Brigham and Women's Hospital

A transformer foundation model trained on a biomedical knowledge graph for zero-shot drug-discovery inference across indications, targets, ADRs, contraindications, and off-label uses.

A self-supervised vision foundation model for structural brain MRI that produces general-purpose features adaptable to diverse downstream clinical and neuroscience tasks.

A weakly supervised pathology foundation model pretrained on 60,530 whole-slide images across 19 anatomical sites for cancer detection, prognosis, and molecular prediction.

A multimodal vision-language copilot for human pathology that analyzes histology images and answers diverse pathology queries in natural language.

Vision-language foundation model for computational pathology, pretrained on 1.17M histopathology image-caption pairs with contrastive and captioning objectives.

A self-supervised 3D CT foundation model that extracts general-purpose tumor representations for cancer imaging biomarker discovery across diverse downstream tasks.