Hugo G Schnack
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Explore the profile of Hugo G Schnack including associated specialties, affiliations and a list of published articles.
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108
Citations
4787
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Recent Articles
1.
van Dee V, Swildens W, Schnack H, Cahn W
Community Ment Health J
. 2024 Dec;
61(2):300-313.
PMID: 39656388
There is no consensus on the definition of recovery of people with psychosis. This may be attributed to the broad concept including clinical, functional and personal recovery domains and the...
2.
van Opstal D, Kia S, Jakob L, Somers M, Sommer I, Rossum I, et al.
Acta Psychiatr Scand
. 2024 Sep;
151(3):280-292.
PMID: 39293941
Introduction: Machine learning models have shown promising potential in individual-level outcome prediction for patients with psychosis, but also have several limitations. To address some of these limitations, we present a...
3.
Poortman S, Setiaman N, Barendse M, Schnack H, Hillegers M, van Haren N
Eur Neuropsychopharmacol
. 2024 Jul;
87:56-66.
PMID: 39084058
Offspring of parents with severe mental illness (e.g., bipolar disorder or schizophrenia) are at increased risk of developing psychopathology. Structural brain alterations have been found in child and adolescent offspring...
4.
Janssen J, Gallego A, Diaz-Caneja C, Lois N, Janssen N, Gonzalez-Penas J, et al.
bioRxiv
. 2024 Jul;
PMID: 38948832
Introduction: Morphometric similarity is a recently developed neuroimaging phenotype of inter-regional connectivity by quantifying the similarity of a region to other regions based on multiple MRI parameters. Altered average morphometric...
5.
Wen J, Nasrallah I, Abdulkadir A, Satterthwaite T, Yang Z, Erus G, et al.
Proc Natl Acad Sci U S A
. 2023 Dec;
120(52):e2300842120.
PMID: 38127979
Normal and pathologic neurobiological processes influence brain morphology in coordinated ways that give rise to patterns of structural covariance (PSC) across brain regions and individuals during brain aging and diseases....
6.
van Dee V, Kia S, Rossum I, Kahn R, Cahn W, Schnack H
Front Psychiatry
. 2023 Oct;
14:1237490.
PMID: 37900290
Introduction: Psychiatric comorbidities have a significant impact on the course of illness in patients with schizophrenia spectrum disorders. To accurately predict outcomes for individual patients using computerized prognostic models, it...
7.
Dwyer D, Chand G, Pigoni A, Khuntia A, Wen J, Antoniades M, et al.
Mol Psychiatry
. 2023 May;
28(5):2008-2017.
PMID: 37147389
Using machine learning, we recently decomposed the neuroanatomical heterogeneity of established schizophrenia to discover two volumetric subgroups-a 'lower brain volume' subgroup (SG1) and an 'higher striatal volume' subgroup (SG2) with...
8.
Hwang G, Wen J, Sotardi S, Brodkin E, Chand G, Dwyer D, et al.
JAMA Psychiatry
. 2023 Apr;
80(5):498-507.
PMID: 37017948
Importance: Autism spectrum disorder (ASD) is associated with significant clinical, neuroanatomical, and genetic heterogeneity that limits precision diagnostics and treatment. Objective: To assess distinct neuroanatomical dimensions of ASD using novel...
9.
van Dee V, Schnack H, Cahn W
Schizophr Res
. 2023 Mar;
254:133-142.
PMID: 36863229
Background: Schizophrenia spectrum disorders (SSD) have heterogeneous outcomes. If we could predict individual outcome and identify predictors of outcome, we could personalize and optimize treatment and care. Recent research showed...
10.
Voppel A, de Boer J, Brederoo S, Schnack H, Sommer I
Schizophr Bull
. 2022 Oct;
49(Suppl_2):S163-S171.
PMID: 36305054
Background And Hypothesis: Speech is a promising marker to aid diagnosis of schizophrenia-spectrum disorders, as it reflects symptoms like thought disorder and negative symptoms. Previous approaches made use of different...