University Health Network

Whole-transcriptome inference from label-free live-cell phase-contrast microscopy, predicting 18,085 genes without staining or lysing the cells.

Micronuclei instance segmentation for fluorescence microscopy, using an anchor-tuned Mask R-CNN to detect micronuclei and link them to parent nuclei.

Image-to-image translation from label-free phase-contrast microscopy to H&E-like images, so pretrained histopathology models run on live cells.

DNA-LLM reasoning model fusing genome foundation model embeddings with an LLM to produce step-by-step pathway and variant effect explanations.

Promptable 3D medical image and video segmentation foundation model fine-tuned from SAM 2.1, cutting lesion annotation time by up to 92%.

Chest X-ray encoder that detects CT-level abnormalities by aligning radiographs with 3D CT volumes and radiology reports in a shared embedding space.

Spatial transcriptomics foundation model continually pretrained on 30 million profiles, with a protocol-aware mixture-of-experts decoder.

Autoregressive genomic foundation models from 20M to 1B parameters that solve ten DNA tasks at once and map sequences to text and images.

Latent diffusion model that paints high-resolution Cell Painting images of cells responding to a chemical compound or an over-expressed gene.

DNA methylation foundation model over 49,156 array CpG sites. Imputes missing values, embeds samples, and predicts epigenetic age and disease risk.

Promptable foundation model for universal medical image segmentation, fine-tuned from SAM on 1.57M image-mask pairs across 10 imaging modalities.