In the study, a supervised learning framework is focused to identify the bipolar disorder (BD) using structural magnetic resonance imaging is focused. The work is based on the newly developed 3D SIFT and 3D SURF feature vectors with pattern recognition technique. The overall hypothesis is to deduct BD results from dysfunctional cellular metabolism within specific brain systems (i.e., anterior limbic brain network) as reflected in abnormalities in brain activation patterns and in specific neurochemical measures. The proposed method is used to integrate neuroimaging in exploring the biomarkers of BD to reveal the mechanism. In the method, two newly developed feature vectors and kernel PCA are combined or connected to project the feature vectors. Diagnosis process is done by random forest. The results reveal that the method has high potential to identify the BD than earlier works, and an average accuracy of 77.77% is reached. This research reveals that neuroimaging studies will help to differentiate BD from healthy controls.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2025 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.