Abstract and concrete categories
Abstract and concrete categories
Specification of abstract data types
Specification of abstract data types
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Clinical knowledge building upon evidence-based medicine is typically represented in textual guidelines, thus providing a rather informal description from a logical point of view. Further, the context which provides utility of these guidelines is not specified in any detail with respect to workflow and underlying motivations for decision-making. In addition, the level of detail is mostly static in the sense that measurements and decision values are fixed and intended for specific user groups. There is thus a lack of flexibility which disables knowledge to be shifted coherently between user levels in the entire workflow and decision process. In this paper, we will discuss formalizations of the underlying logical structures of guidelines from the viewpoint of being represented appropriately at each user level. Further, to establish a formal correctness criterion, the shift from one level of representation to another is required to be morphic in the categorical sense. General logics [7] is the selected generalized, and categorical, framework for our approach to flexible guideline representation. Our medical scope is dementia differential diagnosis based on consensus guidelines [2], and we focus on types of cognitive disorders as a prerequisite for further diagnostic tasks.