Production-grade Python package for epidemiological research, clinical decision support, and public health analysis
A comprehensive, validated, and production-ready solution for cardiovascular risk assessment
Comprehensive collection of major CVD risk prediction algorithms
Type-safe, validated, and thoroughly tested (96% coverage)
Validated against published results, suitable for research
Modern Python with full type hints and comprehensive docs
Optimized for processing 1M+ patient records efficiently
Pydantic validation ensures data integrity and type safety
Choose the right model for your population and use case
Year: 2021
Region: Europe
Year: 2013
Region: US
Year: 2017
Region: UK
Year: 1998
Region: US
Year: 2014
Region: Europe
Year: 2019
Region: Global
Year: 2017
Region: Global
Try the risk calculator with sample patient data
Enter patient information and click "Calculate Risk"
# Install
pip install cvd-risk-calculator
# Usage
from cvd_risk_calculator.models import SCORE2
from cvd_risk_calculator.core.validation import PatientData
patient = PatientData(
age=55, sex="male",
systolic_bp=140.0,
total_cholesterol=6.0,
hdl_cholesterol=1.2,
smoking=True,
region="moderate"
)
model = SCORE2()
result = model.calculate(patient)
print(f"Risk: {result.risk_score:.1f}%")