Inspiration

Medical problems always need a solution regardless of the era we live in. Having an automated system saves time that is required to do the complete diagnosis of the patient and based on the suggestions provided by the system we can only get the patient diagnosed for those diseases that are required.

What it does

This web app predicts the whether the person has diabetes, heart disease, liver disease, kidney disease, or back pain from the given inputs using the machine learning algorithm.

How we built it

Front End

  • Frontend is built only using HTML.
  • Styling is done using internal CSS and Javascript.

Back end

  • Backend is built using machine learning algorithms in Python and hosting it using Flask and Heroku.
  • Logistic Regression algorithms from the sklearn library were used for training and testing of the model.
  • Matplotlib, pandas and numpy were used for training the model.

How it works

  • First, the user enters the information and submits the form.
  • Then the data is sent to the respective trained model.
  • Then it passed through the trained model and sends the output accordingly.
  • Then according to the output given by the model, the result is shown to the user.

Challenges we ran into

  • The first challenge was to find the appropriate machine learning algorithm for the prediction as if the appropriate algorithm is not selected the output obtained would not be what the actual output was.
  • The second challenge was to get the dataset and preprocess it as it contains a lot of duplicates and null values which affects the accuracy of the model.
  • Using HTML and Javascript for styling was challenging as I don't have any experience in front-end development.

Accomplishments that we're proud of

  • Using HTML and Javascript for styling was challenging as I don't have any experience in frontend development I got to know about the basics of frontend development and also the importance of UI/UX for any application.
  • The fully functional website

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