Examination of the predictive value of structural magnetic resonance scans in bipolar disorder: a pattern classification approach.

ABSTRACT:

Background

Bipolar disorder (BD) is one of the leading causes of disability worldwide. Patients are further disadvantaged by delays in accurate diagnosis ranging between 5 and 10 years. We applied Gaussian process classifiers (GPCs) to structural magnetic resonance imaging (sMRI) data to evaluate the feasibility of using pattern recognition techniques for the diagnostic classification of patients with BD.

Method

GPCs were applied to gray (GM) and white matter (WM) sMRI data derived from two independent samples of patients with BD (cohort 1: n = 26; cohort 2: n = 14). Within each cohort patients were matched on age, sex and IQ to an equal number of healthy controls.

Results

The diagnostic accuracy of the GPC for GM was 73% in cohort 1 and 72% in cohort 2; the sensitivi

SUBMITTER: Rocha-Rego V 

PROVIDER: S-EPMC3880067 | biostudies-literature | 2014 Feb

REPOSITORIES: biostudies-literature