Cross-Validation of Functional MRI and Paranoid-Depressive Scale: Results From Multivariate Analysis.

Détails

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Etat: Public
Version: Final published version
Licence: CC BY 4.0
ID Serval
serval:BIB_DD1EF021542D
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Institution
Titre
Cross-Validation of Functional MRI and Paranoid-Depressive Scale: Results From Multivariate Analysis.
Périodique
Frontiers in psychiatry
Auteur(s)
Stoyanov D., Kandilarova S., Paunova R., Barranco Garcia J., Latypova A., Kherif F.
ISSN
1664-0640 (Print)
ISSN-L
1664-0640
Statut éditorial
Publié
Date de publication
2019
Peer-reviewed
Oui
Volume
10
Pages
869
Langue
anglais
Notes
Publication types: Journal Article
Publication Status: epublish
Résumé
Introduction: There exists over the past decades a constant debate driven by controversies in the validity of psychiatric diagnosis. This debate is grounded in queries about both the validity and evidence strength of clinical measures. Materials and Methods: The objective of the study is to construct a bottom-up unsupervised machine learning approach, where the brain signatures identified by three principal components based on activations yielded from the three kinds of diagnostically relevant stimuli are used in order to produce cross-validation markers which may effectively predict the variance on the level of clinical populations and eventually delineate diagnostic and classification groups. The stimuli represent items from a paranoid-depressive self-evaluation scale, administered simultaneously with functional magnetic resonance imaging (fMRI). Results: We have been able to separate the two investigated clinical entities - schizophrenia and recurrent depression by use of multivariate linear model and principal component analysis. Following the individual and group MLM, we identified the three brain patterns that summarized all the individual variabilities of the individual brain patterns. Discussion: This is a confirmation of the possibility to achieve bottom-up classification of mental disorders, by use of the brain signatures relevant to clinical evaluation tests.
Mots-clé
classification, functional MRI, machine learning, psychopathology, validation
Pubmed
Web of science
Open Access
Oui
Création de la notice
15/12/2019 16:57
Dernière modification de la notice
30/04/2021 6:15
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