Aim: To evaluate the value of S-Detect (a computer aided diagnosis system using deep
learning) in breast ultrasound (US) for discriminating benign and malignant breast masses …

Objectives To systematically synthesise available evidence on the nature and effectiveness
of interventions for improving timely diagnosis of breast and cervical cancers in low and …

Purpose: To evaluate the performance of an artificial intelligence (AI) algorithm in a
simulated screening setting and its effectiveness in detecting missed and interval cancers …

Purpose In this study, we aimed to investigate the viability of utilizing CytoSorter® system to
detect circulating tumor cells (CTCs) and to evaluate the diagnostic value of CTCs in breast …

As the core of deep learning methodologies, convolutional neural network (CNN) has
received wide attention in the area of image recognition. In particular, it requires very …

The most common and rapidly spreading disease in the world is breast cancer. Most cases
of breast cancer are observed in females. Breast cancer is controlled with early detection …

We aimed to determine the value of standalone and supplemental automated breast
ultrasound (ABUS) in detecting cancers in an opportunistic screening setting with digital …

PURPOSE We aimed to show the effects of long-term screening on clinical, pathologic, and
survival outcomes in patients with screen-detected breast cancer and compare these …

Background The Bahçeşehir population-based mammography screening program (BMSP)
is an example of Türkiye's first population-based screening program. This study aims to …

Background Developing countries face great challenges in health care because of changing
disease dynamics and the increasing burden of chronic diseases such as cancers. Thus …