A method of comparing the areas under receiver operating characteristic curves derived from the same cases.
Dados Bibliográficos
| ID | 23339090 |
|---|---|
| Autores | J A Hanley, Barbara J Mcneil |
| Ano | 1983 |
| Volume | 148 |
| Fascículo | 3 |
| Páginas | 839-843 |
| Data de publicação | 1983-09-01 |
| Peer Reviewed | Sim |
| Open Access | Não |
| Tipo | ARTICLE |
| Periódico | Radiology (JOURNAL) |
| Identificadores do periódico | ISSN: 0033-8419 • E-ISSN: 1527-1315 |
| Editora | Radiological Society of North America (RSNA) (PUBLISHER) |
| DOI | 10.1148/radiology.148.3.6878708 |
| PMID | 6878708 |
| OpenAlex | W2102150307 |
| Idioma | EN |
| Citações recebidas | 98 |
| Referências citadas | 3 |
Receiver operating characteristic (ROC) curves are used to describe and compare the performance of diagnostic technology and diagnostic algorithms. This paper refines the statistical comparison of the areas under two ROC curves derived from the same set of patients by taking into account the correlation between the areas that is induced by the paired nature of the data. The correspondence between the area under an ROC curve and the Wilcoxon statistic is used and underlying Gaussian distributions (binormal) are assumed to provide a table that converts the observed correlations in paired ratings of images into a correlation between the two ROC areas. This between-area correlation can be used to reduce the standard error (uncertainty) about the observed difference in areas. This correction for pairing, analogous to that used in the paired t-test, can produce a considerable increase in the statistical sensitivity (power) of the comparison. For studies involving multiple readers, this method provides a measure of a component of the sampling variation that is otherwise difficult to obtain.
Correlation · Correlation coefficient · Gaussian · Pattern recognition (psychology) · Receiver operating characteristic · Sampling (signal processing) · Sensitivity (control systems) · Statistic · Statistical power · Statistics · Wilcoxon signed-rank test · AI in cancer detection · Artificial Intelligence · Artificial Intelligence in Healthcare · Computer Science · Digital Imaging for Blood Diseases · Mathematics · Medicine
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| Obras citantes distintas | 98 |
|---|---|
| Citações por ano | 2,65 |
| Intervalo de citações | 1989 - 2025 (37) |
| Velocidade de citação | recent |
| Altamente citado | Não |
| Tipos de citação | Neutras: 89 |