This survey aims to identify commonly used methods, datasets, future trends, knowledge
gaps, constraints, and limitations in the field to provide an overview of current solutions used …

The vast amount of data produced by today's medical imaging systems has led medical
professionals to turn to novel technologies in order to efficiently handle their data and exploit …

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 …

Machine learning techniques are essential components of medical imaging research.
Recently, a highly flexible machine learning approach known as deep learning has …

AI systems are quickly being adopted in radiology and, in general, in healthcare. A myriad of
systems is being proposed and developed on a daily basis for high-stake decisions that can …

COVID-19 is one of the greatest global public health challenges in history. COVID-19 is
caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and is …

Artificial intelligence has provided us with an exploration of a whole new research era. As
more data and better computational power become available, the approach is being …

Healthcare data are inherently multimodal. Almost all data generated and acquired during a
patient's life can be hypothesized to contain information relevant to providing optimal …

CCS Concepts:• Computing methodologies→ Machine learning approaches; Machine
learning;• Social and professional topics→ Computing/technology policy; Medical …

Purpose Artificial intelligence (AI) models are playing an increasing role in biomedical
research and healthcare services. This review focuses on challenges points to be clarified …