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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.

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Citations
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Graph Classification and Clustering Based on Vector Space Embedding

Kaspar Riesen, +1 more
TL;DR: A fundamentally novel approach to graph-based pattern recognition based on vector space embedding of graphs based on dissimilarity space representation originally proposed by Duin and Pekalska to embed graphs in real vector spaces is proposed.
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Intuitionistic fuzzy set vs. fuzzy set application in medical pattern recognition

TL;DR: This investigation shows that both frameworks have powerful capabilities to cope with the uncertainty in the medical pattern recognition problems, but, IFSs yield better detection rate as a result of more accurate modeling which is involved with incurring more computational cost.

Heart Disease Diagnosis using Support Vector Machine

TL;DR: Application of artificial intelligence in typical heart disease diagnosis has been investigated and it is shown that support vector machine can be successfully used for diagnosing heart disease.
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A Novel Fuzzy-Neural Based Medical Diagnosis System

TL;DR: In this article, the real procedure of medical diagnosis which usually is employed by physicians was analyzed and converted to a machine implementable format, and after selecting some symptoms of eight different diseases, a data set contains the information of a few hundreds cases was configured and applied to a MLP neural network.
Journal ArticleDOI

Big Data and the SP Theory of Intelligence

J. Gerard Wolff
- 02 Apr 2014 - 
TL;DR: The SP system-introduced in this paper and fully described elsewhere-may help to overcome the problem of variety in big data and has potential as a universal framework for the representation and processing of diverse kinds of knowledge.
References
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TL;DR: The author examines the role of entropy, inequality, and randomness in the design of codes and the construction of codes in the rapidly changing environment.
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Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference

TL;DR: Probabilistic Reasoning in Intelligent Systems as mentioned in this paper is a complete and accessible account of the theoretical foundations and computational methods that underlie plausible reasoning under uncertainty, and provides a coherent explication of probability as a language for reasoning with partial belief.
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Fuzzy Sets and Fuzzy Logic: Theory and Applications

TL;DR: Fuzzy Sets and Fuzzy Logic is a true magnum opus; it addresses practically every significant topic in the broad expanse of the union of fuzzy set theory and fuzzy logic.
Journal ArticleDOI

Paper: Modeling by shortest data description

Jorma Rissanen
- 01 Sep 1978 - 
TL;DR: The number of digits it takes to write down an observed sequence x1,...,xN of a time series depends on the model with its parameters that one assumes to have generated the observed data.
Journal Article

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TL;DR: XML is an extremely simple dialect of SGML which is completely described in this document, to enable generic SGML to be served, received, and processed on the Web in the way that is now possible with HTML.
Trending Questions (1)
Is medical diagnosis simply a matter of selecting the highest probability match of symptoms?

The paper does not directly answer the question. The paper discusses a novel approach to medical diagnosis based on the SP theory of computing and cognition, but it does not specifically address whether medical diagnosis is simply a matter of selecting the highest probability match of symptoms.