Publication Type

Conference Proceeding Article

Version

publishedVersion

Publication Date

7-2012

Abstract

Brain based diagnostic systems have recently received attention as a tool in the characterization and diagnosis of a variety of neurodevelopmental and psychiatric disorders. Nonetheless, a majority of disorders are still diagnosed entirely based on symptom assessments and behavioral correlates. We therefore propose a method for fusing brain responses with clinical measures for improved diagnosis. To this end, we utilized the flexibility of clustered random subspace brain mapping to detect regions where brain responses in conjunction with a clinical measure could reliably differentiate patients from control subjects. We demonstrate the approach on realistically simulated functional magnetic resonance imaging (fMRI) brain activity and a clinical parameter. We show that the method efficiently identifies brain regions where fused analysis of brain responses and clinical parameters improves diagnosis compared to either measure alone. The proposed method is easy to implement and highly flexible, offering an appealing basis for multimodal brain mapping.

Keywords

Accuracy, Brain modeling, Brain mapping, Autism, Computational modeling, Clustering algorithms

Discipline

Communication | Health Information Technology

Research Areas

Integrative Research Areas

Publication

2012 15th International Conference on Information Fusion, FUSION: Singapore, 9-12 July: Proceedings

First Page

593

Last Page

599

ISBN

9780982443859

Publisher

IEE

City or Country

Pistacataway, NJ

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