Applications of machine learning (ML) methods have been used extensively to solve various
complex challenges in recent years in various application areas, such as medical, financial …

Lithium-ion battery is an appropriate choice for electric vehicle (EV) due to its promising
features of high voltage, high energy density, low self-discharge and long lifecycles. The …

What has happened in machine learning lately, and what does it mean for the future of
medical image analysis? Machine learning has witnessed a tremendous amount of attention …

Molecular imaging has experienced enormous advancements in the areas of imaging
technology, imaging probe and contrast development, and data quality, as well as machine …

Radiomics is an emerging translational field of research aiming to extract mineable high-
dimensional data from clinical images. The radiomic process can be divided into distinct …

Although rapid advances in machine learning have made it increasingly applicable to expert
decision-making, the delivery of accurate algorithmic predictions alone is insufficient for …

The goals of this review paper on deep learning (DL) in medical imaging and radiation
therapy are to (a) summarize what has been achieved to date;(b) identify common and …

Computer-aided diagnosis (CAD) in medicine is the result of a large amount of effort
expended in the interface of medicine and computer science. As some CAD systems in …

Recent critical commentaries unfavorably compare deep learning (DL) with standard
machine learning (SML) approaches for brain imaging data analysis. However, their …

Although computer-aided diagnosis (CAD) is widely used in mammography, conventional
CAD programs that use prompts to indicate potential cancers on the mammograms have not …