https://github.com/vipinchaudhary31122002/cardiopredict
CardioPredict is a smart, ML-powered application that helps analyze your risk of heart disease using interactive forms, clinical features, and trained classification models.
https://github.com/vipinchaudhary31122002/cardiopredict
machine-learning matplotlib numpy pandas python3 random-forest seaborn streamlit
Last synced: over 1 year ago
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CardioPredict is a smart, ML-powered application that helps analyze your risk of heart disease using interactive forms, clinical features, and trained classification models.
- Host: GitHub
- URL: https://github.com/vipinchaudhary31122002/cardiopredict
- Owner: Vipinchaudhary31122002
- Created: 2025-03-13T10:03:06.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2025-04-07T22:23:14.000Z (over 1 year ago)
- Last Synced: 2025-04-12T15:18:42.617Z (over 1 year ago)
- Topics: machine-learning, matplotlib, numpy, pandas, python3, random-forest, seaborn, streamlit
- Language: Jupyter Notebook
- Homepage: https://cardiopredict-esanunwppxn4ey85naeoj5.streamlit.app/
- Size: 4.46 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# 🫀 CardioPredict - Heart Disease Risk Analyzer
**CardioPredict** is a smart, ML-powered application that helps analyze your risk of heart disease using interactive forms, clinical features, and trained classification models. It's designed with doctors, patients, and health enthusiasts in mind — making heart health prediction more accessible than ever!
---
## 🚀 Features
✅ **Smart Risk Prediction**: Instantly predicts whether a patient is at risk of cardiovascular disease.
✅ **Interactive Health Form**: User-friendly dropdowns for 18+ symptoms and risk factors.
✅ **Boolean Mapping**: Uses intuitive True/False and Male/Female inputs.
✅ **ML Integration**: Seamlessly connects to a trained machine learning model.
✅ **Dynamic Input Fields**: Reads from a JSON config so you can easily adjust fields.
✅ **Clean UI/UX**: Sidebar description, emoji-enhanced labels, and structured layout.
✅ **Safe and Local**: All processing happens on your machine. No data leaves your device.
---
## 🛠️ Installation Guide
### 1️⃣ Clone the Repository
```bash
git clone https://github.com/yourusername/CardioPredict
cd CardioPredict
```
### 2️⃣ (Optional) Create a Virtual Environment
```bash
python -m venv env
source env/bin/activate # On Windows: env\Scripts\activate
```
### 3️⃣ Install Dependencies
```bash
pip install -r requirements.txt
```
---
## 🎯 Usage Guide
### 🏁 Start the Application
```bash
streamlit run app.py
```
### 📝 Fill Patient Data
- Use dropdowns to provide information like:
- **Chest Pain**, **Fatigue**, **Shortness of Breath**
- **High BP**, **Diabetes**, **Cholesterol**, etc.
- **Age** and **Gender**
### 💡 Get Risk Prediction
- Submit the form to instantly get:
- ✅ **Low Risk**
- ⚠️ **High Risk**
## 👨💻 Contributing
Contributions are welcome! 🎉
Want to add enhancements or fix bugs?
1. Fork the repo 🍴
2. Create a new branch (`feature-name`) 🌱
3. Make your changes 🛠️
4. Commit & push (`git commit -m 'Add feature'`) 📌
5. Open a pull request ✅
---
## 💡 Future Enhancements
🔹 Add visual analytics (feature importances, SHAP values)
🔹 Export prediction results as PDF report
🔹 Deploy to Streamlit Cloud or Hugging Face Spaces
🔹 Add multilingual support for international use
---
## 📌 Disclaimer
This app is intended **for educational and demonstrative purposes only**. It is **not a substitute for professional medical diagnosis**. Always consult with certified healthcare providers for medical concerns.
---