AI-Powered Computational Vision
Advancing AI-driven computational models for pathology—analyzing cellular, tissue, and molecular patterns to enable next-generation diagnostics, predictive insights, and precision therapies.
AI-Powered Precision Medicine
Building advanced AI-driven models to analyze medical and pathology data—integrating cellular, spatial, and molecular information to deliver predictive insights for next-generation diagnostics and therapies.
AI-Driven Tissue Analysis
Developing scalable computer vision models that decode tissue architecture, detect abnormal cellular patterns, and generate actionable insights for disease diagnosis, treatment planning, and research.
Next-Gen Computational Vision
Leveraging AI-powered computer vision and advanced computational models to decode complex tissue structures, analyze cellular and spatial patterns, and generate predictive insights for next-generation medicine and precision therapies.
Helios: AI-Powered Computational Pathology
Predictive Genetic Mapping Predictive Genetic Mapping
Using advanced AI, the system aims to infer genetic and molecular features from tissue morphology, supporting prediction of mutations, molecular subtypes, and biomarkers directly from images.
Cellular Neighborhood Analysis Cellular Neighborhood Analysis
Spatial modeling of cellular interactions identifies functional microenvironments and cellular niches, offering insights into tissue organization and potential pathological mechanisms
Therapeutic Target Intelligence Therapeutic Target Intelligence
By combining spatial patterns and predicted molecular features, the approach highlights potential vulnerabilities and guides hypothesis generation for therapeutic strategies.
Hypergraph-Driven Patient Insights Hypergraph-Driven Patient Insights
Integrating spatial and molecular tissue features with multi-patient data enables the identification of relationships between tissue architecture and outcomes, supporting population-level analysis.