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Spatial proteomics foundation model for multiplex immunofluorescence, with a 268-marker vocabulary and marker-conditioned 768-dimensional embeddings.
Panoptic segmentation for H&E histopathology, labeling tissue regions and cell nuclei in one pass so tissue context constrains each nuclear call.
Self-supervised colorectal histopathology model turning H&E tiles into interpretable phenotype clusters and a disease-free survival risk score.
Distilled whole-slide pathology foundation model pairing a 22M-parameter ViT-S tile encoder with a LongNet slide encoder for cohort-scale analysis.
Spatial proteomics prediction from routine H&E slides, generating 21-channel virtual multiplex immunofluorescence maps of the tumor microenvironment.
Vision-language model for neuroblastoma pathology that reads H&E slides with their reports to grade tumors, infer biomarkers and stratify risk.
Spatial transcriptomics prediction from histology using conditional neural fields to reconstruct continuous gene expression fields.
Histopathology-to-molecular alignment model that queries H&E slides with gene-set signatures to predict pathway activity without sequencing.
Vision-guided model that builds virtual 3D organoid surrogates from brightfield microscopy to predict chemical perturbation responses without omics.
Histopathology model reconstructing tissue-wide single-cell gene expression from H&E slides, using sparse TMA measurements as molecular anchors.
Histopathology model predicting 102 methylation-defined CNS tumor subtypes from H&E whole-slide images, with calibrated per-case confidence scores.
Pathology vision foundation model adapting DINOv3 self-supervised learning to whole-slide histopathology across many magnifications and scales.
Multimodal foundation model pretrained on 1.76B histology and spatial transcriptomics spots, inferring molecular state from whole-slide images.
Tri-modal foundation model unifying histology images, spatial transcriptomics, and language for zero-shot pathology and spatial biology reasoning.
Diffusion transformer for virtual tissue synthesis, generating H&E histopathology patches conditioned on spatial gene expression and morphology.
Genetically aligned foundation model for blood smear cytology that links single-cell morphology to the chromosomal aberrations behind AML and APL.
Lung pathology foundation model adapted from Virchow2 on whole-slide images, validated across 32 tasks spanning the lung diagnostic workflow.
Multiphoton pathology vision-language system turning one label-free breast section into virtual H&E, a margin heatmap, and a written report.
Multi-organ foundation model aligning histology images with spatial-transcriptomics profiles for zero-shot expression and survival prediction.
Pathology report generation from whole-slide images, refreshing slide context and curated diagnostic concepts at every layer of the encoder.
Virtual spatial transcriptomics foundation model predicting pan-cancer, spatially-resolved single-cell gene expression from H&E histology slides.
Pathology foundation model that infers spatial transcriptomics and proteomics directly from routine H&E whole-slide images, with no spatial assay.