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MOOZY

imported

software/moozy

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

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

MOOZY project image
GitHub preview card for AtlasAnalyticsLab/MOOZY. Served by its origin, not stored here, and not covered by this registry’s licence.
record
Category
Software & Systems
Subcategory
unknown
License
CC-BY-NC-SA-4.0(cc)
Status
active
Maturity
deployed
Organization
AtlasAnalyticsLab
Country
unknown
Homepage
atlasanalyticslab.github.io/MOOZY/
Repository
github.com/AtlasAnalyticsLab/MOOZY
Documentation
unknown
Tags
computational-pathology · digital-pathology · foundation-model · histopathology · medical-imaging · moozy · multiple-instance-learning · pathology-foundation-model · patient-encoder · patient-representation · self-supervised-learning · slide-encoder · slide-representation-learning · survival-prediction · whole-slide-image · wsi-foundation-model
Regulatory
unknown
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.

  • GatedSRPcomputational-pathology · digital-pathology · histopathology · medical-imaging · multiple-instance-learning · slide-representation-learning · survival-prediction · whole-slide-image

    [BMVC 2026 Oral] Gated Spatial Redundancy Projection for Pathology Transformer Attentions

  • SurvivMIL_COMPAYLdigital-pathology · histopathology · multiple-instance-learning · survival-prediction · whole-slide-image

    SurvivMIL: A multimodal, Multiple Instance Learning pipeline for survival outcome of Neuroblastoma Patients

  • ACMILcomputational-pathology · digital-pathology · histopathology · multiple-instance-learning

    Attention-Challenging Multiple Instance Learning for Whole Slide Image Classification (ECCV2024)

  • tcga_segmentationcomputational-pathology · histopathology · medical-imaging · multiple-instance-learning

    Whole Slide Image segmentation with weakly supervised multiple instance learning on TCGA | MICCAI2020 https://arxiv.org/abs/2004.05024

  • HiPScomputational-pathology · digital-pathology · survival-prediction

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

  • torchmilmedical-imaging · multiple-instance-learning · whole-slide-image

    Deep Multiple Instance Learning library for Pytorch

sources
  1. api.github.com/repos/AtlasAnalyticsLab/MOOZY
    retrieved 2026-08-25 · via github-api

    Machine-imported from GitHub search. Last push 2026-07-22, 27 stars, license reported as NOASSERTION. Category and schematic were assigned by keyword heuristics and are unreviewed. GitHub reported NOASSERTION; the licence was read from the LICENSE file as CC-BY-NC-SA-4.0, because GitHub's detector does not recognise open hardware licences.

Not yet verified by a human. Correct this record →

machine-readable

/v1/entries/31.json→ .entries["moozy"]

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