Welcome to our Diabetes Prediction Website! Our platform offers a unique opportunity for users to gain insights into their potential risk of developing diabetes by leveraging predictive analytics and visualization techniques.
Website Link :- https://diabetes-prediction-gamma.vercel.app/
Our Diabetes Prediction Website offers a user-friendly platform for individuals to assess their risk of developing diabetes. By inputting demographic and health data, users receive personalized predictions generated through advanced machine learning algorithms. Our visualization tools provide clear insights into the relationships between various risk factors and diabetes development likelihood. Transparency is key, as our about page offers details on our mission, team, and commitment to data security. Our goal is to empower individuals with actionable insights to make informed decisions for better health outcomes.
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๐ Prediction Page: This page lets you type in your personal details and health info. After that, it gives you an idea of how likely you are to get diabetes. It's like having a little crystal ball for your health!
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๐ Visualization Page: Here, you get to see colorful charts and graphs that show how different things, like your weight or blood sugar levels, might affect your chances of getting diabetes. It's like watching a fun picture book about your health!
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โน๏ธ About Page: Our About Page offers a detailed overview of the Diabetes Prediction Website, elucidating its purpose, features, and the dedicated team driving its development. It serves as a hub of information, empowering users with insights into their health risks while highlighting our mission to democratize predictive analytics for proactive wellness.
To set up the project locally, follow these steps:
git clone <repository_url>
cd diabetes-prediction-website
cd client
npm install
cd ../server
pip install -r requirements.txt
cd client
npm run dev
cd ../server
python app.py
Kindly go through CONTRIBUTION.md to understand everything from setup to contributing guidelines.
If you would like to contribute to the project, please follow our contribution guidelines.
Please note that this project is released with a Contributor Code of Conduct. By participating in this project you agree to abide by its terms.
This project is licensed under the MIT License.
We would like to thank the contributors and the community for their support and feedback !!
If you find this project interesting and inspiring, please consider showing your support by starring it on GitHub!