Multivariate Analysis of Structural and Functional Neuroimaging Can Inform Psychiatric Differential Diagnosis.

Détails

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Etat: Public
Version: Final published version
Licence: CC BY 4.0
ID Serval
serval:BIB_19EF63676FE0
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Institution
Titre
Multivariate Analysis of Structural and Functional Neuroimaging Can Inform Psychiatric Differential Diagnosis.
Périodique
Diagnostics
Auteur⸱e⸱s
Stoyanov D., Kandilarova S., Aryutova K., Paunova R., Todeva-Radneva A., Latypova A., Kherif F.
ISSN
2075-4418 (Print)
ISSN-L
2075-4418
Statut éditorial
Publié
Date de publication
24/12/2020
Peer-reviewed
Oui
Volume
11
Numéro
1
Pages
E19
Langue
anglais
Notes
Publication types: Journal Article
Publication Status: epublish
Résumé
Traditional psychiatric diagnosis has been overly reliant on either self-reported measures (introspection) or clinical rating scales (interviews). This produced the so-called explanatory gap with the bio-medical disciplines, such as neuroscience, which are supposed to deliver biological explanations of disease. In that context the neuro-biological and clinical assessment in psychiatry remained discrepant and incommensurable under conventional statistical frameworks. The emerging field of translational neuroimaging attempted to bridge the explanatory gap by means of simultaneous application of clinical assessment tools and functional magnetic resonance imaging, which also turned out to be problematic when analyzed with standard statistical methods. In order to overcome this problem our group designed a novel machine learning technique, multivariate linear method (MLM) which can capture convergent data from voxel-based morphometry, functional resting state and task-related neuroimaging and the relevant clinical measures. In this paper we report results from convergent cross-validation of biological signatures of disease in a sample of patients with schizophrenia as compared to depression. Our model provides evidence that the combination of the neuroimaging and clinical data in MLM analysis can inform the differential diagnosis in terms of incremental validity.
Mots-clé
depression, diagnosis, discriminative, multivariate linear method, schizophrenia, signatures of disease, validation
Pubmed
Web of science
Open Access
Oui
Création de la notice
11/01/2021 10:21
Dernière modification de la notice
21/11/2022 9:14
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