Medical diagnosis as pattern recognition in a framework of information compression by multiple alignment, unification and search

  • Authors:

  • J. Gerard Wolff

  • Affiliations:

  • CognitionResearch.org.uk, Menai Bridge, UK

  • Venue:
  • Decision Support Systems
  • Year:
  • 2006

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Abstract

This paper describes a novel approach to medical diagnosis based on the SP theory of computing and cognition. The main attractions of this approach are: a format for representing diseases that is simple and intuitive; an ability to cope with errors and uncertainties in diagnostic information; the simplicity of storing statistical information as frequencies of occurrence of diseases; a method for evaluating alternative diagnostic hypotheses that yields true probabilities; and a framework that should facilitate unsupervised learning of medical knowledge and the integration of medical diagnosis with other AI applications.