AIMC Topic: Breast Neoplasms

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Optimizing breast lesions diagnosis and decision-making with a deep learning fusion model integrating ultrasound and mammography: a dual-center retrospective study.

Breast cancer research : BCR
BACKGROUND: This study aimed to develop a BI-RADS network (DL-UM) via integrating ultrasound (US) and mammography (MG) images and explore its performance in improving breast lesion diagnosis and management when collaborating with radiologists, partic...

Prognostic value of circadian rhythm-associated genes in breast cancer.

World journal of surgical oncology
OBJECTIVE: Breast cancer (BC) remains the most prevalent malignancy among women. Clinical evidence indicates that genetic variations related to circadian rhythms, as well as the timing of therapeutic interventions, influence the response to radiation...

Identification of HER2-over-expression, HER2-low-expression, and HER2-zero-expression statuses in breast cancer based on F-FDG PET/CT radiomics.

Cancer imaging : the official publication of the International Cancer Imaging Society
PURPOSE: According to the updated classification system, human epidermal growth factor receptor 2 (HER2) expression statuses are divided into the following three groups: HER2-over-expression, HER2-low-expression, and HER2-zero-expression. HER2-negati...

Enhanced Prognostication of Early Breast Cancer Outcomes Using Deep Learning on Merged Multistain and Multicolor-Depth Tumor Histopathology.

Microscopy and microanalysis : the official journal of Microscopy Society of America, Microbeam Analysis Society, Microscopical Society of Canada
Accurate breast cancer prognosis helps clinicians in selecting optimal treatments, potentially improving patient survival. We tested whether combining deep learning with tumor histopathology images could reliably predict cancer spread. Advantages of ...

Advances in research on receptor heterogeneity in breast cancer liver metastasis.

Bioscience trends
Breast cancer liver metastasis (BCLM) presents a critical challenge in breast cancer treatment and has substantial epidemiological and clinical significance. Receptor status is pivotal in managing both primary breast cancer and its liver metastases. ...

Ultrasound-based deep learning radiomics for enhanced axillary lymph node metastasis assessment: a multicenter study.

The oncologist
BACKGROUND: Accurate preoperative assessment of axillary lymph node metastasis (ALNM) in breast cancer is crucial for guiding treatment decisions. This study aimed to develop a deep-learning radiomics model for assessing ALNM and to evaluate its impa...

Hierarchical diagnosis of breast phyllodes tumors enabled by deep learning of ultrasound images: a retrospective multi-center study.

Cancer imaging : the official publication of the International Cancer Imaging Society
OBJECTIVE: Phyllodes tumors (PTs) are rare breast tumors with high recurrence rates, current methods relying on post-resection pathology often delay detection and require further surgery. We propose a deep-learning-based Phyllodes Tumors Hierarchical...