An overview of artificial intelligence techniques for diagnosis of Schizophrenia based on magnetic resonance imaging modalities: Methods, challenges, and future …

D Sadeghi, A Shoeibi, N Ghassemi, P Moridian… - Computers in Biology …, 2022 - Elsevier
Schizophrenia (SZ) is a mental disorder that typically emerges in late adolescence or early
adulthood. It reduces the life expectancy of patients by 15 years. Abnormal behavior …

Artificial intelligence for brain diseases: A systematic review

A Segato, A Marzullo, F Calimeri, E De Momi - APL bioengineering, 2020 - pubs.aip.org
Artificial intelligence (AI) is a major branch of computer science that is fruitfully used for
analyzing complex medical data and extracting meaningful relationships in datasets, for …

Evidence for embracing normative modeling

S Rutherford, P Barkema, IF Tso, C Sripada… - Elife, 2023 - elifesciences.org
In this work, we expand the normative model repository introduced in Rutherford et al.,
2022a to include normative models charting lifespan trajectories of structural surface area …

Statistical power in network neuroscience

K Helwegen, I Libedinsky… - Trends in Cognitive …, 2023 - cell.com
Network neuroscience has emerged as a leading method to study brain connectivity. The
success of these investigations is dependent not only on approaches to accurately map …

[HTML][HTML] Going deep into schizophrenia with artificial intelligence

JA Cortes-Briones, NI Tapia-Rivas, DC D'Souza… - Schizophrenia …, 2022 - Elsevier
Despite years of research, the mechanisms governing the onset, relapse, symptomatology,
and treatment of schizophrenia (SZ) remain elusive. The lack of appropriate analytic tools to …

Neuroimaging in schizophrenia

MS Keshavan, G Collin, S Guimond… - Neuroimaging …, 2020 - neuroimaging.theclinics.com
Psychotic disorders are mental illnesses characterized by difficulties in reality testing. 1
Schizophrenia is a severe and chronic psychotic disorder with a lifetime prevalence of about …

Graph convolutional networks reveal network-level functional dysconnectivity in schizophrenia

D Lei, K Qin, WHL Pinaya, J Young… - Schizophrenia …, 2022 - academic.oup.com
Abstract Background and Hypothesis Schizophrenia is increasingly understood as a
disorder of brain dysconnectivity. Recently, graph-based approaches such as graph …

[HTML][HTML] Deep learning applications for the classification of psychiatric disorders using neuroimaging data: systematic review and meta-analysis

M Quaak, L van de Mortel, RM Thomas… - NeuroImage: Clinical, 2021 - Elsevier
Deep learning (DL) methods have been increasingly applied to neuroimaging data to
identify patients with psychiatric and neurological disorders. This review provides an …

Deep multimodal predictome for studying mental disorders

MA Rahaman, J Chen, Z Fu, N Lewis… - Human brain …, 2023 - Wiley Online Library
Characterizing neuropsychiatric disorders is challenging due to heterogeneity in the
population. We propose combining structural and functional neuroimaging and genomic …

Towards artificial intelligence in mental health: a comprehensive survey on the detection of schizophrenia

A Tyagi, VP Singh, MM Gore - Multimedia Tools and Applications, 2023 - Springer
Abstract Computer Aided Diagnosis systems assist radiologists and doctors in the early
diagnosis of mental disorders such as Alzheimer's, bipolar disorder, depression, autism …