Objectives Map the current landscape of commercially available artificial intelligence (AI)
software for radiology and review the availability of their scientific evidence. Methods We …

Simple Summary Lung cancer is the leading cause of malignancy-related mortality
worldwide. AI has the potential to help to treat lung cancer from detection, diagnosis and …

Objectives Radiologists' perception is likely to influence the adoption of artificial intelligence
(AI) into clinical practice. We investigated knowledge and attitude towards AI by radiologists …

Objectives Currently, hurdles to implementation of artificial intelligence (AI) in radiology are
a much-debated topic but have not been investigated in the community at large. Also …

AI is a broad concept, grouping initiatives that use a computer to perform tasks that would
usually require a human to complete. AI methods are well suited to predict clinical outcomes …

Over the past few years, artificial intelligence (AI) has made a significant advance in the
medical world, particularly due to developments in the field of machine learning (ML) and …

Objectives A critical problem in radiomic studies is the high dimensionality of the datasets,
which stems from small sample sizes and many generic features extracted from the volume …

Objectives Disseminated bone marrow (BM) involvement is frequent in multiple myeloma
(MM). Whole-body magnetic resonance imaging (wb-MRI) enables to evaluate the whole …

Objective Although artificial intelligence (AI) has demonstrated promise in enhancing breast
cancer diagnosis, the implementation of AI algorithms in clinical practice encounters various …

Quantum machine learning is receiving significant attention currently, but its usefulness in
comparison to classical machine learning techniques for practical applications remains …