A connectionist processing metaphor for diagnostic reasoning

Abstract

This article describes LIBRA/Dx, a competition-based parallel activation model for diagnostic reasoning. Within a causal network, the model uses a neurally inspired processing paradigm to generate the most plausible explanation for a set of observed manifestations. the model was built using LIBRA: a domain-independent parallel activation network generator, that can be used to build network models with processing paradigms that are tailored to the specifics of an application domain. the underlying theory postulates that by simultaneously satisfying multiple constraints that may exist locally among domain concepts in a causal network (e.g., among disorders, syndromes, manifestations, etc.) it is possible to construct a plausible global explanation for a set of observed signs and symptoms. the proposed processing paradigm which uses an associative network of concepts to represent domain knowledge, lends itself to the kind of interactive processing that is necessary to capture the generative capacity of human diagnostic ability in novel situations. LIBRA/Dx offers a new approach to modeling a higher cognitive process: diagnostic reasoning, specifically in terms of the time-course of processing and the nature of knowledge representation. It further contributes to our current understanding of the phenomena of human cognition, which have eluded successful explication in conventional computational formalisms. (Also with the University of Maryland Institute for Advanced Computer Studies (UMIACS). This research was supported in part by the Air Force Office of Scientific Research Award AFOSR-87-0335 and by the Swiss Life Insurance and Pension Company (RENTENANSTALT), Zurich. © 1989 Wiley Periodicals, Inc.)