Artificial intelligence of things for smarter healthcare: A survey of advancements, challenges, and opportunities

S Baker, W Xiang - IEEE Communications Surveys & Tutorials, 2023 - ieeexplore.ieee.org
Healthcare systems are under increasing strain due to a myriad of factors, from a steadily
ageing global population to the current COVID-19 pandemic. In a world where we have …

A systematic review on the potential use of machine learning to classify major depressive disorder from healthy controls using resting state fMRI measures

E Bondi, E Maggioni, P Brambilla… - … & Biobehavioral Reviews, 2023 - Elsevier
Abstract Background Major Depressive Disorder (MDD) is a psychiatric disorder
characterized by functional brain deficits, as documented by resting-state functional …

Disrupted intrinsic functional brain topology in patients with major depressive disorder

H Yang, X Chen, ZB Chen, L Li, XY Li… - Molecular …, 2021 - nature.com
Aberrant topological organization of whole-brain networks has been inconsistently reported
in studies of patients with major depressive disorder (MDD), reflecting limited sample sizes …

Robust dynamic brain coactivation states estimated in individuals

X Peng, Q Liu, CS Hubbard, D Wang, W Zhu… - Science …, 2023 - science.org
A confluence of evidence indicates that brain functional connectivity is not static but rather
dynamic. Capturing transient network interactions in the individual brain requires a …

Cognitive behavioural therapy as an adjunct to pharmacotherapy for primary care based patients with treatment resistant depression: results of the CoBalT …

N Wiles, L Thomas, A Abel, N Ridgway, N Turner… - The Lancet, 2013 - thelancet.com
Background Only a third of patients with depression respond fully to antidepressant
medication but little evidence exists regarding the best next-step treatment for those whose …

Altered brain dynamic in major depressive disorder: state and trait features

N Javaheripour, L Colic, N Opel, M Li… - Translational …, 2023 - nature.com
Temporal neural synchrony disruption can be linked to a variety of symptoms of major
depressive disorder (MDD), including mood rigidity and the inability to break the cycle of …

An insight into diagnosis of depression using machine learning techniques: a systematic review

S Bhadra, CJ Kumar - Current medical research and opinion, 2022 - Taylor & Francis
Background In this modern era, depression is one of the most prevalent mental disorders
from which millions of individuals are affected today. The symptoms of depression are …

Evaluation of risk of bias in neuroimaging-based artificial intelligence models for psychiatric diagnosis: a systematic review

Z Chen, X Liu, Q Yang, YJ Wang, K Miao… - JAMA network …, 2023 - jamanetwork.com
Importance Neuroimaging-based artificial intelligence (AI) diagnostic models have
proliferated in psychiatry. However, their clinical applicability and reporting quality (ie …

Sampling inequalities affect generalization of neuroimaging-based diagnostic classifiers in psychiatry

Z Chen, B Hu, X Liu, B Becker, SB Eickhoff, K Miao… - BMC medicine, 2023 - Springer
Background The development of machine learning models for aiding in the diagnosis of
mental disorder is recognized as a significant breakthrough in the field of psychiatry …

MAMF-GCN: Multi-scale adaptive multi-channel fusion deep graph convolutional network for predicting mental disorder

J Pan, H Lin, Y Dong, Y Wang, Y Ji - Computers in biology and medicine, 2022 - Elsevier
Purpose Existing diagnoses of mental disorders rely on symptoms, patient descriptions, and
scales, which are not objective enough. We attempt to explore an objective diagnostic …