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  • 标题:Quantifying Relative Superiority among Many Binary-valued Diagnostic Tests in the Presence of a Gold Standard
  • 本地全文:下载
  • 作者:Reena Deutsch ; Monica Rivera Mindt ; Ronghui Xu
  • 期刊名称:Journal of Data Science
  • 印刷版ISSN:1680-743X
  • 电子版ISSN:1683-8602
  • 出版年度:2009
  • 卷号:7
  • 期号:02
  • 页码:161-177
  • 出版社:Tingmao Publish Company
  • 摘要:

    Comparison of more than two diagnostic or screening tests for prediction of presence vs. absence of a disease or condition can be complicated when attempting to simultaneously optimize a pair of competing criteria such as sensitivity and specificity. A technique for quantifying relative superiority of a diagnostic test when a gold standard exists in this setting is described. The proposed {\it superiority index} is used to quantify and rank performance of diagnostic tests and combinations of tests. Development of a validated model containing a subset of the tests may be improved by eliminating tests having a very small value for this index. To illustrate, we present an example using a large battery of neuropsychological tests for prediction of cognitive impairment. Using the proposed index, the battery is reduced with favorable results.

  • 关键词:Diagnostic Tests;Screening Tests;Neuropsychological Tests;Cognitive Impairment
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