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:
- User selects relevant symptoms.
 - The input is normalized based on precomputed dataset statistics.
 - The trained model (
theta_final.npy) predicts the stroke risk. 
π Try it Live:
π Files:
app.py: Gradio interface and model inference.theta_final.npy: Trained model parameters.requirements.txt: Dependencies.
π Installation (Local Testing):
pip install gradio numpy
python app.py
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