A formal model of diagnostic inference. I. Problem formulation and decomposition

doi:10.1016/0020-0255(85)90015-5

Information Sciences

Volume 37, Issues 1–3, December 1985, Pages 227-256

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Abstract

This paper, which is Part I of a two-part series, introduces a new model of diagnostic problem solving based on a generalization of the set-covering problem. The model formalizes the concepts of

1.
(1) whether or not a set of one or more disorders is sufficient to explain a set of occurring manifestations,
2.
(2) what a solution is for a diagnostic problem, and
3.
(3) how to generate all of the alternative explanations in a problem's solution.

In addition, conditions for decomposing a diagnostic problem into independent subproblems are stated and proven. This model is of interest because it captures several intuitively plausible features of human diagnostic inference, it directly addresses the issue of multiple simultaneous causative disorders, it can serve as a theoretical basis for expert systems for diagnostic problem solving, and it provides a conceptual framework within which to view some recent AI work on diagnostic problem solving in general. In Part II, the concepts developed in this paper will be used to present algorithms for diagnostic problem solving.

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A formal model of diagnostic inference. I. Problem formulation and decomposition

Abstract

Math. Biosci

Amer. J. Med.

Internat. J. Man-Machine Stud.

Comput. Programs Biomed.

Comput. Programs Biomed.

The diagnostic (problem solving) skill of the neurologist

Arch. Neurol.

Pattern-based interactive diagnosis of multiple disorders: The medas system

IEEE Trans. Pattern Anal. and Machine Intelligence

The diagnostic process

A computational survey of methods for the set covering problem

Management Sci.

Computer assisted diagnosis of abdominal pain