elahe soroush; Alireza Monajemi
Volume 7, Issue 14 , April 2018, , Pages 27-58
Abstract
In today’s world, technology plays an important and crucial role in medicine and healthcare. Medical Artificial Intelligence and Expert Systems are only subsets of the technologies which try to provide automated decision aids for physicians and clinicians. Their goal is to diagnose the illness ...
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In today’s world, technology plays an important and crucial role in medicine and healthcare. Medical Artificial Intelligence and Expert Systems are only subsets of the technologies which try to provide automated decision aids for physicians and clinicians. Their goal is to diagnose the illness and make treatment recommendations. MYClN and INTERNIST-I are among the earliest developed expert systems. However, despite the fact that several of these medical systems have achieved high levels of performance, hardly any has progressed from the research laboratory into practical use. But because of overpromising and failing to deliver them, in artificial intelligence researches face toreduced funding and interest. One of the major reason of these failures is inadequate attention and studies about epistemological considerations. In this paper we are looking for some epistemological obstacles which prevent AI from being successful in medicine. To do so we first briefly introduce cognition errors in medicine which motivate using AI in this field, then review several implemented medical AI systems and finally we discuss epistemological reasons which leads to failure of AI in medicine. These reasons are incorrect hypotheses about nature of knowledge, separating knowledge from decision strategies, inadequate consideration to tacit knowledge and separating knowledge from its context.
