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Radiogenomic analysis of prediction HER2 status in breast cancer by linking ultrasound radiomic feature module with biological functions.

Hao CuiYue SunDantong ZhaoXudong ZhangHanqing KongNana HuPanting WangXiaoxuan ZuoWei FanYuan YaoBaiyang FuJiawei TianMeixin WuYue GaoShangwei NingLei Zhang
Published in: Journal of translational medicine (2023)
We searched for the URFs of HER2-positive breast cancer, and explored the underlying genes and biological functions of these URFs. Furthermore, the radiomics model based on the Logistic classifier and URF-module relatively accurately predicted the HER2 status in breast cancer.
Keyphrases
  • positive breast cancer
  • magnetic resonance imaging
  • machine learning
  • genome wide
  • deep learning
  • lymph node metastasis
  • squamous cell carcinoma
  • magnetic resonance
  • gene expression
  • young adults
  • breast cancer risk