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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Connectivity of the anterior insula differentiates participants with first-episode schizophrenia spectrum disorders from controls: a machine-learning study
Pavol Mikoláš, Tomáš Melicher, Antonín Škoch, et al.
Psychological Medicine (2016) Vol. 46, Iss. 13, pp. 2695-2704
Closed Access | Times Cited: 59

Showing 1-25 of 59 citing articles:

Machine learning in mental health: a scoping review of methods and applications
Adrian Shatte, Delyse Hutchinson, Samantha Teague
Psychological Medicine (2019) Vol. 49, Iss. 09, pp. 1426-1448
Open Access | Times Cited: 684
Cortico-Striatal-Thalamic Loop Circuits of the Salience Network: A Central Pathway in Psychiatric Disease and Treatment
Sarah K. Peters, Katharine Dunlop, Jonathan Downar
Frontiers in Systems Neuroscience (2016) Vol. 10
Open Access | Times Cited: 535
Deep Learning in Radiology
Morgan P. McBee, Omer A. Awan, Andrew Colucci, et al.
Academic Radiology (2018) Vol. 25, Iss. 11, pp. 1472-1480
Open Access | Times Cited: 408
Classification and Prediction of Brain Disorders Using Functional Connectivity: Promising but Challenging
Yuhui Du, Zening Fu, Vince D. Calhoun
Frontiers in Neuroscience (2018) Vol. 12
Open Access | Times Cited: 304
Multi-Site Diagnostic Classification of Schizophrenia Using Discriminant Deep Learning with Functional Connectivity MRI
Ling‐Li Zeng, Huaning Wang, Panpan Hu, et al.
EBioMedicine (2018) Vol. 30, pp. 74-85
Open Access | Times Cited: 241
Towards a brain‐based predictome of mental illness
Barnaly Rashid, Vince D. Calhoun
Human Brain Mapping (2020) Vol. 41, Iss. 12, pp. 3468-3535
Open Access | Times Cited: 149
Towards artificial intelligence in mental health by improving schizophrenia prediction with multiple brain parcellation ensemble-learning
Sunil V. Kalmady, Russell Greiner, Rimjhim Agrawal, et al.
Schizophrenia (2019) Vol. 5, Iss. 1
Open Access | Times Cited: 105
Classifying heterogeneous presentations of PTSD via the default mode, central executive, and salience networks with machine learning
Andrew A. Nicholson, Sherain Harricharan, Maria Densmore, et al.
NeuroImage Clinical (2020) Vol. 27, pp. 102262-102262
Open Access | Times Cited: 77
Updating and characterizing neuroanatomical markers in high-risk subjects, recently diagnosed and chronic patients with schizophrenia: A revised coordinate-based meta-analysis
Donato Liloia, Claudio Brasso, Franco Cauda, et al.
Neuroscience & Biobehavioral Reviews (2021) Vol. 123, pp. 83-103
Open Access | Times Cited: 59
Support vector machine-based classification of first episode drug-naïve schizophrenia patients and healthy controls using structural MRI
Yuan Xiao, Zhihan Yan, Youjin Zhao, et al.
Schizophrenia Research (2017) Vol. 214, pp. 11-17
Closed Access | Times Cited: 73
Disease Definition for Schizophrenia by Functional Connectivity Using Radiomics Strategy
Long‐Biao Cui, Lin Liu, Huaning Wang, et al.
Schizophrenia Bulletin (2018) Vol. 44, Iss. 5, pp. 1053-1059
Open Access | Times Cited: 67
Machine learning multivariate pattern analysis predicts classification of posttraumatic stress disorder and its dissociative subtype: a multimodal neuroimaging approach
Andrew A. Nicholson, Maria Densmore, Margaret C. McKinnon, et al.
