health_score

❤️ Cardiovascular Health Risk Predictor

This model predicts the risk of cardiovascular issues based on personal and clinical bio-metrics. It was trained on the Cardiovascular Disease dataset and is intended for informational and research purposes.

🚀 Model Details

• Task: Binary Classification (Risk / No Risk)
• Framework: Scikit-Learn / Joblib
• Features:
  • age: Age in years
  • gender: Gender (mapped)
  • height: Height in cm
  • weight: Weight in kg
  • systolic_bp: Systolic Blood Pressure
  • diastolic_bp: Diastolic Blood Pressure
  • cholesterol: Cholesterol Level (mapped)
  • gluc: Glucose Level (mapped)
  • smoke: Smoker status
  • alco: Alcohol consumption
  • active: Physical activity
  • bmi: Body Mass Index (calculated)
  • pulse_pressure: Difference between Systolic and Diastolic BP

📊 Performance

The model has been optimized for high recall and ROC-AUC to ensure potential risks are not missed. (Detailed metrics available in training logs).

🛠️ Usage

You can load the model and scaler using pickle or joblib:

import pickle
import pandas as pd

# Load resources
with open('model.pkl', 'rb') as f:
    model = pickle.load(f)
with open('scaler.pkl', 'rb') as f:
    scaler = pickle.load(f)

# Sample prediction
data = pd.DataFrame({...}) # Match feature order
data[scaler_cols] = scaler.transform(data[scaler_cols])
prediction = model.predict(data)

⚠️ Disclaimer

This tool uses a machine learning model for informational purposes only. It is NOT a substitute for professional medical advice, diagnosis, or treatment. Always consult with a qualified healthcare provider for any questions regarding a medical condition.