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Open and reusable deep learning for pathology with WSInfer and QuPath

  • Stony Brook University
  • University of Edinburgh

Research output: Contribution to journalArticlepeer-review

19 Scopus citations

Abstract

Digital pathology has seen a proliferation of deep learning models in recent years, but many models are not readily reusable. To address this challenge, we developed WSInfer: an open-source software ecosystem designed to streamline the sharing and reuse of deep learning models for digital pathology. The increased access to trained models can augment research on the diagnostic, prognostic, and predictive capabilities of digital pathology.

Original languageEnglish
Article number9
Journalnpj Precision Oncology
Volume8
Issue number1
DOIs
StatePublished - Dec 2024

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