Medical diagnosis as pattern recognition in a framework of information compression by multiple alignment, unification and search
J. Gerard Wolff
- Vol. 42, Iss: 2, pp 608-625
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TLDR
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; a framework that should facilitate unsupervised learning of medical knowledge and the integration of medical diagnosis with other AI applications.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.read more
Citations
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