histocartography
importedsoftware/histocartography
A standardized Python API with necessary preprocessing, machine learning and explainability tools to facilitate graph-analytics in computational pathology.
Machine-generated from the listed sources and not yet reviewed by a human.
- Category
- Software & Systems
- Subcategory
- unknown
- License
- AGPL-3.0(osi)
- Status
- dormant
- Maturity
- deployed
- Organization
- BiomedSciAI
- Country
- unknown
- Homepage
- unknown
- Repository
- github.com/BiomedSciAI/histocartography
- Documentation
- unknown
- Tags
- deep-learning · graph-neural-networks · healthcare · machine-learning · pathology · pytorch
- Regulatory
- unknown
Top contributors by commit count, from the project’s public repository. Avatars are served by their origin, not stored here. To be removed from this list, open an issue.
Computed from shared tags, weighted so a rare tag counts for more than a common one. These are suggestions, not curated relationships.
- torchvahadanepathology · pytorch
Gpu accelerated vahadane stain normalization for Digital Pathology workflows.
- medical-imaginghealthcare · pathology
Accelerate ingestion/transformation of pathology images into DICOMWeb
- GNN_for_EHRgraph-neural-networks · pytorch
Code for "Graph Neural Network on Electronic Health Records for Predicting Alzheimer’s Disease"
- pocket-cfdmgraph-neural-networks · pytorch
Augmenting a training dataset of the generative diffusion model for molecular docking with artificial binding pockets
- ShapePharm3Dgraph-neural-networks · pytorch
3D pharmacophore-conditioned molecular diffusion with an E(3)-equivariant EGNN backbone. Generates shape-complementary, drug-like molecules conditioned on pharmacophore point clouds and PMI/SSD…
- torchdruggraph-neural-networks · pytorch
A powerful and flexible machine learning platform for drug discovery
- api.github.com/repos/BiomedSciAI/histocartographyretrieved 2026-08-05 · via github-api
Machine-imported from GitHub search. Last push 2023-12-23, 273 stars, license reported as AGPL-3.0. Category and schematic were assigned by keyword heuristics and are unreviewed.
Not yet verified by a human. Correct this record →
/v1/entries/30.json→ .entries["histocartography"]
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