Conference proceeding
ROC analysis: comparison between the binormal and the Neyman-Pearson model
Conference Record of The Thirtieth Asilomar Conference on Signals, Systems and Computers, v 2, pp 1208-1212 vol.2
1996
Abstract
ROC analysis, a technique widely used to evaluate performance of human observers and medical diagnostic equipment is based on a binormal model, which leads to unrealistic results under many conditions. This paper develops a binormal Neyman-Pearson (BNP) formulation for ROC curves. Comparison shows significant superiority of the BNP model: the results are more accurate, more reliable and applicable to various relationships among the populations' parameters. The formulation is well suited to the statistical estimation of ROC parameters from categorical data from computer and human observer studies.
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Details
- Title
- ROC analysis: comparison between the binormal and the Neyman-Pearson model
- Creators
- T Karayianni - Drexel UniversityO.J TretiakN Herrmann
- Publication Details
- Conference Record of The Thirtieth Asilomar Conference on Signals, Systems and Computers, v 2, pp 1208-1212 vol.2
- Publisher
- IEEE
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- [Retired Faculty]
- Web of Science ID
- WOS:A1997BH95W00240
- Other Identifier
- 991019168113204721
InCites Highlights
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- Web of Science research areas
- Computer Science, Hardware & Architecture
- Computer Science, Information Systems
- Engineering, Electrical & Electronic