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A health diagnostics Next.js app that use machine learning to assess the risk levels of adults getting type 2 diabetes

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stephmukami/iprevent-diabetes-risk-prediction

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iPrevent

A machine learning approach to predicting Type 2 Diabetes.

Key FeaturesHow To UseLicense

Key Features

  • Authentication and authorization
    • Create your own account and log in
  • Risk prediction
    • Fill in information as directed to feed our random forest machine learning model
    • Find out the percentage risk of being diagnosed with Type 2 diabetes
  • Intepretability Analysis
    • Get a list of health attributes that contributed to your risk prediction
  • Relevant recommendations
    • Obtain some next steps to improve your health habits based on your risk prediction *Adherence to responsible computing aspects
    • Deactivate and delete your account to maintain your privacy
    • Send a message of ny provacy concerns you have

How To Use

To clone and run this application, you'll need Git and Node.js (which comes with npm) Python and Flask installed on your computer. From your command line:

# Clone this repository
$ git clone https://github.com/stephmukami/iprevent

# Go into the repository
$ cd iprevent

# Install dependencies
$ npm install

# Run the app
$ npm start

# Run the ml backend
$ cd server
$ python app.py

Note If you're using Linux Bash for Windows, see this guide or use node from the command prompt.

License

MIT


Meet the Team :

Stephanie Mukami

GitHub @stephmukami  · 

Brain Macharia

GitHub @RyanSmoak  · 

Justine Kebiba

GitHub @onsarigo  · 

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A health diagnostics Next.js app that use machine learning to assess the risk levels of adults getting type 2 diabetes

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