---
tags:
- health
- stroke-risk
- machine-learning
- gradio
library_name: gradio
license: mit
widget:
- type: gradio
  src: app.py
---



# Stroke Risk Prediction Model 🚑

This model predicts the stroke risk percentage based on user symptoms using a trained linear regression model.

## 📌 Features:
- ✅ Takes 16 symptoms as input (Checkbox selection)
- ✅ Returns a stroke risk percentage
- ✅ Deployed using Gradio on Hugging Face Spaces

## 🔧 How It Works:
1. User selects relevant symptoms.
2. The input is normalized based on precomputed dataset statistics.
3. The trained model (`theta_final.npy`) predicts the stroke risk.

## 🚀 Try it Live:
[![Hugging Face Space](https://img.shields.io/badge/HuggingFace-Space-blue)](https://huggingface.co/attiquers)

## 📂 Files:
- `app.py`: Gradio interface and model inference.
- `theta_final.npy`: Trained model parameters.
- `requirements.txt`: Dependencies.

## 🛠 Installation (Local Testing):
```bash
pip install gradio numpy
python app.py