PathForge
github.com/sbrussee/pathforgePathForge is a modular benchmarking framework for multiple instance learning in computational pathology. It supports whole slide image feature extraction, HDF5 artifact generation, tile overviews, benchmarking, pipeline optimization, classification, regression, survival and retrieval tasks, and support for model inference and visualization.
Sourced from
- bio.tools — pathforge
- GitHub — github.com/sbrussee/pathforge
Related resources
PathBench-MIL is a comprehensive, flexible benchmarking/AutoML framework for multiple instance learning in histopathology. PathBench-MIL is expected to be deprecated and replaced by PathForge.
General-purpose pathology foundation model pretrained on 100K+ diagnostic whole-slide images across 20 major tissue types, achieving state-of-the-art transfer learning across 30+ clinical tasks and serving as a universal feature extractor for digital pathology (Mahmood Lab, 722+ stars)
Multimodal whole-slide pathology foundation model jointly pretrained on H&E histology and diagnostic text reports, enabling zero-shot cancer subtyping, biomarker prediction, and multimodal reasoning across diverse cancer types (Mahmood Lab, 341+ stars)