Psychological Medicine (2018) Vol. 49, Iss. 12, pp. 2049-2059
Closed Access | Times Cited: 66
Insula functional connectivity in schizophrenia
Julia M. Sheffield, Baxter P. Rogers, Jennifer Urbano Blackford, et al.
Schizophrenia Research (2020) Vol. 220, pp. 69-77
Open Access | Times Cited: 52
Mapping relationships among schizophrenia, bipolar and schizoaffective disorders: A deep classification and clustering framework using fMRI time series
Weizheng Yan, Min Zhao, Zening Fu, et al.
Schizophrenia Research (2021) Vol. 245, pp. 141-150
Open Access | Times Cited: 42
Evaluation of Risk of Bias in Neuroimaging-Based Artificial Intelligence Models for Psychiatric Diagnosis
Zhiyi Chen, Xuerong Liu, Qingwu Yang, et al.
JAMA Network Open (2023) Vol. 6, Iss. 3, pp. e231671-e231671
Open Access | Times Cited: 19
Sampling inequalities affect generalization of neuroimaging-based diagnostic classifiers in psychiatry
Zhiyi Chen, Bowen Hu, Xuerong Liu, et al.
BMC Medicine (2023) Vol. 21, Iss. 1
Open Access | Times Cited: 17
Machine learning classification of first-episode schizophrenia spectrum disorders and controls using whole brain white matter fractional anisotropy
Pavol Mikoláš, Jaroslav Hlinka, Antonín Škoch, et al.
BMC Psychiatry (2018) Vol. 18, Iss. 1
Open Access | Times Cited: 47
Aberrant resting-state functional connectivity of salience network in first-episode schizophrenia
Huan Huang, Botao Zeng, Yuchao Jiang, et al.
Brain Imaging and Behavior (2019) Vol. 14, Iss. 5, pp. 1350-1360
Closed Access | Times Cited: 44
Biomarkers for Prediction of Schizophrenia: Insights From Resting-State EEG Microstates
Yu Luo, Qing Tian, Changming Wang, et al.
IEEE Access (2020) Vol. 8, pp. 213078-213093
Open Access | Times Cited: 41
Schizophrenia: A Survey of Artificial Intelligence Techniques Applied to Detection and Classification
Joel Weijia Lai, Candice Ke En Ang, U. Rajendra Acharya, et al.
International Journal of Environmental Research and Public Health (2021) Vol. 18, Iss. 11, pp. 6099-6099
Open Access | Times Cited: 38
Spontaneous Brain Activity Alterations in First-Episode Psychosis: A Meta-analysis of Functional Magnetic Resonance Imaging Studies
Giulia Cattarinussi, David Antonio Grimaldi, Fabio Sambataro
Schizophrenia Bulletin (2023) Vol. 49, Iss. 6, pp. 1494-1507
Open Access | Times Cited: 13
Overlapping but Asymmetrical Relationships Between Schizophrenia and Autism Revealed by Brain Connectivity
Yujiro Yoshihara, Giuseppe Lisi, Noriaki Yahata, et al.
Schizophrenia Bulletin (2020) Vol. 46, Iss. 5, pp. 1210-1218
Open Access | Times Cited: 39
Deep learning model of fMRI connectivity predicts PTSD symptom trajectories in recent trauma survivors
Shelly Sheynin, Lior Wolf, Ziv Ben‐Zion, et al.
NeuroImage (2021) Vol. 238, pp. 118242-118242
Open Access | Times Cited: 27
Magnetic resonance imaging–based machine learning classification of schizophrenia spectrum disorders: a meta‐analysis
Fabio Di Camillo, David Antonio Grimaldi, Giulia Cattarinussi, et al.
Psychiatry and Clinical Neurosciences (2024)
Open Access | Times Cited: 4
Classification of schizophrenia spectrum disorder using machine learning and functional connectivity: reconsidering the clinical application
Chao Li, Ji Chen, Mengshi Dong, et al.
BMC Psychiatry (2025) Vol. 25, Iss. 1
Open Access
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