Wellness Predict

ACCESS APPLICATION: https://wellnesspredict.streamlit.app/

Introduction

Welcome to the Wellness Predict project! This project aims to provide a user-friendly application for predicting the likelihood of diabetes, heart disease, or Parkinson's disease based on input data. Additionally, it offers healthy lifestyle tips to improve overall well-being.

Features

• Predict the likelihood of diabetes, heart disease, or Parkinson's disease.
• Input data from reports for accurate predictions.
• Get results instantly after prediction.
• Receive warnings before use, emphasizing consulting doctors for medical advice.
• Suitable for medical professionals or individuals with medical knowledge.

Technologies Used

• Python: Programming language used for backend development.
• Streamlit: Open-source app framework used for building interactive web applications.
• Pandas: Library used for data manipulation and analysis.
• Scikit-learn: Library used for machine learning tasks.
• NumPy: Library used for numerical computations.
• HTML: Markup language used for structuring web pages.
• Tailwind CSS: Utility-first CSS framework used for styling web applications.
• Additional libraries and tools used for specific functionalities.

Getting Started

To get started with the Multiple Disease Prediction application, follow these steps:

1. Clone the Repository: Clone this repository to your local machine.

   git clone https://github.com/MahekRohitGor/Wellness_predict.git

2. Install Dependencies: Make sure you have Python installed on your machine. Install the required Python packages using pip.

   pip install -r requirements.txt

3. Run the Application: Run the main.py script to start the application.

   streamlit run "main.py"

4. Usage: Follow the on-screen instructions to input data from reports, predict disease likelihood, and view results.
5. Consultation: Remember to consult medical professionals before taking any medications or treatments based on the predictions.

Files Description

diabetes_model.sav: Saved model for diabetes prediction.
heart_model.sav: Saved model for heart disease prediction.
parkinson_model.sav: Saved model for Parkinson's disease prediction.
index.html: HTML file for the application's homepage.
life.html: HTML file for displaying healthy lifestyle tips.
main.py: Python script for running the application.

Stay healthy, stay informed, and empower yourself with the knowledge to lead a happier, healthier life.
Created with ❤️