Deep learning with a convolutional neural network (CNN) is gaining attention recently for its
high performance in image recognition. Images themselves can be utilized in a learning …

Deep learning has been applied to clinical applications in not only radiology, but also all
other areas of medicine. This review provides a technical and clinical overview of deep …

The artificial neural network (ANN)–a machine learning technique inspired by the human
neuronal synapse system–was introduced in the 1950s. However, the ANN was previously …

The use of machine learning (ML) has been increasing rapidly in the medical imaging field,
including computer-aided diagnosis (CAD), radiomics, and medical image analysis …

Deep learning has rapidly advanced in various fields within the past few years and has
recently gained particular attention in the radiology community. This article provides an …

Deep learning is a branch of artificial intelligence where networks of simple interconnected
units are used to extract patterns from data in order to solve complex problems. Deep …

Deep learning (DL) is one of the branches of artificial intelligence that has seen exponential
growth in recent years. The scientific community has focused its attention on DL due to its …

As radiology is inherently a data-driven specialty, it is especially conducive to utilizing data
processing techniques. One such technique, deep learning (DL), has become a remarkably …

Artificial intelligence (AI) is the most revolutionizing development in the health care industry
in the current decade, with diagnostic imaging having the greatest share in such …

Deep learning is a class of machine learning methods that are gaining success and
attracting interest in many domains, including computer vision, speech recognition, natural …