AIMC Topic: Breast Neoplasms
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Transforming breast cancer diagnosis and treatment with large language Models: A comprehensive survey.
Methods (San Diego, Calif.)
Apr 6, 2025
Breast cancer (BrCa), being one of the most prevalent forms of cancer in women, poses many challenges in the field of treatment and diagnosis due to its complex biological mechanisms. Early and accurate diagnosis plays a fundamental role in improving...
Using artificial intelligence system for assisting the classification of breast ultrasound glandular tissue components in dense breast tissue.
Scientific reports
Apr 6, 2025
To investigate the potential of employing artificial intelligence (AI) -driven breast ultrasound analysis models for the classification of glandular tissue components (GTC) in dense breast tissue. A total of 1,848 healthy women with mammograms classi...
Deep learning prediction of mammographic breast density using screening data.
Scientific reports
Apr 4, 2025
This study investigated a series of deep learning (DL) models for the objective assessment of four categories of mammographic breast density (e.g., fatty, scattered, heterogeneously dense, and extremely dense). A retrospective analysis was conducted ...
Multi-Scale Dynamic Sparse Token Multi-Instance Learning for Pathology Image Classification.
IEEE journal of biomedical and health informatics
Apr 4, 2025
In many challenging breast cancer pathology images, the proportion of truly informative tumor regions is extremely limited. The disparity between the essential information required for clinical diagnosis (Tumor area less than 10$\%$) and the vast amo...
FET-UNet: Merging CNN and transformer architectures for superior breast ultrasound image segmentation.
Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
Apr 3, 2025
PURPOSE: Breast cancer remains a significant cause of mortality among women globally, highlighting the critical need for accurate diagnosis. Although Convolutional Neural Networks (CNNs) have shown effectiveness in segmenting breast ultrasound images...
Early prediction of neoadjuvant therapy response in breast cancer using MRI-based neural networks: data from the ACRIN 6698 trial and a prospective Chinese cohort.
Breast cancer research : BCR
Apr 3, 2025
BACKGROUND: Early prediction of treatment response to neoadjuvant therapy (NAT) in breast cancer patients can facilitate timely adjustment of treatment regimens. We aimed to develop and validate a MRI-based enhanced self-attention network (MESN) for ...
VBVT-Net: VOI-Based VVBP-Tensor Network for High-Attenuation Artifact Suppression in Digital Breast Tomosynthesis Imaging.
IEEE transactions on medical imaging
Apr 3, 2025
High-attenuation (HA) artifacts may lead to obscured subtle lesions and lesion over-estimation in digital breast tomosynthesis (DBT) imaging. High-attenuation artifact suppression (HAAS) is vital for widespread DBT applications in clinic. The convent...
Multiparametric MRI-based Interpretable Machine Learning Radiomics Model for Distinguishing Between Luminal and Non-luminal Tumors in Breast Cancer: A Multicenter Study.
Academic radiology
Apr 1, 2025
RATIONALE AND OBJECTIVES: To construct and validate an interpretable machine learning (ML) radiomics model derived from multiparametric magnetic resonance imaging (MRI) images to differentiate between luminal and non-luminal breast cancer (BC) subtyp...
Global disparities in artificial intelligence-based mammogram interpretation for breast cancer: A scientometric analysis of representation, trends, and equity.
European journal of cancer (Oxford, England : 1990)
Apr 1, 2025
BACKGROUND: Breast cancer (BC) is the most frequently diagnosed cancer and the leading cause of cancer death among women worldwide. Artificial intelligence (AI) shows promise for improving mammogram interpretation, especially in resource-limited sett...
Multiparametric MRI and transfer learning for predicting positive margins in breast-conserving surgery: a multi-center study.
International journal of surgery (London, England)
Apr 1, 2025
This study aimed to predict positive surgical margins in breast-conserving surgery (BCS) using multiparametric MRI (mpMRI) and radiomics. A retrospective analysis was conducted on data from 444 BCS patients from three Chinese hospitals between 2019 a...
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