The Multi-Risk Assessment application is an AI-driven health evaluation platform that combines machine learning models with intuitive data visualization to assess risks for five major medical conditions. Developed using Python, this tool enables users to input personal health metrics and receive instant risk assessments for breast cancer, cardiovascular diseases, hepatic disorders, diabetes mellitus, and cerebrovascular incidents.
Breast cancer detection using cellular characteristic analysis
Cardiovascular risk evaluation through vital sign assessment
Hepatic health screening via blood chemistry parameters
Diabetes predisposition analysis based on metabolic indicators
Stroke probability calculation incorporating lifestyle factors
Dynamic comparison charts showing user metrics against population averages
Instant graphical feedback using Matplotlib visualizations
Model transparency displays explaining each assessment's methodology
Frontend: Streamlit-powered responsive interface
Backend: Scikit-learn models with Pandas data processing
Infrastructure: Modular Python architecture enabling easy model updates
The application interface showcases:
Clean input forms with parameter validation
Side-by-side comparisons of user data and reference ranges
Model performance metrics and confidence intervals
Interactive result dashboards with prevention recommendations
This tool aims to bridge healthcare accessibility gaps by providing:
Early risk identification through predictive analytics
Patient education via visual data representation
Continuous model improvement through user feedback integration
Cross-platform compatibility for widespread accessibility
The system emphasizes preventive healthcare strategies while maintaining strict data privacy standards, offering users a confidential self-assessment platform without replacing professional medical consultation.
