title: An expert system designed as a tutoring tool in cervical cytology: TTCC-1 system.
abstract: A knowledge-based intelligent system being developed as a computer-assisted tutoring tool that can be used by teachers and students of cervical cytology is described. This system uses a combination of frames and rules as knowledge representation. Combination data structures called "prototypes" characterize the typical cytoplasmic and nuclear features of classes of cervical cells by using a specific prototype for each hypothesized cell type. A hypothesis-directed approach is used for problem solving. Rules are associated with each prototype or hypothesis. There are two major kinds of rules: deducing rules, used for deducing certainty factors (expressed as degrees of certainty of the hypotheses), and strategy rules, used for guiding the user in reaching a conclusion about the test cell. With an easy-to-use interactive menu, the user inputs a series of sets of qualitative cell features, which the system utilizes at various inference stages and finally arrives at a decision about the cell type.
authors.affiliation: Department of Electrical Engineering and Computer Science, Polytechnic University, Brooklyn, NY 11201.
authors.forename: Z Y
authors.initials: ZY
authors.lastname: Tang
authors.forename: A
authors.initials: A
authors.lastname: Savino
authors.forename: E K
authors.initials: EK
authors.lastname: Wong
authors.forename: L G
authors.initials: LG
authors.lastname: Koss
authors.forename: L G
authors.initials: LG
authors.lastname: Shaw
mesh_terms: D003585:Cell Biology / Q000193:education*; D002584:Cervix Uteri / Q000166:cytology*; D003194:Computer-Assisted Instruction / Q000295:instrumentation / Q000379:methods; D005103:Expert Systems; D005260:Female; D006801:Humans; D012984:Software