Background Artificial intelligence (AI) is often heralded as a potential disruptor that will
transform the practice of medicine. The amount of data collected and available in health …

Tissue engineering research has undergone to a revolutionary improvement, thanks to
technological advancements, such as the introduction of bioprinting technologies. The ability …

Background Artificial intelligence (AI) for healthcare presents potential solutions to some of
the challenges faced by health systems around the world. However, it is well established in …

Objective The attitudes about the usage of artificial intelligence in healthcare are
controversial. Unlike the perception of healthcare professionals, the attitudes of patients and …

Abstract Forms of Artificial Intelligence (AI) are already being deployed into clinical settings
and research into its future healthcare uses is accelerating. Despite this trajectory, more …

Diabetic retinopathy (DR) is a leading cause of blindness globally. There is growing
evidence to support the use of artificial intelligence (AI) in diabetic eye care, particularly for …

Background The number of artificial intelligence (AI) studies in medicine has exponentially
increased recently. However, there is no clear quantification of the clinical benefits of …

eXplainable AI (XAI) involves two intertwined but separate challenges: the development of
techniques to extract explanations from black-box AI models and the way such explanations …

Objective Despite recent calls for home healthcare (HHC) to integrate informatics, the
application of machine learning in HHC is relatively unknown. Thus, this study aimed to …

Objectives This study aimed to systematically review recent health economic evaluations
(HEEs) of artificial intelligence (AI) applications in healthcare. The aim was to discuss …