Abstract
A new generation of intelligent systems is growing up in the community of Artificial Intelligence in Medicine. The main goal of these systems is the representation and use of real theory of diseases, as they are represented in medical textbooks or in scientific articles, rather than the heuristic shortcuts of human experts. In this paper, we will argue that the difficulties in the integration of basic science and clinical knowledge in intelligent systems arise from ontological differences between these kinds of knowledge and that the solution can be found in their dynamic integration during the reasoning process. In order to illustrate this point, we will first describe an epistemological analysis of the interplay between basic science knowledge and clinical knowledge, and then we will provide the example of a computational architecture implementing this view.
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