Abstract
AbstractDigital 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.
Funder
U.S. Department of Health & Human Services | NIH | National Institute of General Medical Sciences
Stony Brook Provost ProFund 2022 award; the generosity of Bob Beals and Betsy Barton
Wellcome Trust
Stony Brook Provost ProFund 2022 award; the generosity of Bob Beals and Betsy Barton.
Publisher
Springer Science and Business Media LLC
Cited by
5 articles.
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