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Expert systems in histopathology. II. Knowledge representation and rule-based systems.

作者信息

Bartels P H, Hiessl H

机构信息

Optical Sciences Center, University of Arizona, Tucson 85721.

出版信息

Anal Quant Cytol Histol. 1989 Jun;11(3):147-53.

PMID:2663006
Abstract

Two aspects of expert systems for use in diagnostic histopathology and cytopathology are examined: knowledge representation and the structure and operation of rule-based systems. Knowledge may be represented, e.g., in semantic networks, frames, multiple contexts and model-based structures; the choice of structure should be matched to the type of information to create an efficient and logically adequate expert system. In a rule-based system, knowledge is represented as "rules," often in the form of "IF (condition)-THEN (conclusion)" rules. The anatomy of such rules and their operation is explored via the use of examples. Uncertainty in rules is briefly addressed, and their processing by the symbolic reasoning of the "inference engine" of the expert system is described, including both "forward-chaining" ("data-driven") operations and "backward-chaining" ("goal-driven") operations.

摘要

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