MODULE 2: DIAGNOSTIC & THERAPY SELECTION
Early detection and personalized therapeutic strategy using multi-omics integration, imaging analysis, and AI-powered treatment response forecasting.
Michael Reed
Microbiome & Metabolomics Researcher
Precision diagnosis meets personalized treatment
Module 2 acts as an intelligent super-agent that integrates mammography, MRI, ultrasound, histology, and genetics (BRCA, PIK3CA, HER2) to deliver early detection and personalized therapeutic recommendations.
By combining multiple diagnostic modalities with synthetic data generation and spatiotemporal prediction models, we create comprehensive treatment strategies tailored to individual patient profiles.
What makes it work
Our diagnostic super-agent uses advanced AI to synthesize information from multiple sources and predict optimal treatment pathways.
Integration of imaging: mammography, MRI, ultrasound, histology
Genetic analysis: BRCA1/2, PIK3CA, HER2 mutations
Synthetic data generation using GANs, VAEs, and diffusion models
Treatment response forecasting with XAI visualization
Technologies and Approaches
Module 2 employs GNNs and Transformers for spatiotemporal predictions, analyzing how cancer develops over time and predicting treatment efficacy before implementation. The system generates synthetic training data to improve model accuracy while maintaining patient privacy.
Integration with PACS/LIS/LIMS workflows ensures seamless adoption in clinical environments. The super-agent provides explainable recommendations that support physician decision-making rather than replacing clinical judgment.
