Deep learning has received extensive research interest in develo** new medical image
processing algorithms, and deep learning based models have been remarkably successful …

Significant evolution in deep learning took place in 2010, when software developers started
using graphical processing units for general-purpose applications. From that date, the deep …

Since its renaissance, deep learning has been widely used in various medical imaging tasks
and has achieved remarkable success in many medical imaging applications, thereby …

Coronavirus (COVID-19) is a viral disease caused by severe acute respiratory syndrome
coronavirus 2 (SARS-CoV-2). The spread of COVID-19 seems to have a detrimental effect …

The number of publications on deep learning for cancer diagnostics is rapidly increasing,
and systems are frequently claimed to perform comparable with or better than clinicians …

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 …

Deep learning methods, and in particular convolutional neural networks (CNNs), have led to
an enormous breakthrough in a wide range of computer vision tasks, primarily by using …

Transfer learning from natural images to medical images has been established as one of the
most practical paradigms in deep learning for medical image analysis. To fit this paradigm …

Cancer is a fatal illness often caused by genetic disorder aggregation and a variety of
pathological changes. Cancerous cells are abnormal areas often growing in any part of …

Artificial intelligence (AI) has contributed substantially to the resolution of a variety of
biomedical problems, including cancer, over the past decade. Deep learning, a subfield of AI …