Abstract
Models have traditionally been mostly either prescriptive, expressing the function, structure and behavior of a system-to-be, or descriptive, specifying a system so it can be understood and analyzed. In this work, we offer a third kind—diagnostic models. We have built a model for assessing potential pediatric failure to thrive (FTT) during the perinatal stage. Although FTT is commonly found in young children and has been studied extensively, the exact etiology is often not clear. The ideal solution is for a pediatrician to input pertinent data and information in a single tool in order to obtain some assessment on the potential etiology. We present FTTell—an executable model-based medical knowledge aggregation and diagnosis tool, in which the qualitative considerations and quantitative parameters of the problem are modeled using a Methodical Approach to Executable Integrative Modeling (MAXIM)—an extended version of Object-Process Methodology (OPM) ISO 19450, focusing on the perinatal stage. The efficacy of the tool is demonstrated on three real-life cases, and the tool’s diagnosis outcomes may be compared with and critiqued by a domain expert.
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The research in this paper was partially funded by the Gordon Center for Systems Engineering at the Technion, Israel Institute for Technology.
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Levi-Soskin, N., Shaoul, R., Kohen, H., Jbara, A., Dori, D. (2019). Model-Based Diagnosis with FTTell: Assessing the Potential for Pediatric Failure to Thrive (FTT) During the Perinatal Stage. In: Wrycza, S., Maślankowski, J. (eds) Information Systems: Research, Development, Applications, Education. SIGSAND/PLAIS 2019. Lecture Notes in Business Information Processing, vol 359. Springer, Cham. https://doi.org/10.1007/978-3-030-29608-7_4
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