Differences Between Schizophrenic and Normal Subjects Using Network Properties from fMRI.
Schizophrenia has been proposed to result from impairment of functional connectivity. We aimed to use machine learning to distinguish schizophrenic subjects from normal controls using a publicly available functional MRI (fMRI) data set. Global and local parameters of functional connectivity were ext...
| Publicado en: | Journal of Digital Imaging Vol. 31; no. 2; pp. 252 - 262 |
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| Autores principales: | , , , , , |
| Formato: | diagnostic images equations & formulas research tables/charts Journal Article |
| Publicado: |
Springer Nature
Apr2018
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=128715848&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 128715848 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 08971889 DOQ jtl: Journal of Digital Imaging issn: 08971889 maglogo: N pubinfo: dt: Apr2018 vid: 31 iid: 2 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 128715848 128715848 128715848 10.1007/s10278-017-0020-4 128715848 ppf: 252 ppct: 10 formats: fmt: @attributes: type: P tig: atl: Differences Between Schizophrenic and Normal Subjects Using Network Properties from fMRI. aug: au: Youngoh Bae Kumarasamy, Kunaraj Ali, Issa M. Korfiatis, Panagiotis Akkus, Zeynettin Erickson, Bradley J. affil: School of Medicine, CHA University, Seongnam-si, Gyeonggi-do, South Korea sug: subj: Schizophrenia Diagnosis Magnetic Resonance Imaging Methods Neural Networks (Computer) Human Machine Learning Validity Cerebral Cortex Temporal Lobe Parietal Lobe ab: Schizophrenia has been proposed to result from impairment of functional connectivity. We aimed to use machine learning to distinguish schizophrenic subjects from normal controls using a publicly available functional MRI (fMRI) data set. Global and local parameters of functional connectivity were extracted for classification. We found decreased global and local network connectivity in subjects with schizophrenia, particularly in the anterior right cingulate cortex, the superior right temporal region, and the inferior left parietal region as compared to healthy subjects. Using support vector machine and 10-fold cross-validation, nine features reached 92.1% prediction accuracy, respectively. Our results suggest that there are significant differences between control and schizophrenic subjects based on regional brain activity detected with fMRI. pubtype: Academic Journal doctype: diagnostic images equations & formulas research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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