🏥 Heart Disease Prediction – RAMP Challenge

📌 Introduction

Cardiovascular diseases are among the leading causes of mortality worldwide. Accurate and early diagnosis of heart disease is crucial for effective treatment and prevention. The goal of this challenge is to build predictive models that classify whether a patient has heart disease based on clinical and diagnostic features.

The target variable y is binary:

• y = 1: The patient has heart disease.
• y = 0: The patient does not have heart disease.

Automating this classification process could significantly aid healthcare professionals in making quick and reliable diagnoses.

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🎯 Challenge Objective

Participants will build machine learning models to classify patients as having heart disease or not, based on structured clinical data. The goal is to maximize classification performance while ensuring interpretability and clinical relevance.

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📊 Evaluation Metrics

Models will be evaluated using:

• Accuracy
• Precision, Recall, and F1-score
• ROC-AUC Score

The final ranking will be based on a weighted combination of these metrics.

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📂 Repository Structure

📁 heart-disease-prediction/
│── 📄 heart_disease_starting_kit.ipynb  # Starter Notebook with data exploration and model training
│── 📁 data/                             # Dataset files (if applicable)
│── 📁 models/                           # Trained models and experiment logs
│── 📁 src/                              # Python scripts for preprocessing & modeling
│── 📄 README.md                         # Project documentation (this file)

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🔧 Setup Instructions

1️⃣ Clone the Repository

git clone https://github.com/YourUsername/heart-disease-prediction.git
cd heart-disease-prediction

2️⃣ Install Dependencies

pip install -r requirements.txt

3️⃣ Run the Jupyter Notebook

Launch Jupyter Notebook and open heart_disease_starting_kit.ipynb:

jupyter notebook

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📌 Dataset

The dataset contains various clinical and diagnostic features such as:

• Age
• Blood Pressure
• Cholesterol Levels
• Electrocardiogram Results
• Maximum Heart Rate Achieved
• Chest Pain Type
• And more...

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🚀 How to Contribute

If you’d like to improve the project:

1. Fork the repository.
2. Create a new branch (feature-branch).
3. Make your changes and commit (git commit -m "Add new feature").
4. Push to your branch and create a Pull Request.

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📜 License

This project is licensed under the MIT License. Feel free to use and contribute!