Enhancing HER2 testing in breast cancer: predicting fluorescence in situ hybridization (FISH) scores from immunohistochemistry images via deep learning

Enhancing HER2 testing in breast cancer: predicting fluorescence in situ hybridization (FISH) scores from immunohistochemistry images via deep learning

Abstract Breast cancer affects millions globally, necessitating precise biomarker testing for effective treatment. HER2 testing is crucial for guiding therapy, particularly with novel antibody‐drug conjugates (ADCs) like trastuzumab deruxtecan, which shows promise for breast cancers with low HER2 ex...

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Bibliographic Details
Main Authors: Daniel O Macaulay, Wenchao Han, Mark D Zarella, Chris A Garcia, Thomas E Tavolara
Format: Article
Language:English
Published: Wiley 2025-03-01
Series:The Journal of Pathology: Clinical Research
Subjects:
HER2
deep learning
breast cancer
immunohistochemistry
biomarkers
in situ hybridization
Online Access:https://doi.org/10.1002/2056-4538.70024
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