This systematic review aimed to assess the methods used to classify mammographic breast
parenchymal features in relation to the prediction of future breast cancer. The databases …

Mammographic textures show promise as breast cancer risk predictors, distinct from
mammographic density. Yet, there is a lack of comprehensive evidence to determine the …

The analysis of mammograms using artificial intelligence (AI) has shown great potential for
assisting breast cancer screening. We use saliency maps to study the role of breast lesions …

This commentary is about predicting a woman's breast cancer risk from her mammogram,
building on the work of Wolfe, Boyd and Yaffe on mammographic density. We summarise …

Background The extent to which known and unknown factors explain how much people of
the same age differ in disease risk is fundamental to epidemiology. Risk factors can be …

Background Parenchymal analysis has shown promising performance for the assessment of
breast cancer risk through the characterization of the texture features of mammography …

Introduction Breast cancer (BC), the most frequently diagnosed malignancy among women
worldwide, presents a public health challenge and affects mortality rates. Breast‐conserving …

Purpose This research on breast cancer risk assessment aims to develop models that
predict the likelihood of breast cancer. In recent years, the computerized analysis of visual …

Variance of age-specific log incidence decomposition (VALID): a unifying model of
measured and unmeasured genetic and non-geneti Page 1 Methods Variance of age-specific …

Recent non-linear ultrasound imaging methods estimate acoustic tissue properties, such as
speed-of-sound (SOS), density, and compressibility, among others. These methods can be …