模糊逻辑:预测乳糜泻最简单的技术

Sunny Thukral, J. Bal
{"title":"模糊逻辑:预测乳糜泻最简单的技术","authors":"Sunny Thukral, J. Bal","doi":"10.22232/stj.2019.07.02.11","DOIUrl":null,"url":null,"abstract":"The need for the proposed system mounts due to expensive clinical cost, the prolonged period of Genetic testing and especially painful for an individual to perform all certain clinical tests to diagnose celiac disease. With this proposed method, an individual can foretell celiac disease by just input crisp values of varied symptoms using fuzzy logic. A case study was conducted using a questionnaire procedure to obtain out the requisite symptoms in Amritsar, Punjab on 700 individuals; having 303 females and 393 males. So, the proposed system will be implemented using Mamdani Model and forms the prediction output practicing de-fuzzification when correlated with computed values produced optimum correctness. The proposed system will have a disease prediction of 96.11% accuracy according to the input values given by an individual to authenticate the celiac disease. The proposed system will provide a fruitful outcome for individuals and physicians for celiac disease disclosure in few seconds without any painful testing strategy.","PeriodicalId":22107,"journal":{"name":"Silpakorn University Science and Technology Journal","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Fuzzy Logic: An Easiest Technique to Predict Celiac Disease\",\"authors\":\"Sunny Thukral, J. Bal\",\"doi\":\"10.22232/stj.2019.07.02.11\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The need for the proposed system mounts due to expensive clinical cost, the prolonged period of Genetic testing and especially painful for an individual to perform all certain clinical tests to diagnose celiac disease. With this proposed method, an individual can foretell celiac disease by just input crisp values of varied symptoms using fuzzy logic. A case study was conducted using a questionnaire procedure to obtain out the requisite symptoms in Amritsar, Punjab on 700 individuals; having 303 females and 393 males. So, the proposed system will be implemented using Mamdani Model and forms the prediction output practicing de-fuzzification when correlated with computed values produced optimum correctness. The proposed system will have a disease prediction of 96.11% accuracy according to the input values given by an individual to authenticate the celiac disease. The proposed system will provide a fruitful outcome for individuals and physicians for celiac disease disclosure in few seconds without any painful testing strategy.\",\"PeriodicalId\":22107,\"journal\":{\"name\":\"Silpakorn University Science and Technology Journal\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Silpakorn University Science and Technology Journal\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.22232/stj.2019.07.02.11\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Silpakorn University Science and Technology Journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.22232/stj.2019.07.02.11","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3

摘要

由于昂贵的临床费用、长期的基因检测以及对个人进行所有诊断乳糜泻的临床检测的痛苦,对拟议系统的需求增加了。使用该方法,个体可以通过使用模糊逻辑输入各种症状的清晰值来预测乳糜泻。在旁遮普省阿姆利则,对700人进行了案例研究,采用问卷调查程序得出了必要的症状;有303名女性和393名男性。因此,所提出的系统将使用Mamdani模型实现,并在与计算值相关时形成进行去模糊化的预测输出,从而产生最佳的正确性。根据个人提供的诊断乳糜泻的输入值,该系统的疾病预测准确率将达到96.11%。该系统将为个人和医生在几秒钟内提供富有成效的结果,而无需任何痛苦的测试策略。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Fuzzy Logic: An Easiest Technique to Predict Celiac Disease
The need for the proposed system mounts due to expensive clinical cost, the prolonged period of Genetic testing and especially painful for an individual to perform all certain clinical tests to diagnose celiac disease. With this proposed method, an individual can foretell celiac disease by just input crisp values of varied symptoms using fuzzy logic. A case study was conducted using a questionnaire procedure to obtain out the requisite symptoms in Amritsar, Punjab on 700 individuals; having 303 females and 393 males. So, the proposed system will be implemented using Mamdani Model and forms the prediction output practicing de-fuzzification when correlated with computed values produced optimum correctness. The proposed system will have a disease prediction of 96.11% accuracy according to the input values given by an individual to authenticate the celiac disease. The proposed system will provide a fruitful outcome for individuals and physicians for celiac disease disclosure in few seconds without any painful testing strategy.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信