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Published on: May 10, 2019
Validation of Monte Carlo estimates of three-class ideal observer operating points for normal data
1The Department of Physiology, 303 E Superior St., Northwestern University, Chicago, IL 60611, USA. darrin.c.edwards@gmail.com
Rationale And Objectives:
Traditional two-class receiver operating characteristic (ROC) analysis is inadequate for the complete evaluation of observer performance in tasks with more than two classes.
Materials And Methods:
Here, a Monte Carlo estimation method for operating point coordinates on a three-class ROC surface is developed and compared with analytically calculated coordinates in two special cases: (1) univariate and (2) restricted bivariate trinormal underlying data.
Results:
In both cases, the statistical estimates were found to be good in the sense that the analytical values lay within the 95% confidence interval of the estimated values about 95% of the time.
Conclusions:
The statistical estimation method should be key in the development of a pragmatic performance metric for evaluation of observers in classification tasks with three or more classes.
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