Background Improved breast cancer risk assessment models are needed to enable
personalized screening strategies that achieve better harm-to-benefit ratio based on earlier …

As the demand for quality healthcare increases, healthcare systems worldwide are
grappling with time constraints and excessive workloads, which can compromise the quality …

With the help of machine learning, many of the problems that have plagued mammography
in the past have been solved. Effective prediction models need many normal and tumor …

Artificial intelligence (AI) in radiology is a rapidly developing field with several prospective
clinical studies demonstrating its benefits in clinical practice. In 2022, the Korean Society of …

Breast cancer is a significant health concern for women, emphasizing the need for early
detection. This research focuses on developing a computer system for asymmetry detection …

Objective To evaluate whether artificial intelligence (AI) for detecting breast cancer on
mammography can improve the performance and time efficiency of radiologists reading …

Purpose To evaluate the stand-alone diagnostic performances of AI-CAD and outcomes of
AI-CAD detected abnormalities when applied to the mammographic interpretation workflow …

Background Comparative performance between artificial intelligence (AI) and breast US for
women with dense breasts undergoing screening mammography remains unclear. Purpose …

Simple Summary The aim of this study was to perform an external validation in a US
screening cohort of a mammography-derived AI risk model that was originally developed in …

To investigate whether artificial-intelligence-based, computer-aided diagnosis (AI-CAD)
could facilitate the detection of missed cancer on digital mammography, a total of 204 …