Cancer prevention research (Philadelphia, Pa.)
Jan 6, 2025
Mammographic density is a strong risk factor for breast cancer and is reported clinically as part of Breast Imaging Reporting and Data System (BI-RADS) results issued by radiologists. Automated assessment of density is needed that can be used for bot...
BACKGROUND: Cancer patients have up to a 3-fold higher risk for cardiovascular disease (CVD) than the general population. Traditional CVD risk scores may be less accurate for them. We aimed to develop cancer-specific CVD risk scores and compare them ...
Studies show that breast screening participants are open to artificial intelligence (AI) in breast screening, but hold concerns about AI performance, governance, equitable access, and dependence on technology. Little is known of consumers' views on h...
BACKGROUND: Breast cancer is a heterogeneous malignancy with complex molecular characteristics, making accurate prognostication and treatment stratification particularly challenging. Emerging evidence suggests that lactylation, a novel post-translati...
This study presents a convolutional neural network (CNN)-based method for the classification and recognition of breast cancer pathology images. It aims to solve the problems existing in traditional pathological tissue analysis methods, such as time-c...
BACKGROUND: Checkpoint kinase 1 (CHEK1) is often overexpressed in solid tumors. Nonetheless, the prognostic significance of CHEK1 in breast cancer (BrC) remains unclear. This study used pathomics leverages machine learning to predict BrC prognosis ba...
PURPOSE: This study evaluates the impact of artificial intelligence (AI) assistance on the diagnostic performance of radiologists with varying levels of experience in interpreting mammograms in a Malaysian tertiary referral center, particularly in wo...
OBJECTIVE: The aim of this study was to compare image quality features and lesion characteristics between a faster deep learning (DL) reconstructed T2-weighted (T2-w) fast spin-echo (FSE) Dixon sequence with super-resolution (T2) and a conventional T...
Journal of cellular and molecular medicine
Jan 1, 2025
Breast cancer (BRCA) is one of the most common malignancies and a leading cause of cancer-related mortality among women globally. Despite advances in diagnosis and treatment, the heterogeneity of BRCA presents significant challenges for effective man...
A deep learning model, trained using transcriptomic data, inexpensively quantifies and fine-maps ITH due to subtype admixture in routine images of LumA breast cancer, the most favorable subtype. This new approach could facilitate exploration of the m...
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