Our graduation project is a web application that uses a machine learning model to predict whether a person has diabetes or not based on their health metrics. We built the web application using Flask as the backend and HTML, CSS, and JavaScript as the frontend. Features
The web application has the following features:
User interface: Users can enter their health metrics, such as BMI, blood pressure, and glucose level, into the web application's form.
Prediction: The machine learning model predicts whether the user has diabetes or not based on their health metrics.
Feedback: The web application provides feedback to the user on their predicted diabetes risk level, along with suggestions for improving their health.
We used the following technologies to build the web application:
Flask: Python-based web framework for the backend
HTML: Markup language for creating the structure of the web pages
CSS: Styling language for designing the look and feel of the web pages
JavaScript: Programming language for implementing dynamic behavior and interactivity on the web pages
Scikit-learn: Machine learning library for building the predictive model
To run the application, follow these steps:
Clone the repository to your local machine.
Install the required dependencies by running pip install -r requirements.txt in the terminal.
Set the FLASK_APP environment variable to app.py by running export FLASK_APP=app.py in the terminal.
Start the server by running flask run in the terminal.
Open your web browser and navigate to http://localhost:5000 to access the application.
Enter your health metrics into the form and click the "Predict" button to see your diabetes risk level.
Our diabetes prediction website is a web application that provides users with an easy and convenient way to assess their diabetes risk level based on their health metrics. By using machine learning to make predictions, our web application can help users identify potential health concerns and take action to improve their health. We hope that our project will be useful to anyone looking for a simple and accessible way to monitor their health. when u clone this project and install it pls install all flask packages cause if u don't nothing will work
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