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heart-disease-predictor's Introduction

HeartFlex - Heart Disease Predictor Screen Shot 2020-07-03 at 5 41 08 PM

Description

  • An app developed using Flutter to predict the risk of having an heart attack.
  • Uses a hyperparameter tuned LogisticRegression machine learning model with an accuarcy of 86% to predict the result.
  • Uses a total of thirteen paramaters (details can be found in folder machine_learning_model) as the basis of scoring.
  • A Python backend is used to load the trained machine learning model and provide the result in json format to the Flutter frontend

Visuals

final_pls_1

final_pls_2


Requirements

  • In order for the code to work:

    • Please ensure to run the python backend to access the result of the machine learning model
  • To run on a real device please run the following commands on the terminal and replace the url in the code with the url derived

    • brew cask install ngrok
    • ngrok http 5000

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