Catching-up on Research Related to AI-based Tools Implementation in Clinical Settings : Viewpoint (Preprint)

Abstract

There is a consensus among researchers and practitioners recognizing that the use of artificial intelligence (AI)-based tools can provide high benefits in addition to having significant impacts not only on the practice of medicine but also on medical training and education. At the same time, although the development of AI-based tools is progressing rapidly in the field of medicine, their implementation in clinical care practice situations has not yet become a generalized reality. This situation is partially due to the paucity of knowledge related to their implementation practices. Hence, investigating AI-based tool implementation best practices is crucial not only for their acceptance by the main stakeholders, but also for generating the expected benefits. Consequently, there is a pressing need to design best practices for implementing AI-based tools in clinical care practice settings. This view point is a calling that provides three axes of research worth pursuing to bridge the gap between the rapid development of AI-based tools in the field of medicine and their actual implementation in clinical care practice settings and thus it should be of interest to health professionals and researchers.