Classification Accuracy of Neuroimaging Biomarkers in Attention-Deficit/Hyperactivity Disorder: Effects of Sample Size and Circular Analysis.

ABSTRACT:

Background

Motivated by an inconsistency between reports of high diagnosis-classification accuracies and known heterogeneity in attention-deficit/hyperactivity disorder (ADHD), this study assessed classification accuracy in studies of ADHD as a function of methodological factors that can bias results. We hypothesized that high classification results in ADHD diagnosis are inflated by methodological factors.

Methods

We reviewed 69 studies (of 95 studies identified) that used neuroimaging features to predict ADHD diagnosis. Based on reported methods, we assessed the prevalence of circular analysis, which inflates classification accuracy, and evaluated the relationship between sample size and accuracy to test if small-sample models tend to report higher classification accuracy,

SUBMITTER: Pulini AA 

PROVIDER: S-EPMC6310118 | biostudies-literature | 2019 Feb

REPOSITORIES: biostudies-literature