Identifying neuropsychiatric disorders using unsupervised clustering methods: Data and code.

ABSTRACT: This article provides data for five different neuropsychiatric disorders-Attention Deficit Hyperactivity Disorder, Alzheimer's Disease, Autism Spectrum Disorder, Post-Traumatic Stress Disorder, and Post-Concussion Syndrome-along with healthy controls. The data includes clinical diagnostic labels, phenotypic variables, and resting-state functional magnetic resonance imaging connectivity features obtained from individuals. In addition, it provides the source MATLAB codes used for data analyses. Three existing clustering methods have been incorporated into the provided code, which do not require a priori specification of the number of clusters. A genetic algorithm based feature selection method has also been included to find the relevant subset of features and clustering the subset of

SUBMITTER: Zhao X 

PROVIDER: S-EPMC6321965 | biostudies-literature | 2019 Feb

REPOSITORIES: biostudies-literature