Decision making based on evidence other than human reasoning is becoming increasingly important in healthcare. Much valuable evidence is in the form of the treatment processes used by healthcare institutions, and in their meta-analyses. This paper presents a new framework for representing and synthesizing knowledge from treatment processes, and discusses the role and integration of this knowledge in case-based reasoning systems. With respect to patient status, as single instants cannot convey sufficient information, time series are analyzed and classified to improve decision-making ability. We aim at the elicitation of new knowledge that is valuable for improving case-based reasoning steps, taking into account international standards, ontologies, information models, nomenclatures and multiple types of indicators. The integration of formal process-modeling in case-based reasoning is exemplified by a real-world application scenario. After evaluation with a medical-rehabilitation data set, results show a strong correspondence between treatment recommended by the proposed system and clinical practice
['Laia Subirats', 'Luigi Ceccaroni', 'Jose M. Maroto', 'Carmen de Pablo', 'Felip Miralles']
Medical-treatment Recommendation and the Integration of Process Models into Knowledge-based Systems