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Journal of Healthcare Engineering
Volume 2, Issue 2, Pages 241-258
Research Article

Modeling Medical Diagnosis Using a Comprehensive Cognitive Architecture

Stephen Strain1 and Stan Franklin2

1Department of Biomedical Engineering, University of Memphis, Memphis, TN, USA
2Department of Computer Science, University of Memphis, Memphis, TN, USA

Received 1 July 2010; Accepted 1 December 2010

Copyright © 2011 Hindawi Publishing Corporation. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Medical diagnosis is accomplished by a set of complex cognitive processes requiring the iterative application of abduction, deduction, and induction. Previous research in computational modeling of medical diagnosis has had only limited success by defining sub-domains that offer a computationally tractable problem. However, the aspect of diagnostic reasoning requiring intelligence lies in the extraction of a well-structured problem from an ill-structured one. We propose an agent, based on the Learning Intelligent Distribution Agent (LIDA) model of cognition, which utilizes deliberation, learning, and a neurologically inspired cognitive cycle. The proposed agent, MAX (for "Medical Agent X") will be equipped to comprehend clinical data in the context of its perceptual ontology and learned associations, and to construct, evaluate, and refine by investigation a differential diagnosis that progressively reduces the dimensionality of its search space with each iteration. Furthermore, the agent will appropriately modify its own ontology with experience and supervised instruction.