AI in medical education--another grand challenge for medical informatics.
The potential benefits of artificial intelligence in medicine (AIM) were never realized as anticipated. This paper addresses ways in which such potential can be achieved. Recent discussions of this topic have proposed a stronger integration between AIM applications and health information systems, and emphasize computer guidelines to support the new health care paradigms of evidence-based medicine and cost-effectiveness. These proposals, however, promote the initial definition of AIM applications as being AI systems that can perform or aid in diagnoses. We challenge this traditional philosophy of AIM and propose a new approach aiming at empowering health care workers to become independent self-sufficient problem solvers and decision makers. Our philosophy is based on findings from a review of empirical research that examines the relationship between the health care personnel's level of knowledge and skills, their job satisfaction, and the quality of the health care they provide. This review supports addressing the quality of health care by empowering health care workers to reach their full potential. As an aid in this empowerment process we argue for reviving a long forgotten AIM research area, namely, AI based applications for medical education and training. There is a growing body of research in artificial intelligence in education that demonstrates that the use of artificial intelligence can enhance learning in numerous domains. By examining the strengths of these educational applications and the results from previous AIM research we derive a framework for empowering medical personnel and consequently raising the quality of health care through the use of advanced AI based technology.
Lillehaug
S I
SI
Department of Medical Informatics and Computer Science, University of Linköping, Sweden. svili@ida.liu.se
Lajoie
S P
SP
D001185:Artificial Intelligence; D003657:Decision Making; D004501:Education, Medical / Q000379:methods*; D006282:Health Personnel; D006801:Humans; D007858:Learning; D008490:Medical Informatics / Q000193:education*; D011361:Professional Competence