connected it

Demo video

Parkinson_web_app.mp4

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This web app helps to predict the Parkinson disease status of a patient. It can be helpful for any test center who can upload there patient details and easily get a prediction.

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