文章基本信息

标题：A Decision Support System for Tuberculosis Diagnosability
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作者：Navneet Walia ; Harsukpreet Singh ; Sharad Kumar Tiwari 等
期刊名称：International Journal on Soft Computing
电子版ISSN：2229-7103
出版年度：2015
卷号：6
期号：3
页码：1
DOI：10.5121/ijsc.2015.6301
出版社：Academy & Industry Research Collaboration Center (AIRCC)
摘要：In order to cope with real-world problems more effectively, we tend to design a decision support system fortuberculosis bacterium class identification. In this paper, we are concerned to propose a fuzzydiagnosability approach, which takes value between {0, 1} and based on observability of events, weformalized the construction of diagnoses that are used to perform diagnosis. In particular, we present aframework of the fuzzy expert system; discuss the suitability of artificial intelligence as a novel softparadigm and reviews work from the literature for the development of a medical diagnostic system. Thenewly proposed approach allows us to deal with problems of diagnosability for both crisp and fuzzy valueof input data. Accuracy analysis of designed decision support system based on demographic data was doneby comparing expert knowledge and system generated response. This basic emblematic approach usingfuzzy inference system is presented that describes a technique to forecast the existence of bacterium andprovides support platform to pulmonary researchers in identifying the ailment effectively.
关键词：Expert system; fuzzy diagnosability; rulebased method; MATLAB; Tuberculosis (TB).