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What Would It Take for Electrophysiology to Become Clinically Useful?

Published online by Cambridge University Press:  07 November 2014

Eugene Somoza  and
Sunme Kim
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Abstract

In this article we discuss the procedures that should be followed in order to develop diagnostic tests based on electro-physiologic parameters that would be useful to practicing psychiatrists in their efforts to diagnose mental disorders. To do this, we start by giving an overview of receiver operating characteristic (ROC) analysis, with which a candidate diagnostic test can be characterized mathematically. This methodology allows for an estimate of the overall discriminating power of the diagnostic test and thus can be used to compare the performance of one diagnostic test with that of another. However, ROC analysis cannot be used for optimizing a given diagnostic test (ie, determining the “best” cut-off) and, because it does not incorporate Bayes' theorem, it cannot be used to compare the performances of diagnostic tests when it is given to different risk groups for the target disorder. Both of these problems can be solved by using the concept of information theory. The equation for information gain automatically takes Bayes' theorem into consideration and also provides an intrinsic criterion for finding the cutoff that best discriminates between individuals who do and those who do not have the target disorder. Neither ROC analysis nor information theory are model dependent; however, if the equation for the frequency distribution of the electrophysiologic variable is known for the disease-positive and disease-negative populations, the calculations are greatly simplified. Therefore, the assumption is often made that both of these distributions (or transformations of the distributions) are Gaussian. However, studies have shown that the results of ROC analysis are quite robust to deviations from normality of the underlying distributions.

Type
Feature Articles
Information
CNS Spectrums , Volume 4 , Issue 8: Neurologic Electrophysiology: Closing in on a Moving Picture of the Brain , August 1999 , pp. 58 - 64,80
Copyright
Copyright © Cambridge University Press 1999

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