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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:

Will Machine Learning Enable Us to Finally Cut the Gordian Knot of Schizophrenia
Neeraj Tandon, Rajiv Tandon
Schizophrenia Bulletin (2018) Vol. 44, Iss. 5, pp. 939-941
Open Access | Times Cited: 31

Showing 1-25 of 31 citing articles:

Improving Mental Health Services: A 50-Year Journey from Randomized Experiments to Artificial Intelligence and Precision Mental Health
Leonard Bickman
Administration and Policy in Mental Health and Mental Health Services Research (2020) Vol. 47, Iss. 5, pp. 795-843
Open Access | Times Cited: 137
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
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: 88
Using Machine Learning in Psychiatry: The Need to Establish a Framework That Nurtures Trustworthiness
Chelsea Chandler, Peter W. Foltz, Brita Elvevåg
Schizophrenia Bulletin (2019)
Open Access | Times Cited: 58
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: 53
Applying speech technologies to assess verbal memory in patients with serious mental illness
Terje B. Holmlund, Chelsea Chandler, Peter W. Foltz, et al.
npj Digital Medicine (2020) Vol. 3, Iss. 1
Open Access | Times Cited: 40
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
Automation to optimise physician treatment of individual patients: examples in psychiatry
Michael Bauer, Scott Monteith, John Geddes, et al.
The Lancet Psychiatry (2019) Vol. 6, Iss. 4, pp. 338-349
Closed Access | Times Cited: 38
Artificial intelligence-based classification of schizophrenia: A high density electroencephalographic and support vector machine study
Sai Krishna Tikka, Bikesh Kumar Singh, SHaque Nizamie, et al.
Indian Journal of Psychiatry (2020) Vol. 62, Iss. 3, pp. 273-273
Open Access | Times Cited: 38
Using machine learning to explain the heterogeneity of schizophrenia. Realizing the promise and avoiding the hype
Neeraj Tandon, Rajiv Tandon
Schizophrenia Research (2019) Vol. 214, pp. 70-75
Closed Access | Times Cited: 36
Examination of retinal vascular trajectory in schizophrenia and bipolar disorder
Abhishek Appaji, Bhargavi Nagendra, Dona Maria Chako, et al.
Psychiatry and Clinical Neurosciences (2019) Vol. 73, Iss. 12, pp. 738-744
Open Access | Times Cited: 33
Reinventing schizophrenia. Updating the construct
Rajiv Tandon, Matcheri S. Keshavan, Henry A. Nasrallah
Schizophrenia Research (2022) Vol. 242, pp. 1-3
Closed Access | Times Cited: 18
Baseline structural and functional magnetic resonance imaging predicts early treatment response in schizophrenia with radiomics strategy
Long‐Biao Cui, Yu‐Fei Fu, Lin Liu, et al.
European Journal of Neuroscience (2020) Vol. 53, Iss. 6, pp. 1961-1975
Open Access | Times Cited: 25
Machine learning in psychiatry- standards and guidelines
Neeraj Tandon, Rajiv Tandon
Asian Journal of Psychiatry (2019) Vol. 44, pp. A1-A4
Closed Access | Times Cited: 20
Identifying psychosis spectrum disorder from experience sampling data using machine learning approaches
Daniel Stamate, Andrea Katrinecz, Daniel Ståhl, et al.
Schizophrenia Research (2019) Vol. 209, pp. 156-163
Open Access | Times Cited: 19
Neuroanatomical Features That Predict Response to Electroconvulsive Therapy Combined With Antipsychotics in Schizophrenia: A Magnetic Resonance Imaging Study Using Radiomics Strategy
Yi‐Bin Xi, Long‐Biao Cui, Jie Gong, et al.
Frontiers in Psychiatry (2020) Vol. 11
Open Access | Times Cited: 15
A step-by-step tutorial on how to build a machine learning model
Sandra Vieira, Rafael Garcia‐Dias, Walter Hugo Lopez Pinaya
Machine learning (2019), pp. 343-370
Closed Access | Times Cited: 13
Classification of first-episode psychosis using cortical thickness: A large multicenter MRI study
Alessandro Pigoni, Dominic Dwyer, Letizia Squarcina, et al.
European Neuropsychopharmacology (2021) Vol. 47, pp. 34-47
Closed Access | Times Cited: 9
Computational psychiatry and the psychopathology of psychosis: Promising leads and blind alleys
Rajiv Tandon
Schizophrenia Research (2023) Vol. 254, pp. 143-145
Closed Access | Times Cited: 3
Agreement on the contours of schizophrenia: The first order of business
Rajiv Tandon
Schizophrenia Research (2022) Vol. 242, pp. 135-137
Closed Access | Times Cited: 5
Accelerated aging signatures in subjects with schizophrenia and their unaffected siblings
Diego Barreto Rebouças, Juliana Sartori, Diego Librenza‐Garcia, et al.
Journal of Psychiatric Research (2021) Vol. 139, pp. 30-37
Closed Access | Times Cited: 7
Building the Precision Medicine for Mental Disorders via Radiomics/Machine Learning and Neuroimaging
Long‐Biao Cui, Xian Xu, Feng Cao
Frontiers in Neuroscience (2021) Vol. 15
Open Access | Times Cited: 7
Application of computational methods to the study of schizophrenia an exciting but treacherous frontier
Rajiv Tandon
Asian Journal of Psychiatry (2023) Vol. 87, pp. 103752-103752
Closed Access | Times Cited: 2
Inference of social cognition in schizophrenia patients with neurocognitive domains and neurocognitive tests using automated machine learning
Eugene Lin, Chieh‐Hsin Lin, Hsien‐Yuan Lane
Asian Journal of Psychiatry (2023) Vol. 91, pp. 103866-103866
Closed Access | Times Cited: 2
Bias, noise, and interpretability in machine learning
Hugo G. Schnack
Machine learning (2019), pp. 307-328
Closed Access | Times Cited: 5
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