AIMC Topic: Breast Neoplasms

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Enhancing lesion detection in automated breast ultrasound using unsupervised multi-view contrastive learning with 3D DETR.

Medical image analysis
The inherent variability of lesions poses challenges in leveraging AI in 3D automated breast ultrasound (ABUS) for lesion detection. Traditional methods based on single scans have fallen short compared to comprehensive evaluations by experienced sono...

The status of serum 25(OH)D levels is related to breast cancer.

Cancer treatment and research communications
AIM: Breast cancer is the second most common cancer among women and the leading cause of cancer-related mortality in this population. Numerous factors have been identified as either risk factors or protective factors for breast cancer. However, the r...

Multi-institutional Knowledge-Based (KB) plan prediction benchmark models for whole breast irradiation.

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)
PURPOSE: To train and validate KB prediction models by merging a large multi-institutional cohort of whole breast irradiation (WBI) plans using tangential fields.

Attention-guided erasing for enhanced transfer learning in breast abnormality classification.

International journal of computer assisted radiology and surgery
PURPOSE: Breast cancer remains one of the most prevalent cancers globally, necessitating effective early screening and diagnosis. This study investigates the effectiveness and generalizability of our recently proposed data augmentation technique, att...

Epigenetic profiling for prognostic stratification and personalized therapy in breast cancer.

Frontiers in immunology
BACKGROUND: The rising incidence of breast cancer and its heterogeneity necessitate precise tools for predicting patient prognosis and tailoring personalized treatments. Epigenetic changes play a critical role in breast cancer progression and therapy...

Personalized treatment strategies for breast adenoid cystic carcinoma: A machine learning approach.

Breast (Edinburgh, Scotland)
BACKGROUND: Breast adenoid cystic carcinoma (BACC) is a rare subtype of breast cancer that accounts for less than 0.1 % of all cases. This study was designed to assess the efficacy of various treatment approaches for BACC and to create the first web-...

Annotation-free deep learning algorithm trained on hematoxylin & eosin images predicts epithelial-to-mesenchymal transition phenotype and endocrine response in estrogen receptor-positive breast cancer.

Breast cancer research : BCR
Recent evidence indicates that endocrine resistance in estrogen receptor-positive (ER+) breast cancer is closely correlated with phenotypic characteristics of epithelial-to-mesenchymal transition (EMT). Nonetheless, identifying tumor tissues with a m...

AI image analysis as the basis for risk-stratified screening.

Japanese journal of radiology
Artificial intelligence (AI) has emerged as a transformative tool in breast cancer screening, with two distinct applications: computer-aided cancer detection (CAD) and risk prediction. While AI CAD systems are slowly finding its way into clinical pra...

A Radiomic-Clinical Model of Contrast-Enhanced Mammography for Breast Cancer Biopsy Outcome Prediction.

Academic radiology
RATIONALE AND OBJECTIVES: In the USA over 1 million breast biopsies are performed annually. Approximately 9.6% diagnostic exams were given Breast Imaging Reporting and Data System (BI-RADS) ≥4A, most of which are 4A/4B. Contrast-enhanced mammography ...