Conformal Prediction for Uncertainty Quantification and Reliable HER2 Status Classification in Breast Cancer IHC Images

Conformal Prediction for Uncertainty Quantification and Reliable HER2 Status Classification in Breast Cancer IHC Images

Accurate assessment of Human Epidermal growth factor receptor 2 (HER2) status in breast cancer is crucial for determining treatment eligibility for targeted therapies. Although machine learning approaches have shown promise in automating HER2 status classification from immunohistochemistry (IHC) ima...

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Bibliographic Details
Main Authors: Surayuth Pintawong, Shanop Shuangshoti, Tikamporn Jitpasutham, Somruethai Shuangshoti, Kulachet Wiwatwarayos, Thananop Kobchaisawat, Thanarat H. Chalidabhongse
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Breast cancer
conformal prediction
digital pathology
handcrafted features
HER2 status
immunohistochemistry
Online Access:https://ieeexplore.ieee.org/document/10933960/
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https://ieeexplore.ieee.org/document/10933960/

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