https://github.com/jkanishkha0305/fetal-health-prediction-from-ctg-data-using-ensemble-learning

Prediction of Women health and Fetal Health from CTG Data using Ensemble learning Techniques
https://github.com/jkanishkha0305/fetal-health-prediction-from-ctg-data-using-ensemble-learning

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Prediction of Women health and Fetal Health from CTG Data using Ensemble learning Techniques

• Host: GitHub
• URL: https://github.com/jkanishkha0305/fetal-health-prediction-from-ctg-data-using-ensemble-learning
• Owner: Jkanishkha0305
• License: mit
• Created: 2022-10-24T16:23:07.000Z (about 2 years ago)
• Default Branch: main
• Last Pushed: 2023-10-13T20:49:51.000Z (about 1 year ago)
• Last Synced: 2023-10-15T12:03:12.041Z (about 1 year ago)
• Language: Jupyter Notebook
• Homepage:
• Size: 11.6 MB
• Stars: 1
• Watchers: 3
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# Fetal Health Prediction from CTG Data using Ensemble Learning

🌟 Welcome to the world of advanced healthcare and cutting-edge data science! In this project, we delve into the vital realm of maternal and fetal health, harnessing the power of Ensemble Learning.

## Table of Contents

- [Introduction](#introduction)

- [Key Features](#key-features)

- [Tech Stack](#tech-stack)

- [Contributing](#contributing)

- [License](#license)

## Introduction

Healthcare is evolving rapidly, and the well-being of expectant mothers and their unborn children is a top priority. Our project focuses on predicting fetal health using advanced Machine Learning and Deep Learning techniques. By analyzing Cardiotocography (CTG) data, we aim to provide valuable insights into the health of both women and their fetuses, aiding healthcare professionals in making informed decisions.

## Key Features

- 📊 Ensemble Learning: Utilizing the power of Ensemble Learning to improve predictive accuracy.

- 🤰 Women's Health Prediction: Assessing the health of expectant mothers alongside fetal health.

- 📈 Data Analysis: In-depth analysis of CTG data for comprehensive health assessment.

- 🧠 Machine Learning and Deep Learning: Implementing state-of-the-art ML and DL algorithms.

- 🚀 Predictive Insights: Empowering healthcare professionals with actionable insights.

- 🏥 Future of Healthcare: Shaping the future of maternal and fetal care through data science.

## Tech Stack

Our project leverages a range of powerful libraries and tools for predictive analysis, including:

- TensorFlow

- PyTorch

- Scikit-learn

- Pandas

- NumPy

- Matplotlib

- Jupyter Notebook

## Contributing

We welcome contributions from data scientists, healthcare experts, and enthusiasts. Follow our [Contributing Guide](/CONTRIBUTING.md) to learn how to get involved.

## License

This project is licensed under the MIT License. For details, refer to the [LICENSE](/LICENSE) file.

🌟🤰 Embrace the future of healthcare with Fetal Health Prediction! 🚀🏥