A Review of the Application of Information Theory to Clinical Diagnostic Testing

被引:10
作者
Benish, William A. [1 ]
机构
[1] Case Western Reserve Univ, Dept Internal Med, Cleveland, OH 44106 USA
关键词
entropy; information theory; multiple diagnostic tests; mutual information; relative entropy;
D O I
10.3390/e22010097
中图分类号
O4 [物理学];
学科分类号
0702 ;
摘要
The fundamental information theory functions of entropy, relative entropy, and mutual information are directly applicable to clinical diagnostic testing. This is a consequence of the fact that an individual's disease state and diagnostic test result are random variables. In this paper, we review the application of information theory to the quantification of diagnostic uncertainty, diagnostic information, and diagnostic test performance. An advantage of information theory functions over more established test performance measures is that they can be used when multiple disease states are under consideration as well as when the diagnostic test can yield multiple or continuous results. Since more than one diagnostic test is often required to help determine a patient's disease state, we also discuss the application of the theory to situations in which more than one diagnostic test is used. The total diagnostic information provided by two or more tests can be partitioned into meaningful components.
引用
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页数:20
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