1. Ultrasound-based radiomics nomogram for predicting HER2- low expression breast cancer.
- Author
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Xueling Zhang, Shaoyou Wu, Xiao Zu, Xiaojing Li, Qing Zhang, Yongzhen Ren, Xiaoqin Qian, Shan Tong, and Hongbo Li
- Subjects
MEDICAL sciences ,TRIPLE-negative breast cancer ,EPIDERMAL growth factor receptors ,METASTATIC breast cancer ,HER2 positive breast cancer ,CONTRAST-enhanced magnetic resonance imaging ,MUCINOUS adenocarcinoma - Abstract
This article presents a study on the development and validation of an ultrasound-based radiomics nomogram for predicting HER2-low expression breast cancer. The study included 222 patients with breast cancer, and machine learning methods were used to extract radiomics features from ultrasound images. The features were then used to construct a prediction model, which was validated using a training cohort and a test cohort. The nomogram, incorporating radiomics features and clinical risk factors, showed high prediction value for HER2-low expression breast cancer. This non-invasive approach could be useful for early detection and clinical therapy planning. [Extracted from the article]
- Published
- 2024
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