Abstract
We present the results of a pilot study created to explore a sub-set of complex data, utilizing an agent-based model simulation tool. These results center on data taken from hospital admission records, tracking patient attributes and how they relate to patient outcomes. The focus of this work is to highlight three design principles: 1) using an iterative process between the modeling of a system and the grounding of that simulation with real-world data; 2) a focus on agent primitives, emphasizing bottom-up emergence of effects, rather than topdown control; and 3) integration of various “theories” of patient care and hospital effectiveness as a method for experimentation with Complex Adaptive Systembased data mining.
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Carmichael, T., Hadzikadic, M., Gajic, O. (2010). Pilot Study: Agent-Based Exploration of Complex Data in a Hospital Environment. In: Cao, L., Bazzan, A.L.C., Gorodetsky, V., Mitkas, P.A., Weiss, G., Yu, P.S. (eds) Agents and Data Mining Interaction. ADMI 2010. Lecture Notes in Computer Science(), vol 5980. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15420-1_3
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DOI: https://doi.org/10.1007/978-3-642-15420-1_3
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