Formalization and Induction of Medical Expert System Rules Based on Rough Set Theory

An algorithm of uncertain reasoning which more than one result of a new object can be obtained according to the known knowledge is an important part of an expert system. A new object is an especial decision rule which has only a predecessor. In order to resolve the problem that the differences of attributes’ importance in the new object are not considered in traditional methods of uncertain reasoning, a new uncertain reasoning algorithm based on the rules set which is obtained on the basis of the rough set theory is proposed. In the algorithm, both subjective factors and objective factors in the process of reasoning are considered, and the proportion of subjective factors to objective factors can be controlled by users. So the algorithm is better than the tradition method in flexibility and practicability.

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Designing a Rule Based Expert System for Selecting Pavement Rehabilitation Treatments Using Rough Set Theory

Intelligent Decision Technologies - Smart Innovation, Systems and Technologies ◽

10.1007/978-3-642-29977-3_47 ◽

2012 ◽

pp. 471-480 ◽

Cited By ~ 1

Author(s):

Ehsan Akhlaghi ◽

Farshid Abdi

Keyword(s):

Expert System ◽

Set Theory ◽

Rough Set ◽

Rough Set Theory ◽

Pavement Rehabilitation ◽

Rule Based

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Fault diagnosis model based on rough set theory and expert system

2009 ISECS International Colloquium on Computing, Communication, Control, and Management ◽

10.1109/cccm.2009.5267478 ◽

2009 ◽

Author(s):

Zuo Yougang

Keyword(s):

Fault Diagnosis ◽

Expert System ◽

Set Theory ◽

Rough Set ◽

Rough Set Theory ◽

Model Based ◽

Diagnosis Model

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Present State of the Medical Expert System CADIAG-2

Methods of Information in Medicine ◽

10.1055/s-0038-1635354 ◽

1985 ◽

Vol 24 (01) ◽

pp. 13-20 ◽

Cited By ~ 47

Author(s):

K.-P. Adlassnig ◽

G. Kolarz ◽

W. Scheithauer

Keyword(s):

Expert System ◽

Clinical Diagnosis ◽

Set Theory ◽

Fuzzy Set ◽

Fuzzy Set Theory ◽

Mathematical Tool ◽

Diagnostic Systems ◽

Medical Expert ◽

Medical Expert System ◽

Medical Diagnostic

SummaryUncertainty of knowledge about the patient and about medical relationships is generally accepted and considered to be an inherent concept in medicine. The physician, however, is quite capable of drawing conclusions from this information. Naturally, these conclusions are approximate rather than precise.Fuzzy set theory provides the possibility of defining imprecise medical entities as fuzzy sets. It offers a linguistic concept with excellent approximation to medical texts. In addition, fuzzy logic presents powerful reasoning methods that can handle approximate inferences. These facts make fuzzy set theory highly suitable for the development of computer-based medical diagnostic systems.The medical expert system CADIAG-2 provides evidence that fuzzy set theory is a suitable mathematical tool for formalizing medical processes.CADIAG-2/RHEUMA is being extensively tested on cases from a rheumatological hospital. Results from 327 cases are presented. In 265 cases, i.e. 81%, the clinical diagnosis could be either confirmed (223 cases, i.e. 68.2%) or established as a diagnostic hypothesis (42 cases, i.e. 12.8%).CADIAG-2/PANCREAS was tested on 47 cases of pancreatic diseases. In 43 cases, i.e. 91.5%, the clinical diagnosis was either confirmed by CADIAG-2 or established as one of the hypotheses with the highest or second highest number of points in a ranked list of hypotheses.

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