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The Receiver Operational Characteristic for Binary Classification with Multiple Indices and Its Application to the Neuroimaging Study of Alzheimer's Disease
Found in: IEEE/ACM Transactions on Computational Biology and Bioinformatics
By Xia Wu, Juan Li,Napatkamon Ayutyanont,Hillary Protas,William Jagust,Adam Fleisher,Eric Reiman, Li Yao, Kewei Chen
Issue Date:January 2013
pp. 173-180
Given a single index, the receiver operational characteristic (ROC) curve analysis is routinely utilized for characterizing performances in distinguishing two conditions/groups in terms of sensitivity and specificity. Given the availability of multiple dat...
 
Linear and Non-linear Geometric Object Matching with Implicit Representation
Found in: Pattern Recognition, International Conference on
By Alex Leow, Ming-Chang Chiang, Hillary Protas, Paul Thompson, Luminita Vese, Henry S. C. Huang
Issue Date:August 2004
pp. 710-713
This paper deals with the matching of geometric objects including points, curves, surfaces, and subvolumes using implicit object representations in both linear and non-linear settings. This framework can be applied to feature-based non-linear image warping...
 
The Receiver Operational Characteristic for Binary Classification with Multiple Indices and Its Application to the Neuroimaging Study of Alzheimer's Disease
Found in: IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
By Adam Fleisher, Eric Reiman, Hillary Protas, Juan Li, Kewei Chen, Li Yao, Napatkamon Ayutyanont, William Jagust, Xia Wu
Issue Date:January 2013
pp. 173-180
Given a single index, the receiver operational characteristic (ROC) curve analysis is routinely utilized for characterizing performances in distinguishing two conditions/groups in terms of sensitivity and specificity. Given the availability of multiple dat...
     
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