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HiPS

imported

software/hips

Histomic Prognostic Signature (HiPS): A population-level computational histologic signature for invasive breast cancer prognosis

Machine-generated from the listed sources and not yet reviewed by a human.

record
Category
Software & Systems
Subcategory
unknown
License
MIT(osi)
Status
dormant
Maturity
deployed
Organization
PathologyDataScience
Country
unknown
Homepage
unknown
Documentation
unknown
Tags
biomarker-discovery · biomedical-image-processing · breast-cancer · computational-pathology · digital-pathology · explainable-ai · survival-prediction
Regulatory
unknown
built by · 1

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.

similar by tags

Computed from shared tags, weighted so a rare tag counts for more than a common one. These are suggestions, not curated relationships.

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    Amgad M, Salgado R, Cooper LA. A panoptic segmentation approach for tumor-infiltrating lymphocyte assessment: development of the MuTILs model and PanopTILs dataset. medRxiv 2022.01.08.22268814.

  • SurvivMIL_COMPAYLdigital-pathology · survival-prediction

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  • pathmlbiomedical-image-processing · computational-pathology · digital-pathology

    Tools for computational pathology

  • H2G-Netbreast-cancer · computational-pathology · digital-pathology

    🚀 H2G-Net: Segmentation of breast cancer region from whole slide images

  • xMILcomputational-pathology · digital-pathology · explainable-ai

    xMIL: Insightful Explanations for Multiple Instance Learning in Histopathology

  • pbmfbiomarker-discovery

    Predictive Biomarker Modeling Framework (PBMF)

sources
  1. api.github.com/repos/PathologyDataScience/HiPS
    retrieved 2026-08-05 · via github-api

    Machine-imported from GitHub search. Last push 2024-04-09, 33 stars, license reported as MIT. Category and schematic were assigned by keyword heuristics and are unreviewed.

Not yet verified by a human. Correct this record →

machine-readable

/v1/entries/23.json→ .entries["hips"]

Entries are sharded 64 ways by a stable hash of the id, so a consumer can find any record without an index.