Publications by authors named "Baiyang Fu"

Breast cancer is the leading cause of death and morbidity among women. A major challenge for clinical management of breast cancer is the dissemination of breast cancer cells from the primary tumor site via lymphatic drainage, resulting in metastatic tumor spread. Recent studies have found that high expression of the microRNA miR-146a-5p is associated with better survival outcomes for breast cancer patients.

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Article Synopsis
  • - The study focuses on developing a deep learning (DL) model to help differentiate mucinous breast carcinoma (MBC) from fibroadenomas (FA) using ultrasound (US) images, aiming to improve diagnostic accuracy for radiologists.
  • - 884 patients were analyzed, with their US images split into training and test sets to create and compare three DL models, identifying the one with the best performance for MBC diagnosis.
  • - The DL+ age-tree model outperformed other models and significantly improved the diagnostic accuracy of both junior and senior radiologists, showing promise in reducing MBC misdiagnosis.
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Background: At present, there is no research on which surgical method can lead to a better prognosis in elderly patients with early breast cancer. The purpose of this study was to establish a nomogram to predict the survival outcome of elderly patients with early breast cancer and to compare the prognosis of the breast-conserving surgery (BCS) group who did not receive postoperative radiotherapy and the mastectomy group through risk stratification.

Methods: This study included patients with early breast cancer aged ≥70 years from the Surveillance, Epidemiology, and End Results database (n = 20,520).

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Background: Human epidermal growth factor receptor 2 (HER2) overexpressed associated with poor prognosis in breast cancer and HER2 has been defined as a therapeutic target for breast cancer treatment. We aimed to explore the molecular biological information in ultrasound radiomic features (URFs) of HER2-positive breast cancer using radiogenomic analysis. Moreover, a radiomics model was developed to predict the status of HER2 in breast cancer.

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