Judgement, as one of the core tenets of medicine, relies upon the integration of multilayered
data with nuanced decision making. Cancer offers a unique context for medical decisions …

Abstract Machine learning (ML) is a burgeoning field of medicine with huge resources being
applied to fuse computer science and statistics to medical problems. Proponents of ML extol …

Computer‐aided diagnosis (CAD) has been a major field of research for the past few
decades. CAD uses machine learning methods to analyze imaging and/or nonimaging …

OBJECTIVE. Machine learning (ML) and artificial intelligence (AI) are rapidly becoming the
most talked about and controversial topics in radiology and medicine. Over the past few …

In this paper, we give a short introduction to machine learning and survey its applications in
radiology. We focused on six categories of applications in radiology: medical image …

Computer-aided diagnosis (CAD), encompassing computer-aided detection and
quantification, is an established and rapidly growing field of research. In daily practice …

The roles of physicists in medical imaging have expanded over the years, from the study of
imaging systems (sources and detectors) and dose to the assessment of image quality and …

Background The aim of this study was to develop and evaluate a deep neural network
model in the automated detection of pulmonary embolism (PE) from computed tomography …

Supplying a comprehensive overview of healthcare analytics research, Healthcare Data
Analytics provides an understanding of the analytical techniques currently available to solve …

Computer‐aided detection and diagnosis (CAD) systems are increasingly being used as an
aid by clinicians for detection and interpretation of diseases. Computer‐aided detection …