Evaluation and Comparison of Diagnostic Test Performance Based on Information Theory

Özlem Ege Oruç, Armağan Kanca
{"title":"Evaluation and Comparison of Diagnostic Test Performance Based on Information Theory","authors":"Özlem Ege Oruç, Armağan Kanca","doi":"10.5923/J.STATISTICS.20110101.03","DOIUrl":null,"url":null,"abstract":"A fundamental concept of information theory, relative entropy and mutual information, is directly applicable to evaluation of diagnostic test performance. The aim of this study is to demonstrate how basic concepts in information theory apply to the problem of quantifying major depressive disorder diagnostic test performance. In this study, the per- formances of the Dexamethasone Suppression Test-DST and the Thyroid-Stimulating Hormone Test-TSH, two of the di- agnosis tests of Major Depressive Disorder, are evaluated with the method of Information Theory. The amount of informa- tion gained by performing a diagnostic test can be quantified by calculating the relative entropy between the posttest and pretest probability distributions. And also demonstrates that diagnostic test performance can be quantified as the average amount of information the test result provides about the disease state. It is aimed that this study will hopefully give various points of view to the researchers who want to make research on this subject by explaining how the tests used for the diag- nosis of various diseases are evaluated with this way.","PeriodicalId":91518,"journal":{"name":"International journal of statistics and applications","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2012-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International journal of statistics and applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5923/J.STATISTICS.20110101.03","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5

Abstract

A fundamental concept of information theory, relative entropy and mutual information, is directly applicable to evaluation of diagnostic test performance. The aim of this study is to demonstrate how basic concepts in information theory apply to the problem of quantifying major depressive disorder diagnostic test performance. In this study, the per- formances of the Dexamethasone Suppression Test-DST and the Thyroid-Stimulating Hormone Test-TSH, two of the di- agnosis tests of Major Depressive Disorder, are evaluated with the method of Information Theory. The amount of informa- tion gained by performing a diagnostic test can be quantified by calculating the relative entropy between the posttest and pretest probability distributions. And also demonstrates that diagnostic test performance can be quantified as the average amount of information the test result provides about the disease state. It is aimed that this study will hopefully give various points of view to the researchers who want to make research on this subject by explaining how the tests used for the diag- nosis of various diseases are evaluated with this way.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
基于信息论的诊断试验性能评价与比较
信息论的一个基本概念,即相对熵和互信息,直接适用于诊断测试性能的评估。本研究的目的是展示信息论的基本概念如何应用于量化重度抑郁症诊断测试表现的问题。本研究运用信息论的方法对重度抑郁症的两项诊断测试——地塞米松抑制测试(dst)和促甲状腺激素测试(tsh)的表现进行评价。通过执行诊断测试获得的信息量可以通过计算测试后和测试前概率分布之间的相对熵来量化。并且还证明了诊断测试性能可以量化为测试结果提供的关于疾病状态的平均信息量。本研究旨在通过解释如何用这种方法评估用于各种疾病诊断的测试,为想要研究这一主题的研究人员提供不同的观点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
A Study of the Non-Medical Use of Pharmaceutical Drugs among Tertiary Institution Students in South-East Nigeria Another Two-Parameter Poisson –Sujatha Distribution A New Method for Generating Distributions: An Application to Flow Data Weighted Quasi Lindley Distribution with Properties and Applications Household Poverty-Risk Analysis and Prediction Using Bayesian Ordinal Probit Models
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1