Blood-Based Cancer Mathematical Model: Machine Learning Enhanced Framework for Precision Oncology

This repository provides a comprehensive blood-based cancer mathematical model integrating 47 biomarkers with 8 machine learning methods for precision oncology applications. The 15-dimensional dynamical system describes cancer-immune-treatment dynamics with complete stability analysis, mathematical validation, and clinical deployment capabilities. Key features include: (1) Multi-scale modeling of tumor populations, immune response, and treatment effects, (2) Machine learning integration achieving >96% R² for parameter estimation, (3) Comprehensive stability analysis with eigenvalue decomposition, (4) Production-ready clinical prediction system with confidence scoring, and (5) Complete mathematical proofs and validation. The system demonstrates 93% stability rate across biologically realistic parameter ranges and is ready for prospective clinical validation.