Deep learning models for histologic grading of breast cancer and association with disease prognosis

Deep learning models for histologic grading of breast cancer and association with disease prognosis

Abstract Histologic grading of breast cancer involves review and scoring of three well-established morphologic features: mitotic count, nuclear pleomorphism, and tubule formation. Taken together, these features form the basis of the Nottingham Grading System which is used to inform breast cancer cha...

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Bibliographic Details
Main Authors: Ronnachai Jaroensri, Ellery Wulczyn, Narayan Hegde, Trissia Brown, Isabelle Flament-Auvigne, Fraser Tan, Yuannan Cai, Kunal Nagpal, Emad A. Rakha, David J. Dabbs, Niels Olson, James H. Wren, Elaine E. Thompson, Erik Seetao, Carrie Robinson, Melissa Miao, Fabien Beckers, Greg S. Corrado, Lily H. Peng, Craig H. Mermel, Yun Liu, David F. Steiner, Po-Hsuan Cameron Chen
Format: Article
Language:English
Published: Nature Portfolio 2022-10-01
Series:npj Breast Cancer
Online Access:https://doi.org/10.1038/s41523-022-00478-y

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https://doi.org/10.1038/s41523-022-00478-y

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