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Multivariate Pattern Classification of Primary Insomnia Using Three Types of Functional Connectivity Features

Objective: To explore whether or not functional connectivity (FC) could be used as a potential biomarker for classification of primary insomnia (PI) at the individual level by using multivariate pattern analysis (MVPA).Methods: Thirty-eight drug-naive patients with PI, and 44 healthy controls (HC) u...

Täydet tiedot

Tallennettuna:
Päätekijät: Chao Li, Yuanqi Mai, Mengshi Dong, Yi Yin, Kelei Hua, Shishun Fu, Yunfan Wu, Guihua Jiang
Aineistotyyppi: Artigo
Kieli:Inglês
Julkaistu: Frontiers Media S.A. 2019-10-01
Sarja:Frontiers in Neurology
Aiheet:
primary insomnia
insular cortex
frontal lobe
machine learning
support vector machine
Linkit:https://www.frontiersin.org/article/10.3389/fneur.2019.01037/full
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