ArticleDiagnostics (Basel, Switzerland)2020
Multivariate Analysis of Structural and Functional Neuroimaging Can Inform Psychiatric Differential Diagnosis.
Article in Diagnostics (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Examining early structural and functional brain alterations in postpartum depression through multimodal neuroimaging.Scientific reports · 2021Trial
- Association between Cortical Gyrification and Major Depression: Clinical Correlates.Psychopathology · 2026Article
- 7-Tesla ultra-high field MRI of the parahippocampal cortex reveals evidence of common neurobiological mechanisms of major depressive disorder and neurotic personality traits.Translational psychiatry · 2025Article
- Scientific psychiatry within technical reach.World journal of psychiatry · 2025Article
- Functional magnetic resonance imaging study of group independent components underpinning item responses to paranoid-depressive scale.World journal of clinical cases · 2023Article
- Application of Mass Multivariate Analysis on Neuroimaging Data Sets for Precision Diagnostics of Depression.Diagnostics (Basel, Switzerland) · 2022Article
- Perspectives before incremental trans-disciplinary cross-validation of clinical self-evaluation tools and functional MRI in psychiatry: 10 years later.Frontiers in psychiatry · 2022Article
- Pharmaco-Magnetic Resonance as a Tool for Monitoring the Medication-Related Effects in the Brain May Provide Potential Biomarkers for Psychotic Disorders.International journal of molecular sciences · 2021Review
- Implications from translational cross-validation of clinical assessment tools for diagnosis and treatment in psychiatry.World journal of psychiatry · 2021Review
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Authors and funding
7 authors.
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Abstract
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.
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