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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:

A support vector machine model provides an accurate transcript-level-based diagnostic for major depressive disorder
Jessica S. Yu, Albert Xue, Eva E. Redei, et al.
Translational Psychiatry (2016) Vol. 6, Iss. 10, pp. e931-e931
Open Access | Times Cited: 50

Showing 1-25 of 50 citing articles:

Towards revolutionizing precision healthcare: A systematic literature review of artificial intelligence methods in precision medicine
Wafae Abbaoui, Sara Retal, Brahim El Bhiri, et al.
Informatics in Medicine Unlocked (2024) Vol. 46, pp. 101475-101475
Open Access | Times Cited: 26
An insight into diagnosis of depression using machine learning techniques: a systematic review
Sweta Bhadra, Chandan Jyoti Kumar
Current Medical Research and Opinion (2022) Vol. 38, Iss. 5, pp. 749-771
Closed Access | Times Cited: 53
Prediction of generalized anxiety levels during the Covid-19 pandemic: A machine learning-based modeling approach
Faisal Albagmi, Aisha Alansari, Deema Saad Al Shawan, et al.
Informatics in Medicine Unlocked (2022) Vol. 28, pp. 100854-100854
Open Access | Times Cited: 37
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
Whole-brain resting-state functional connectivity identified major depressive disorder: A multivariate pattern analysis in two independent samples
Xue Zhong, Huqing Shi, Qingsen Ming, et al.
Journal of Affective Disorders (2017) Vol. 218, pp. 346-352
Closed Access | Times Cited: 53
Machine learning based prediction of depression among type 2 diabetic patients
Raid M. Khalil, Adel Al-Jumaily
2021 16th International Conference on Intelligent Systems and Knowledge Engineering (ISKE) (2017), pp. 1-5
Closed Access | Times Cited: 40
Disrupted Regional Homogeneity in Melancholic and Non-melancholic Major Depressive Disorder at Rest
Meiqi Yan, Yuqiong He, Xilong Cui, et al.
Frontiers in Psychiatry (2021) Vol. 12
Open Access | Times Cited: 31
Multi-Bands Joint Graph Convolution EEG Functional Connectivity Network for Predicting Mental Disorders
Cancheng Li, Shengbo Gao, Jicong Zhang
International Journal of Crowd Science (2024) Vol. 8, Iss. 2, pp. 65-70
Open Access | Times Cited: 4
Identifying Plasma Biomarkers with high specificity for major depressive disorder: A multi-level proteomics study
Yachen Shi, Ruize Song, Liping Wang, et al.
Journal of Affective Disorders (2020) Vol. 277, pp. 620-630
Closed Access | Times Cited: 32
Abnormalities in cognitive-related functional connectivity can be used to identify patients with schizophrenia and individuals in clinical high-risk
Yangpan Ou, Zhaobin Chen, Ying Wang, et al.
BMC Psychiatry (2025) Vol. 25, Iss. 1
Open Access
Machine learning approaches for classifying major depressive disorder using biological and neuropsychological markers: A meta-analysis
Lin Zhang, L. K. Jian, Yun Long, et al.
Neuroscience & Biobehavioral Reviews (2025), pp. 106201-106201
Closed Access
Patient Survival After Kidney Transplantation: Important Role of Graft-sustaining Factors as Determined by Predictive Modeling Using Random Survival Forest Analysis
Irina Scheffner, Matthias Gietzelt, Tanja Abeling, et al.
Transplantation (2019) Vol. 104, Iss. 5, pp. 1095-1107
Closed Access | Times Cited: 29
Characterization of Iranian Grapevine Cultivars Using Machine Learning Models
Bahman Panahi, Seyed Abolghasem Mohammadi, Hamed Doulati-Baneh
