🧠 AxionCura – Early Stroke Prediction System

An AI-powered stroke risk prediction system built using Python and Machine Learning. The model analyzes patient health parameters to predict the likelihood of stroke and support early preventive action.

🚀 Features

1. Data Preprocessing – Handles missing values and encodes categorical features.
2. Machine Learning Model – Trained classification model for stroke prediction.
3. Pipeline Integration – End-to-end preprocessing + model bundled using joblib.
4. Model Serialization – Saved trained model for direct inference.
5. Prediction System – Accepts patient input and outputs stroke risk prediction.

📂 Project Structure

AxionCura/
├── app.py
├── main.py
├── stroke_pipeline.joblib
├── stroke.csv
├── requirements.txt

💡 Technologies Used

• Python
• Pandas
• NumPy
• Scikit-learn
• Joblib

🛠️ How to Run

1. Clone the repository:

git clone https://github.com/Agent-A345/AxionCura.git

2. Install the dependencies:

pip install -r requirements.txt

3. Run the application

python app.py

📊 Model Objective

Predict whether a patient is at risk of stroke based on health and lifestyle attributes such as age, glucose level, BMI, hypertension, heart disease, and smoking status.

🔄 Future Enhancements

• Web-based deployment
• Model performance optimization
• Explainable AI integration
• Real-time risk scoring

📝 License

This project is licensed under the MIT License.