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OpenAlex Citation Counts

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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:

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: 118

Showing 1-25 of 118 citing articles:

Artificial Intelligence for Mental Health Care: Clinical Applications, Barriers, Facilitators, and Artificial Wisdom
Ellen Lee, John Torous, Munmun De Choudhury, et al.
Biological Psychiatry Cognitive Neuroscience and Neuroimaging (2021) Vol. 6, Iss. 9, pp. 856-864
Open Access | Times Cited: 236
Evaluation of artificial intelligence techniques in disease diagnosis and prediction
Nafiseh Ghaffar Nia, Erkan Kaplanoğlu, Ahad Nasab
Discover Artificial Intelligence (2023) Vol. 3, Iss. 1
Open Access | Times Cited: 169
Clinical prediction models in psychiatry: a systematic review of two decades of progress and challenges
Alan J. Meehan, Stephanie J. Lewis, Seena Fazel, et al.
Molecular Psychiatry (2022) Vol. 27, Iss. 6, pp. 2700-2708
Open Access | Times Cited: 116
Modern views of machine learning for precision psychiatry
Zhe Chen, Prathamesh Kulkarni, Isaac R. Galatzer‐Levy, et al.
Patterns (2022) Vol. 3, Iss. 11, pp. 100602-100602
Open Access | Times Cited: 84
The performance of artificial intelligence-driven technologies in diagnosing mental disorders: an umbrella review
Alaa Abd‐Alrazaq, Dari Alhuwail, Jens Schneider, et al.
npj Digital Medicine (2022) Vol. 5, Iss. 1
Open Access | Times Cited: 58
Artificial intelligence, machine learning, and deep learning for clinical outcome prediction
Rowland W. Pettit, Robert Fullem, Chao Cheng, et al.
Emerging Topics in Life Sciences (2021) Vol. 5, Iss. 6, pp. 729-745
Open Access | Times Cited: 57
Risk of bias of prognostic models developed using machine learning: a systematic review in oncology
Paula Dhiman, Jie Ma, Constanza L. Andaur Navarro, et al.
Diagnostic and Prognostic Research (2022) Vol. 6, Iss. 1
Open Access | Times Cited: 44
Applications of artificial intelligence−machine learning for detection of stress: a critical overview
Alexios‐Fotios A. Mentis, Donghoon Lee, Panos Roussos
Molecular Psychiatry (2023) Vol. 29, Iss. 6, pp. 1882-1894
Closed Access | Times Cited: 35
Diagnosis of autism spectrum disorder based on functional brain networks and machine learning
Caroline L. Alves, Thaise G. L. de O. Toutain, Patrícia de Carvalho Aguiar, et al.
Scientific Reports (2023) Vol. 13, Iss. 1
Open Access | Times Cited: 25
Overinterpretation of findings in machine learning prediction model studies in oncology: a systematic review
Paula Dhiman, Jie Ma, Constanza L. Andaur Navarro, et al.
Journal of Clinical Epidemiology (2023) Vol. 157, pp. 120-133
Open Access | Times Cited: 24
Predicting whether patients will achieve minimal clinically important differences following hip or knee arthroplasty
Benedikt Langenberger, Daniel Schrednitzki, Andreas M. Halder, et al.
Bone and Joint Research (2023) Vol. 12, Iss. 9, pp. 512-521
Open Access | Times Cited: 23
From Serendipity to Precision: Integrating AI, Multi-Omics, and Human-Specific Models for Personalized Neuropsychiatric Care
Masaru Tanaka
Biomedicines (2025) Vol. 13, Iss. 1, pp. 167-167
Open Access | Times Cited: 1
Artificial intelligence and its impact on the domains of universal health coverage, health emergencies and health promotion: An overview of systematic reviews
Antonio Martínez-Millana, Aida Saez-Saez, Roberto Tornero-Costa, et al.
International Journal of Medical Informatics (2022) Vol. 166, pp. 104855-104855
Open Access | Times Cited: 36
The performance of machine learning models in predicting suicidal ideation, attempts, and deaths: A meta-analysis and systematic review
Karen Kusuma, Mark Larsen, Juan C. Quiroz, et al.
Journal of Psychiatric Research (2022) Vol. 155, pp. 579-588
Closed Access | Times Cited: 35
Transparency of Artificial Intelligence in Healthcare: Insights from Professionals in Computing and Healthcare Worldwide
José Bernal, Claudia Mazo
Applied Sciences (2022) Vol. 12, Iss. 20, pp. 10228-10228
Open Access | Times Cited: 30
Machine learning approaches for prediction of bipolar disorder based on biological, clinical and neuropsychological markers: A systematic review and meta-analysis
F. Colombo, F. Calesella, Mario Gennaro Mazza, et al.
Neuroscience & Biobehavioral Reviews (2022) Vol. 135, pp. 104552-104552
Closed Access | Times Cited: 25
Mapping the genetic architecture of cortical morphology through neuroimaging: progress and perspectives
Dennis van der Meer, Tobias Kaufmann
Translational Psychiatry (2022) Vol. 12, Iss. 1
Open Access | Times Cited: 23
Deep Learning for Cross-Diagnostic Prediction of Mental Disorder Diagnosis and Prognosis Using Danish Nationwide Register and Genetic Data
Rosa Lundbye Allesøe, Wesley K. Thompson, Jonas Bybjerg‐Grauholm, et al.
JAMA Psychiatry (2022) Vol. 80, Iss. 2, pp. 146-146
Open Access | Times Cited: 23
Analysis of functional connectivity using machine learning and deep learning in different data modalities from individuals with schizophrenia
Caroline L. Alves, Thaise G. L. de O. Toutain, Joel Augusto Moura Porto, et al.
Journal of Neural Engineering (2023) Vol. 20, Iss. 5, pp. 056025-056025
Open Access | Times Cited: 14
Systematic reviews of machine learning in healthcare: a literature review
Katarzyna Kolasa, Bisrat Yeshewas Admassu, Malwina Hołownia-Voloskova, et al.
Expert Review of Pharmacoeconomics & Outcomes Research (2023) Vol. 24, Iss. 1, pp. 63-115
Open Access | Times Cited: 14
Effective dimensionality reduction model with machine learning classification for microarray gene expression data
Yakub Kayode Saheed
Elsevier eBooks (2023), pp. 153-164
Closed Access | Times Cited: 13
Detecting acute respiratory diseases in the pediatric population using cough sound features and machine learning: A systematic review
Roneel V. Sharan, Hania Rahimi‐Ardabili
International Journal of Medical Informatics (2023) Vol. 176, pp. 105093-105093
Open Access | Times Cited: 13
Machine-learning-based diagnosis of drug-naive adult patients with attention-deficit hyperactivity disorder using mismatch negativity
Sungkean Kim, Ji Hyun Baek, Young‐Joon Kwon, et al.
Translational Psychiatry (2021) Vol. 11, Iss. 1
Open Access | Times Cited: 28
Application of machine learning methods in predicting schizophrenia and bipolar disorders: A systematic review
Mahdieh Montazeri, Mitra Montazeri, Kambiz Bahaadinbeigy, et al.
Health Science Reports (2022) Vol. 6, Iss. 1
Open Access | Times Cited: 20
Machine learning for prediction of schizophrenia using genetic and demographic factors in the UK biobank
Matthew Bracher‐Smith, Elliott Rees, Georgina Menzies, et al.
Schizophrenia Research (2022) Vol. 246, pp. 156-164
Open Access | Times Cited: 19
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