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title: Stroke Prediction Model
emoji: 🧠
colorFrom: red
colorTo: blue
sdk: docker
app_file: app.py
pinned: false
---
# Stroke Risk Prediction Model
This Hugging Face Space hosts a machine learning model for stroke risk prediction based on various health and demographic factors.
## Model Overview
- **Type**: Random Forest Classifier
- **Target**: Binary classification (stroke risk)
- **Output**: Probability of stroke risk + risk category
- **Features**: Age, gender, hypertension, heart disease, BMI, glucose levels, and more
## API Endpoints
### POST `/api/predict`
Predicts stroke risk based on patient health data.
#### Request Format
```json
{
"gender": "Male",
"age": 67,
"hypertension": 1,
"heart_disease": 0,
"ever_married": "Yes",
"work_type": "Private",
"Residence_type": "Urban",
"avg_glucose_level": 228.69,
"bmi": 36.6,
"smoking_status": "formerly smoked"
}
```
#### Response Format
```json
{
"probability": 0.72,
"prediction": "High Risk",
"stroke_prediction": 1,
"risk_factors": [
"Advanced Age (>65)",
"Very High Blood Glucose (>200)",
"Obesity (BMI > 30)",
"Former Smoker"
],
"important_features": [
{"feature": "avg_glucose_level", "importance": 0.31},
{"feature": "age", "importance": 0.28},
{"feature": "bmi", "importance": 0.15}
],
"execution_time_ms": 50,
"using_model": true,
"model_version": "1.0"
}
```
### GET `/`
Returns information about the model and API usage.
## Parameter Details
| Parameter | Description | Type | Values |
|-----------|-------------|------|--------|
| gender | Gender of the patient | String | "Male", "Female", "Other" |
| age | Age in years | Number | 0-120 |
| hypertension | Whether patient has hypertension | Number | 0 (No), 1 (Yes) |
| heart_disease | Whether patient has heart disease | Number | 0 (No), 1 (Yes) |
| ever_married | Whether patient has ever been married | String | "Yes", "No" |
| work_type | Type of work/employment | String | "Private", "Self-employed", "Govt_job", "children", "Never_worked" |
| Residence_type | Type of residence | String | "Urban", "Rural" |
| avg_glucose_level | Average glucose level in blood (mg/dL) | Number | 50-300+ |
| bmi | Body Mass Index | Number | 10-50+ |
| smoking_status | Smoking status of patient | String | "never smoked", "formerly smoked", "smokes", "Unknown" |
## Risk Categories
- **Very Low Risk**: < 10% probability
- **Low Risk**: 10-20% probability
- **Moderate Risk**: 20-40% probability
- **High Risk**: 40-60% probability
- **Very High Risk**: > 60% probability
## Model Training
This model was trained on a dataset of over 5,000 patients with various health metrics and stroke outcomes. It identifies key risk factors like:
- Age
- High blood pressure
- Heart disease
- Glucose levels
- BMI
- Smoking status
## Integration with BrainWise App
This model serves as the backend for the BrainWise app's stroke risk calculator, providing users with risk assessments based on their health metrics.
## Disclaimer
This model is for informational purposes only and should not replace professional medical advice. Always consult with healthcare providers for medical decisions. |