Machine learning in mental health: a scoping review of methods and applications
BackgroundThis paper aims to synthesise the literature on machine learning (ML) and big
data applications for mental health, highlighting current research and applications in …
data applications for mental health, highlighting current research and applications in …
[HTML][HTML] Classification and prediction of brain disorders using functional connectivity: promising but challenging
Brain functional imaging data, especially functional magnetic resonance imaging (fMRI)
data, have been employed to reflect functional integration of the brain. Alteration in brain …
data, have been employed to reflect functional integration of the brain. Alteration in brain …
[HTML][HTML] Methodological and quality flaws in the use of artificial intelligence in mental health research: systematic review
R Tornero-Costa, A Martinez-Millana… - JMIR Mental …, 2023 - mental.jmir.org
Background: Artificial intelligence (AI) is giving rise to a revolution in medicine and health
care. Mental health conditions are highly prevalent in many countries, and the COVID-19 …
care. Mental health conditions are highly prevalent in many countries, and the COVID-19 …
[HTML][HTML] Multi-site diagnostic classification of schizophrenia using discriminant deep learning with functional connectivity MRI
Background A lack of a sufficiently large sample at single sites causes poor generalizability
in automatic diagnosis classification of heterogeneous psychiatric disorders such as …
in automatic diagnosis classification of heterogeneous psychiatric disorders such as …
Machine learning studies on major brain diseases: 5-year trends of 2014–2018
K Sakai, K Yamada - Japanese journal of radiology, 2019 - Springer
Abstract In the recent 5 years (2014–2018), there has been growing interest in the use of
machine learning (ML) techniques to explore image diagnosis and prognosis of therapeutic …
machine learning (ML) techniques to explore image diagnosis and prognosis of therapeutic …
Transdiagnostic dysfunctions in brain modules across patients with schizophrenia, bipolar disorder, and major depressive disorder: a connectome-based study
Psychiatric disorders, including schizophrenia (SCZ), bipolar disorder (BD), and major
depressive disorder (MDD), share clinical and neurobiological features. Because previous …
depressive disorder (MDD), share clinical and neurobiological features. Because previous …
An attention-based hybrid deep learning framework integrating brain connectivity and activity of resting-state functional MRI data
Functional magnetic resonance imaging (fMRI) as a promising tool to investigate psychotic
disorders can be decomposed into useful imaging features such as time courses (TCs) of …
disorders can be decomposed into useful imaging features such as time courses (TCs) of …
[HTML][HTML] Group ICA for identifying biomarkers in schizophrenia:'Adaptive'networks via spatially constrained ICA show more sensitivity to group differences than spatio …
Brain functional networks identified from fMRI data can provide potential biomarkers for
brain disorders. Group independent component analysis (GICA) is popular for extracting …
brain disorders. Group independent component analysis (GICA) is popular for extracting …
[HTML][HTML] Aberrant dynamic functional connectivity of default mode network in schizophrenia and links to symptom severity
Background: Schizophrenia affects around 1% of the global population. Functional
connectivity extracted from resting-state functional magnetic resonance imaging (rs-fMRI) …
connectivity extracted from resting-state functional magnetic resonance imaging (rs-fMRI) …
Detecting schizophrenia at the level of the individual: relative diagnostic value of whole-brain images, connectome-wide functional connectivity and graph-based …
BackgroundPrevious studies using resting-state functional neuroimaging have revealed
alterations in whole-brain images, connectome-wide functional connectivity and graph …
alterations in whole-brain images, connectome-wide functional connectivity and graph …