TumorBERT utilizes a BERT-based architecture to capture mutational patterns within the genomic. By integrating clinical variables, it enables personalized prediction of patient survival risk, achieving an AUROC of 0.72. GeneMed-RAG, built on RAG technology, automatically parses genomic reports and retrieves relevant therapeutic content curated knowledge base of cancer pharmacogenomics. It generates highly accurate, evidence-based medication recommendations with an accuracy of 98.3%.

This technology integrates BERT with RAG to create an oncology digital twin system for precision cancer medicine. TumorBERT uses codon-based encoding with OncoKB and COSMIC databases. It utilizes Gated Cross-Modal Attention for genetic-clinical data fusion, effectively surpassing the limitations of conventional machine learning methods. GeneMed-RAG generates drug recommendations from NCCN guidelines with 98.3% accuracy, surpassing GPT-4o performance.

This AI precision oncology solution uses OncoDT to rapidly analyze genetic reports, creating benefits for all. It enables personalized patient care and treatment. It also benefits hospitals by reducing time, pharmaceutical companies by simulating drug efficacy and screening patients. Interactive AI teaching systems help medical education. The solution targets the global tumor companion diagnostics market with test-agnostic strategies to enable partnerships for global expansion.