Proceedings of the National Academy of Sciences India Section B Biological Sciences (2019) Vol. 90, Iss. 3, pp. 615-621
Closed Access | Times Cited: 26
The Wistar Kyoto Rat: A Model of Depression Traits
Eva E. Redei, Mallory E. Udell, Leah C. Solberg Woods, et al.
Current Neuropharmacology (2022) Vol. 21, Iss. 9, pp. 1884-1905
Open Access | Times Cited: 16
Evaluating predictive artificial intelligence approaches used in mobile health platforms to forecast mental health symptoms among youth: a systematic review
Jamin Patel, Chih-Ching Hung, Tarun Reddy Katapally
Psychiatry Research (2024) Vol. 343, pp. 116277-116277
Open Access | Times Cited: 3
Heterogeneous stock rats: a model to study the genetics of despair‐like behavior in adolescence
Katie Holl, Hong He, Michael J. Wedemeyer, et al.
Genes Brain & Behavior (2017) Vol. 17, Iss. 2, pp. 139-148
Open Access | Times Cited: 28
Conceptual endophenotypes: A strategy to advance the impact of psychoneuroendocrinology in precision medicine
Dirk H. Hellhammer, Gunther Meinlschmidt, Jens C. Pruessner
Psychoneuroendocrinology (2018) Vol. 89, pp. 147-160
Open Access | Times Cited: 25
Abnormal Default-Mode Network Homogeneity in Melancholic and Nonmelancholic Major Depressive Disorder at Rest
Meiqi Yan, Xilong Cui, Feng Liu, et al.
Neural Plasticity (2021) Vol. 2021, pp. 1-12
Open Access | Times Cited: 20
Variability and association among some pomological and physiochemical traits in spring frost tolerant genotypes of Persian walnut (Juglans regia L.) and selection of genotypes with superior traits based on machine learning algorithms
Bahman Panahi, Sadegh Tajaddod, Hossein Mohammadzadeh Jallali, et al.
Genetic Resources and Crop Evolution (2021) Vol. 69, Iss. 3, pp. 959-971
Closed Access | Times Cited: 19
Quantitative Assessment of Speech in Cerebellar Ataxia Using Magnitude and Phase Based Cepstrum
Bipasha Kashyap, Pubudu N. Pathirana, Malcolm Horne, et al.
Annals of Biomedical Engineering (2020) Vol. 48, Iss. 4, pp. 1322-1336
Closed Access | Times Cited: 17
Abnormal long- and short-range functional connectivity in patients with first-episode drug-naïve melancholic and non-melancholic major depressive disorder
Lulu Zhang, Xilong Cui, Yangpan Ou, et al.
Journal of Affective Disorders (2022) Vol. 320, pp. 360-369
Closed Access | Times Cited: 11
Metabolic Fingerprints of Effective Fluoxetine Treatment in the Prefrontal Cortex of Chronically Socially Isolated Rats: Marker Candidates and Predictive Metabolites
Dragana Filipović, Julica Inderhees, Αλεξάνδρα Κορδά, et al.
International Journal of Molecular Sciences (2023) Vol. 24, Iss. 13, pp. 10957-10957
Open Access | Times Cited: 6
Imaging and Genetic Biomarkers Predicting Transition to Psychosis
Stuart Hunter, Stephen M. Lawrie
Current topics in behavioral neurosciences (2018), pp. 353-388
Closed Access | Times Cited: 17
Whole genome sequencing of nearly isogenic WMI and WLI inbred rats identifies genes potentially involved in depression and stress reactivity
Tristan V. de Jong, Panjun Kim, Victor Guryev, et al.
Scientific Reports (2021) Vol. 11, Iss. 1
Open Access | Times Cited: 12
Genetic variation of the mineralocorticoid receptor gene (MR, NR3C2) is associated with a conceptual endophenotype of “CRF-hypoactivity”
Robert Kumsta, David Kliegel, Michael Linden, et al.
Psychoneuroendocrinology (2018) Vol. 105, pp. 79-85
Closed Access | Times Cited: 14
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