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tags:
- health
- stroke-risk
- machine-learning
- gradio
library_name: gradio
license: mit
widget:
- type: gradio
src: app.py
---
# Stroke Risk Prediction Model π
This model predicts the stroke risk percentage based on user symptoms using a trained linear regression model.
## π Features:
- β
Takes 16 symptoms as input (Checkbox selection)
- β
Returns a stroke risk percentage
- β
Deployed using Gradio on Hugging Face Spaces
## π§ 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.
## π Try it Live:
[](https://huggingface.co/attiquers)
## π Files:
- `app.py`: Gradio interface and model inference.
- `theta_final.npy`: Trained model parameters.
- `requirements.txt`: Dependencies.
## π Installation (Local Testing):
```bash
pip install gradio numpy
python app.py
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