Deep learning identifies morphological features in breast cancer predictive of cancer ERBB2 status and trastuzumab treatment efficacy

Deep learning identifies morphological features in breast cancer predictive of cancer ERBB2 status and trastuzumab treatment efficacy

Abstract The treatment of patients with ERBB2 (HER2)-positive breast cancer with anti-ERBB2 therapy is based on the detection of ERBB2 gene amplification or protein overexpression. Machine learning (ML) algorithms can predict the amplification of ERBB2 based on tumor morphological features, but it i...

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Bibliographic Details
Main Authors: Dmitrii Bychkov, Nina Linder, Aleksei Tiulpin, Hakan Kücükel, Mikael Lundin, Stig Nordling, Harri Sihto, Jorma Isola, Tiina Lehtimäki, Pirkko-Liisa Kellokumpu-Lehtinen, Karl von Smitten, Heikki Joensuu, Johan Lundin
Format: Article
Language:English
Published: Nature Publishing Group 2021-02-01
Series:Scientific Reports
Online Access:https://doi.org/10.1038/s41598-021-83102-6

Internet

https://doi.org/10.1038/s41598-021-83102-6

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