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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.

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Showing 1-25 of 73 citing articles:

Artificial intelligence and machine learning‐aided drug discovery in central nervous system diseases: State‐of‐the‐arts and future directions
Sezen Vatansever, Avner Schlessinger, Daniel Wacker, et al.
Medicinal Research Reviews (2020) Vol. 41, Iss. 3, pp. 1427-1473
Open Access | Times Cited: 272
Consistent gene signature of schizophrenia identified by a novel feature selection strategy from comprehensive sets of transcriptomic data
Qingxia Yang, Bo Li, Jing Tang, et al.
Briefings in Bioinformatics (2019) Vol. 21, Iss. 3, pp. 1058-1068
Closed Access | Times Cited: 212
Introduction to machine learning
Sandra Vieira, Walter Hugo Lopez Pinaya, Andrea Mechelli
Machine learning (2019), pp. 1-20
Closed Access | Times Cited: 184
Making Individual Prognoses in Psychiatry Using Neuroimaging and Machine Learning
Ronald J. Janssen, Janaı́na Mourão-Miranda, Hugo G. Schnack
Biological Psychiatry Cognitive Neuroscience and Neuroimaging (2018) Vol. 3, Iss. 9, pp. 798-808
Open Access | Times Cited: 164
The foundation and architecture of precision medicine in neurology and psychiatry
Harald Hampel, Peng Gao, Jeffrey L. Cummings, et al.
Trends in Neurosciences (2023) Vol. 46, Iss. 3, pp. 176-198
Open Access | Times Cited: 70
Machine learning for genetic prediction of psychiatric disorders: a systematic review
Matthew Bracher‐Smith, Karen Crawford, Valentina Escott‐Price
Molecular Psychiatry (2020) Vol. 26, Iss. 1, pp. 70-79
Open Access | Times Cited: 120
Using Machine Learning and Structural Neuroimaging to Detect First Episode Psychosis: Reconsidering the Evidence
Sandra Vieira, Qiyong Gong, Walter Hugo Lopez Pinaya, et al.
Schizophrenia Bulletin (2018) Vol. 46, Iss. 1, pp. 17-26
Open Access | Times Cited: 89
Advanced EEG-based learning approaches to predict schizophrenia: Promises and pitfalls
Carla Barros, Carlos A. Silva, Ana P. Pinheiro
Artificial Intelligence in Medicine (2021) Vol. 114, pp. 102039-102039
Open Access | Times Cited: 80
Can we predict who will benefit from cognitive-behavioural therapy? A systematic review and meta-analysis of machine learning studies
Sandra Vieira, Xinyi Liang, Raquel Guiomar, et al.
Clinical Psychology Review (2022) Vol. 97, pp. 102193-102193
Open Access | Times Cited: 49
Artificial intelligence-assisted psychosis risk screening in adolescents: Practices and challenges
Xiaojie Cao, Xinqiao Liu
World Journal of Psychiatry (2022) Vol. 12, Iss. 10, pp. 1287-1297
Open Access | Times Cited: 45
Speech disturbances in schizophrenia: Assessing cross-linguistic generalizability of NLP automated measures of coherence
Alberto Parola, Jessica Mary Lin, Arndis Simonsen, et al.
Schizophrenia Research (2022) Vol. 259, pp. 59-70
Open Access | Times Cited: 39
Translational machine learning for psychiatric neuroimaging
Martin Walter, Sarah Alizadeh, Hamidreza Jamalabadi, et al.
Progress in Neuro-Psychopharmacology and Biological Psychiatry (2018) Vol. 91, pp. 113-121
Closed Access | Times Cited: 69
Computing schizophrenia: ethical challenges for machine learning in psychiatry
Georg Starke, Eva De Clercq, Stefan Borgwardt, et al.
Psychological Medicine (2020) Vol. 51, Iss. 15, pp. 2515-2521
Open Access | Times Cited: 56
Morphological Profiling of Schizophrenia: Cluster Analysis of MRI-Based Cortical Thickness Data
Yunzhi Pan, Weidan Pu, Xudong Chen, et al.
Schizophrenia Bulletin (2019) Vol. 46, Iss. 3, pp. 623-632
Open Access | Times Cited: 55
Voice Patterns as Markers of Schizophrenia: Building a Cumulative Generalizable Approach Via a Cross-Linguistic and Meta-analysis Based Investigation
Alberto Parola, Arndis Simonsen, Jessica Mary Lin, et al.
Schizophrenia Bulletin (2023) Vol. 49, Iss. Supplement_2, pp. S125-S141
Open Access | Times Cited: 19
A comprehensive review of predictive analytics models for mental illness using machine learning algorithms
Md. Monirul Islam, Shahriar Hassan, Sharmin Akter, et al.
Healthcare Analytics (2024) Vol. 6, pp. 100350-100350
Open Access | Times Cited: 8
Neuroanatomical heterogeneity of schizophrenia revealed by semi-supervised machine learning methods
Nicolas Honnorat, Aoyan Dong, Eva Meisenzahl‐Lechner, et al.
Schizophrenia Research (2017) Vol. 214, pp. 43-50
Open Access | Times Cited: 57
Classification of First-Episode Schizophrenia Using Multimodal Brain Features: A Combined Structural and Diffusion Imaging Study
Sugai Liang, Yinfei Li, Zhong Zhang, et al.
Schizophrenia Bulletin (2018) Vol. 45, Iss. 3, pp. 591-599
Open Access | Times Cited: 53
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: 6
Effectiveness of Machine Learning Technology in Detecting Patterns of Certain Diseases Within Patient Electronic Healthcare Records
Dilip Kumar Sharma, Dhruva Sreenivasa Chakravarthi, Raja Sarath Kumar Boddu, et al.
Smart innovation, systems and technologies (2022), pp. 73-81
Closed Access | Times Cited: 21
From models to tools: clinical translation of machine learning studies in psychosis
Andrea Mechelli, Sandra Vieira
Schizophrenia (2020) Vol. 6, Iss. 1
Open Access | Times Cited: 30
Individualized prediction of three- and six-year outcomes of psychosis in a longitudinal multicenter study: a machine learning approach
Jessica de Nijs, Thijs Jan Burger, Ronald J. Janssen, et al.
Schizophrenia (2021) Vol. 7, Iss. 1
Open Access | Times Cited: 26
Characterizing speech heterogeneity in schizophrenia-spectrum disorders.
Priscilla P. Oomen, Janna N. de Boer, Sanne Brederoo, et al.
Journal of Psychopathology and Clinical Science (2022) Vol. 131, Iss. 2, pp. 172-181
Open Access | Times Cited: 19
Transdiagnostic connectome signatures from resting-state fMRI predict individual-level intellectual capacity
Xiaoyu Tong, Hua Xie, Nancy B. Carlisle, et al.
Translational Psychiatry (2022) Vol. 12, Iss. 1
Open Access | Times Cited: 17
Can we diagnose mental disorders in children? A large‐scale assessment of machine learning on structural neuroimaging of 6916 children in the adolescent brain cognitive development study
Richard Gaus, Sebastian Pölsterl, Ellen Greimel, et al.
JCPP Advances (2023) Vol. 3, Iss. 4
Open Access | Times Cited: 10
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