Pathology Foundation Model - Nature Medicine

Multimodal Whole Slide Foundation Model for Pathology - Nature Medicine

nnMIL: A generalizable multiple instance learning framework for computational pathology

Spatial Expression-Aligned Learning to improve pathology foundation models

[ECCV 2026] A Patient-First Foundation Model for Computational Pathology

A Molecular-Guided Foundation Model with Adaptive Region Modeling for Whole Slide Image Analysis

[MICCAI2026] Official Repo of "GeneRAG: A Retrieval-Augmented Framework for Spatially Resolved Gene Expression Prediction"

JEPA-Histo: Joint-Embedding Predictive Architecture for Histopathology Representation Learning

A unified benchmarking harness for pathology foundation models. It stitches three upstream benchmark suites (eva by kaiko, HEST, and PLISM) behind a single CLI with a pluggable model registry.

Pathology whole-slide images (WSIs) pretraining

Modular online patch streaming from whole-slide images for training pathology foundation models. No pre-extraction, no disk overhead – patches are sampled, filtered, and augmented on-the-fly.