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Fertility Diagnoser

Fertility Diagnoser is a web application designed to predict fertility levels using machine learning. This project combines the power of React for the frontend and Python for the backend and machine learning components. By inputting specific data such as age and hormone levels, users can obtain personalized predictions about their fertility.

Table of Contents

Introduction

The Fertility Diagnoser web application is a powerful tool that leverages machine learning algorithms to provide fertility predictions. By analyzing user-inputted data, the application generates personalized insights into fertility levels, helping individuals make informed decisions about their reproductive health.

Features

  • User-friendly interface for inputting age, hormone levels, and other relevant data
  • Machine learning model trained to predict fertility levels accurately
  • Personalized fertility predictions tailored to individual user profiles

Technologies Used

  • React: A popular JavaScript library for building user interfaces
  • Python: A versatile programming language used for backend development and machine learning
  • sklearn: A machine learning library in Python used for training and testing the fertility prediction model

Installation

  1. Clone the repository: git clone https://github.com/Qamar2315/fertility_diagnoser
  2. Navigate to the project directory: cd fertility-diagnoser
  3. Install the required dependencies:
    • For the frontend: npm install
    • For the backend: pip install -r requirements.txt

Usage

  1. Start the frontend development server: npm start
  2. Launch the backend server: python app.py
  3. Access the web application in your browser at http://localhost:3000

Contributing

Contributions are welcome! If you would like to contribute to the Fertility Diagnoser project, please follow these steps:

  1. Fork the repository
  2. Create a new branch
  3. Make your changes
  4. Submit a pull request

Please note that Fertility Diagnoser is not a substitute for professional medical advice. It is recommended to consult with a healthcare professional for accurate diagnosis and guidance regarding fertility-related concerns.