Dynamic Network Construction and Updating Techniques for the Diagnosis of Acute Abdominal Pain

Computing diagnoses in domains with continuously changing data is a difficult but essential aspect of solving many problems. To address this task, this paper describes 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. 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 of this paper 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.