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A knowledge-based expert system for the planning of dental caries preventive programs.

机译：基于知识的专家系统，用于预防龋齿计划。

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摘要

One problem dental public health administrators or policy makers often face is difficulty in choosing among alternate dental caries preventive programs, including the option of no preventive program at all. Questions on what can be prevented and at what cost and by what means are always present. The aim of this project is to develop a Knowledge-Based Expert System (KBES) prototype to guide the planning of dental caries preventive programs. While a final choice must include judgment on the part of local decision makers, such a computer program may offer a valuable framework to guide the process of choice. The KBES prototype has been called Preventive Program Model (PPM) and was developed using the C Language Integrated Production System (Clips). It has three modules: (1) strategies recommended for fluoride-, diet- and sealant-based programs, (2) efficacy/effectiveness of dental caries preventive measures, and (3) an estimation model for the effectiveness of the sealant-based program. A pilot validation questionnaire completed by 13 dental experts (N = 18) tested the program input, output and the reasoning process. Fifty percent of respondents agreed that there was enough input information to recommend particular strategies and, 80% of the PPM outcomes for Module 1 were equivalent to the answers given by at least 50% of such respondents. In Module 3, the PPM estimation on the effectiveness of pit-and-fissure sealants gave comparable results to expert estimation. Such results suggest the potential use of knowledge-based expert systems in public health programs.
机译：牙科公共卫生管理人员或政策制定者经常面临的一个问题是难以在其他龋齿预防计划中进行选择，包括根本没有预防计划的选择。总是存在关于可以预防什么，以什么代价以及通过什么手段可以预防的问题。该项目的目的是开发一个基于知识的专家系统（KBES）原型，以指导龋齿预防计划的规划。虽然最终选择必须包括地方决策者的判断，但这种计算机程序可能会提供有价值的框架来指导选择过程。 KBES原型称为预防程序模型（PPM），是使用C语言集成生产系统（剪辑）开发的。它包含三个模块：（1）为基于氟化物，饮食和密封剂的计划推荐的策略；（2）预防龋齿的功效/效果；以及（3）基于密封剂的计划的有效性的估计模型。由13位牙科专家（N = 18）填写的试点验证问卷测试了程序的输入，输出和推理过程。 50％的受访者同意，有足够的输入信息来推荐特定策略，并且模块1的PPM结果的80％至少等于此类受访者的50％给出的答案。在第3单元中，关于坑缝密封剂有效性的PPM估算得出了与专家估算相当的结果。这样的结果表明在公共卫生计划中潜在使用基于知识的专家系统。

著录项

  • 作者

    Werner, Carlos Wagner de Araujo.;

  • 作者单位

    University of Michigan, School of Public Health.;

  • 授予单位 University of Michigan, School of Public Health.;
  • 学科 Dentistry.;Artificial intelligence.;Computer science.;Public health.
  • 学位 Dr.P.H.
  • 年度 1994
  • 页码 238 p.
  • 总页数 238
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
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