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<p>Computing diagnoses in domains with continuously changing data is difficult but essential aspect of solving many problems. To address this task, a dynamic influence diagram (ID) construction and updating system (DYNASTY) and its application to constructing a decision-theoretic model to diagnose acute abdominal pain, which is a domain in which the findings evolve during the diagnostic process, are described. For a system that evolves over time, DYNASTY constructs a parsimonious ID and then dynamically updates the ID, rather than constructing a new network from scratch for every time interval. In addition, DYNASTY contains algorithms that test the sensitivity of the constructed network's system parameters. The main contributions are: (1) presenting an efficient temporal influence diagram technique based on parsimonious model construction; and (2) formalizing the principles underlying a diagnostic tool for acute abdominal pain that explicitly models time-varying findings.</p>
acute abdominal pain diagnosis; dynamic influence diagram construction and updating system; medical diagnostic computing; knowledge based systems; diagnostic reasoning; DYNASTY; decision-theoretic model; temporal influence diagram; parsimonious model; knowledge based systems; medical diagnostic computing; patient diagnosis

G. Provan and J. Clarke, "Dynamic Network Construction and Updating Techniques for the Diagnosis of Acute Abdominal Pain," in IEEE Transactions on Pattern Analysis & Machine Intelligence, vol. 15, no. , pp. 299-307, 1993.
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