Longitudinal multimodal patient foundation model for oncology, fusing clinical records, DNA, RNA, and H&E pathology into one patient-state embedding.
Multimodal foundation model for precision neurology that reconstructs a patient's molecular brain state from blood to predict disease progression.
BERT-style language model for somatic mutations, pretrained on cancer sequencing from 210,000+ patients for tumor subtyping and therapy response.
Cancer genomics foundation model embedding clinical gene-panel mutations into tumor subtype vectors. Pretrained on 30,328 tumors and 8 networks.
Single-cell transcriptomics model fine-tuned on 1.12M CAR-T profiles to annotate T cell subtypes and predict therapy response and neurotoxicity.