医学应用中的模糊专家系统广义模型

IF 0.5 Q4 COMPUTER SCIENCE, THEORY & METHODS Applied Computer Systems Pub Date : 2019-12-01 DOI:10.2478/acss-2019-0016
Osée Muhindo Masivi
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引用次数: 0

摘要

摘要近二十年来,医学模糊专家系统呈指数级增长。这些系统处理特定形式的医疗和健康问题,导致不同的模型,这些模型依赖于应用程序,可能缺乏适应性。本研究提出了一种包含现有专业模糊系统主要特征的广义模型。通过设计进行泛化建模,其中区分系统的主要组件被识别并用作一般模型的组件。原型表明,提出的模型允许医学专家为任何医疗应用定义模糊变量(规则库),用户输入症状(事实库)并从设计的广义核心推理引擎中询问他们的医疗状况。进一步的研究可能包括增加更多的组成条件,更多的组合技术和更多的测试在不同的环境,以检查其精度,灵敏度和特异性。
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Fuzzy Expert System Generalised Model for Medical Applications
Abstract Over the past two decades an exponential growth of medical fuzzy expert systems has been observed. These systems address specific forms of medical and health problems resulting in differentiated models which are application dependent and may lack adaptability. This research proposes a generalized model encompassing major features in specialized existing fuzzy systems. Generalization modelling by design in which the major components of differentiated the system were identified and used as the components of the general model. The prototype shows that the proposed model allows medical experts to define fuzzy variables (rules base) for any medical application and users to enter symptoms (facts base) and ask their medical conditions from the designed generalised core inference engine. Further research may include adding more composition conditions, more combining techniques and more tests in several environments in order to check its precision, sensitivity and specificity.
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来源期刊
Applied Computer Systems
Applied Computer Systems COMPUTER SCIENCE, THEORY & METHODS-
自引率
10.00%
发文量
9
审稿时长
30 weeks
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