Clinical utility of receptor status prediction in breast cancer and misdiagnosis identification using deep learning on hematoxylin and eosin-stained slides

Clinical utility of receptor status prediction in breast cancer and misdiagnosis identification using deep learning on hematoxylin and eosin-stained slides

Abstract Background Molecular profiling of estrogen receptor (ER), progesterone receptor (PR), and ERBB2 (also known as Her2) is essential for breast cancer diagnosis and treatment planning. Nevertheless, current methods rely on the qualitative interpretation of immunohistochemistry and fluorescence...

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Main Authors: Gil Shamai, Ran Schley, Alexandra Cretu, Tal Neoran, Edmond Sabo, Yoav Binenbaum, Shachar Cohen, Tal Goldman, António Polónia, Keren Drumea, Karin Stoliar, Ron Kimmel
Format: Article
Language:English
Published: Nature Portfolio 2024-12-01
Series:Communications Medicine
Online Access:https://doi.org/10.1038/s43856-024-00695-5
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