Diabetes Web App using Streamlit

This repository contains a web application for diabetes prediction using Streamlit, a popular Python library for creating web apps with minimal effort. The app leverages a dataset with various features related to diabetes to provide predictions and insights.

Dataset Features

The dataset used in this web app contains the following features:

1. Age
2. Gender
3. Body Mass Index (BMI)
4. Blood Pressure
5. Insulin Level
6. Skin Thickness
7. Glucose Level
8. Diabetes Pedigree Function
9. Number of Pregnancies

These features play a crucial role in predicting the likelihood of an individual having diabetes, and the web app utilizes them to provide accurate predictions.The dataset is publicly available on kaggle https://www.kaggle.com/datasets/mrsimple07/diabetes-prediction Here's the link to the web app https://diabetes-web-app-007.streamlit.app/

Usage

To run the web app locally, follow these steps:

1. Clone the repository to your local machine.
2. Install the required dependencies listed in the requirements.txt file.
3. Run the Streamlit app using the command streamlit run app.py.
4. Access the web app through the provided local URL.

Contributions

Contributions to this project are welcome! If you have any ideas for improvements or new features, feel free to open an issue or submit a pull request.

Thank you for your interest in our diabetes prediction web app! We hope it provides valuable insights and assistance in the field of healthcare.