接收机工作特性
线性判别分析
绘图(图形)
判别函数分析
逻辑回归
人工智能
模式识别(心理学)
计算机科学
数据挖掘
统计
数学
机器学习
作者
M H Zweig,Gregory Campbell
出处
期刊:Clinical Chemistry
[Oxford University Press]
日期:1993-04-01
卷期号:39 (4): 561-577
被引量:5855
标识
DOI:10.1093/clinchem/39.4.561
摘要
The clinical performance of a laboratory test can be described in terms of diagnostic accuracy, or the ability to correctly classify subjects into clinically relevant subgroups. Diagnostic accuracy refers to the quality of the information provided by the classification device and should be distinguished from the usefulness, or actual practical value, of the information. Receiver-operating characteristic (ROC) plots provide a pure index of accuracy by demonstrating the limits of a test's ability to discriminate between alternative states of health over the complete spectrum of operating conditions. Furthermore, ROC plots occupy a central or unifying position in the process of assessing and using diagnostic tools. Once the plot is generated, a user can readily go on to many other activities such as performing quantitative ROC analysis and comparisons of tests, using likelihood ratio to revise the probability of disease in individual subjects, selecting decision thresholds, using logistic-regression analysis, using discriminant-function analysis, or incorporating the tool into a clinical strategy by using decision analysis.
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