An assessment of breast cancer HER2, ER, and PR expressions based on mammography using deep learning with convolutional neural networks

An assessment of breast cancer HER2, ER, and PR expressions based on mammography using deep learning with convolutional neural networks

Abstract Mammography is the recommended imaging modality for breast cancer screening. Expressions of human epidermal growth factor receptor 2 (HER2), estrogen receptor (ER), and progesterone receptor (PR) are critical to the development of therapeutic strategies for breast cancer. In this study, a d...

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Bibliographic Details
Main Authors: Shun Zeng, Hongyu Chen, Rui Jing, Wenzhuo Yang, Ligong He, Tianle Zou, Peng Liu, Bo Liang, Dan Shi, Wenhao Wu, Qiusheng Lin, Zhenyu Ma, Jinhui Zha, Yonghao Zhong, Xianbin Zhang, Guangrui Shao, Peng Gong
Format: Article
Language:English
Published: Nature Portfolio 2025-02-01
Series:Scientific Reports
Subjects:
Mammography
Deep learning
Breast cancer
Histopathology
Online Access:https://doi.org/10.1038/s41598-024-83597-9
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