[HTML][HTML] Gray matter volume drives the brain age gap in schizophrenia: a SHAP study
Neuroimaging-based brain age is a biomarker that is generated by machine learning (ML)
predictions. The brain age gap (BAG) is typically defined as the difference between the …
predictions. The brain age gap (BAG) is typically defined as the difference between the …
[HTML][HTML] Predicting aging trajectories of decline in brain volume, cortical thickness and fractional anisotropy in schizophrenia
Brain-age prediction is a novel approach to assessing deviated brain aging trajectories in
different diseases. However, most studies have used an average brain age gap (BAG) of …
different diseases. However, most studies have used an average brain age gap (BAG) of …
Brain age prediction in schizophrenia: Does the choice of machine learning algorithm matter?
Brain-predicted age difference (brainPAD) has been used in schizophrenia to assess
individual-level deviation in the biological age of the patients' brain (ie, brain-age) from …
individual-level deviation in the biological age of the patients' brain (ie, brain-age) from …
Brain age gap as a potential biomarker for schizophrenia: a multi-site structural MRI study
W Man, H Ding, C Chai, X An, F Liu… - 2021 43rd Annual …, 2021 - ieeexplore.ieee.org
Gray matter atrophy in schizophrenia has been widely recognized; however, it remains
controversial whether it reflects a neurodegenerative condition. Recent studies have …
controversial whether it reflects a neurodegenerative condition. Recent studies have …
[HTML][HTML] Investigating brain aging trajectory deviations in different brain regions of individuals with schizophrenia using multimodal magnetic resonance imaging and …
Although many studies on brain-age prediction in patients with schizophrenia have been
reported recently, none has predicted brain age based on different neuroimaging modalities …
reported recently, none has predicted brain age based on different neuroimaging modalities …
[HTML][HTML] Advanced brain-age in psychotic psychopathology: evidence for transdiagnostic neurodevelopmental origins
Schizophrenia is characterized by abnormal brain structure such as global reductions in
gray matter volume. Machine learning models trained to estimate the age of brains from …
gray matter volume. Machine learning models trained to estimate the age of brains from …
[HTML][HTML] The impact of schizophrenia and intelligence on the relationship between age and brain volume
Age has been shown to have an impact on both grey (GM) and white matter (WM) volume,
with a steeper slope of age-related decline in schizophrenia compared to healthy controls. In …
with a steeper slope of age-related decline in schizophrenia compared to healthy controls. In …
[HTML][HTML] Detection of advanced brain aging in schizophrenia and its structural underpinning by using normative brain age metrics
Conceptualizing mental disorders as deviations from normative functioning provides a
statistical perspective for understanding the individual heterogeneity underlying psychiatric …
statistical perspective for understanding the individual heterogeneity underlying psychiatric …
Neuroimaging-based brain-age prediction of first-episode schizophrenia and the alteration of brain age after early medication
YB Xi, XS Wu, LB Cui, LJ Bai, SQ Gan… - The British Journal of …, 2022 - cambridge.org
Background Neuroimaging-and machine-learning-based brain-age prediction of
schizophrenia is well established. However, the diagnostic significance and the effect of …
schizophrenia is well established. However, the diagnostic significance and the effect of …
[HTML][HTML] Accelerated global and local brain aging differentiate cognitively impaired from cognitively spared patients with schizophrenia
Background Accelerated aging has been proposed as a mechanism underlying the clinical
and cognitive presentation of schizophrenia. The current study extends the field by …
and cognitive presentation of schizophrenia. The current study extends the field by …