One of the most promising areas of health innovation is the application of artificial
intelligence (AI), primarily in medical imaging. This article provides basic definitions of terms …

Radiomics research is rapidly growing in recent years, but more concerns on radiomics
reliability are also raised. This review attempts to update and overview the current status of …

Advances in both imaging and computers have led to the rise in the potential use of artificial
intelligence (AI) in various tasks in breast imaging, going beyond the current use in …

Machine‐learning techniques have led to remarkable advances in data extraction and
analysis of medical imaging. Applications of machine learning to breast MRI continue to …

OBJECTIVE. The purpose of this article is to compare traditional versus machine learning–
based computer-aided detection (CAD) platforms in breast imaging with a focus on …

The degree of normal fibroglandular tissue that enhances on breast MRI, known as
background parenchymal enhancement (BPE), was initially described as an incidental …

The adoption of enterprise digital imaging, along with the development of quantitative
imaging methods and the re-emergence of statistical learning, has opened the opportunity …

Breast cancer remains the most diagnosed cancer in women. Advances in medical imaging
modalities and technologies have greatly aided in the early detection of breast cancer and …

In recent years, machine learning (ML) researchers have changed their focus towards
biological problems that are difficult to analyse with standard approaches. Large initiatives …

Simple Summary Currently, breast contrast-enhanced MRI is the most sensitive imaging
technique for breast cancer detection; however, its specificity is low given the common …