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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:

Development of a prognostic model for mortality in COVID-19 infection using machine learning
Adam L. Booth, Elizabeth Abels, Peter McCaffrey
Modern Pathology (2020) Vol. 34, Iss. 3, pp. 522-531
Open Access | Times Cited: 162

Showing 1-25 of 162 citing articles:

Prediction models for diagnosis and prognosis of covid-19: systematic review and critical appraisal
Laure Wynants, Ben Van Calster, Gary S. Collins, et al.
BMJ (2020), pp. m1328-m1328
Open Access | Times Cited: 2843
Machine learning approaches in COVID-19 diagnosis, mortality, and severity risk prediction: A review
Norah Alballa, Isra Al-Turaiki
Informatics in Medicine Unlocked (2021) Vol. 24, pp. 100564-100564
Open Access | Times Cited: 196
Comparing machine learning algorithms for predicting COVID-19 mortality
Khadijeh Moulaei, Mostafa Shanbehzadeh, Zahra Mohammadi-Taghiabad, et al.
BMC Medical Informatics and Decision Making (2022) Vol. 22, Iss. 1
Open Access | Times Cited: 121
Review on the Evaluation and Development of Artificial Intelligence for COVID-19 Containment
Md. Mahadi Hasan, Muhammad Usama Islam, Muhammad Jafar Sadeq, et al.
Sensors (2023) Vol. 23, Iss. 1, pp. 527-527
Open Access | Times Cited: 47
Machine learning algorithms to predict depression in older adults in China: a cross-sectional study
Yongping Song, Chen Lin, Haoqiang Liu, et al.
Frontiers in Public Health (2025) Vol. 12
Open Access | Times Cited: 2
Temporal and spatial analysis of COVID-19 transmission in China and its influencing factors
Qian Wang, Wen Dong, Kun Yang, et al.
International Journal of Infectious Diseases (2021) Vol. 105, pp. 675-685
Open Access | Times Cited: 94
A machine learning based exploration of COVID-19 mortality risk
Mahdi Mahdavi, Hadi Choubdar, Erfan Zabeh, et al.
PLoS ONE (2021) Vol. 16, Iss. 7, pp. e0252384-e0252384
Open Access | Times Cited: 81
A systematic review on AI/ML approaches against COVID-19 outbreak
Onur Doğan, Sanju Tiwari, M. A. Jabbar, et al.
Complex & Intelligent Systems (2021) Vol. 7, Iss. 5, pp. 2655-2678
Open Access | Times Cited: 76
The Serum Metabolome of Moderate and Severe COVID-19 Patients Reflects Possible Liver Alterations Involving Carbon and Nitrogen Metabolism
Marianna Caterino, Michele Costanzo, Roberta Fedele, et al.
International Journal of Molecular Sciences (2021) Vol. 22, Iss. 17, pp. 9548-9548
Open Access | Times Cited: 73
The Role of Acidosis in the Pathogenesis of Severe Forms of COVID-19
Yury D. Nechipurenko, Denis Semyonov, I. A. Lavrinenko, et al.
Biology (2021) Vol. 10, Iss. 9, pp. 852-852
Open Access | Times Cited: 65
Comprehensive Survey of Using Machine Learning in the COVID-19 Pandemic
Nora El-Rashidy, Samir Abdelrazik, Tamer Abuhmed, et al.
Diagnostics (2021) Vol. 11, Iss. 7, pp. 1155-1155
Open Access | Times Cited: 57
Reviewing methods of deep learning for diagnosing COVID-19, its variants and synergistic medicine combinations
Qandeel Rafique, Ali Rehman, Muhammad Sher Afghan, et al.
Computers in Biology and Medicine (2023) Vol. 163, pp. 107191-107191
Open Access | Times Cited: 25
Explainable machine-learning tools for predictive maintenance of circulating water systems in nuclear power plants
Linyu Lin, Cody Walker, Vivek Agarwal
Nuclear Engineering and Technology (2025), pp. 103588-103588
Open Access | Times Cited: 1
COVID Mortality Prediction with Machine Learning Methods: A Systematic Review and Critical Appraisal
Francesca Bottino, Emanuela Tagliente, Luca Pasquini, et al.
Journal of Personalized Medicine (2021) Vol. 11, Iss. 9, pp. 893-893
Open Access | Times Cited: 54
Artificial Intelligence: Review of Current and Future Applications in Medicine
L. Brannon Thomas, Stephen Mastorides, Narayan Viswanadhan, et al.
Federal practitioner (2021), Iss. 38 (11)
Open Access | Times Cited: 48
Machine Learning Sensors for Diagnosis of COVID-19 Disease Using Routine Blood Values for Internet of Things Application
Andrei Velichko, Mehmet Tahir Huyut, Maksim Belyaev, et al.
Sensors (2022) Vol. 22, Iss. 20, pp. 7886-7886
Open Access | Times Cited: 38
Neuroimaging in the Era of Artificial Intelligence: Current Applications
Robert Monsour
Federal practitioner (2022), Iss. 39 (Suppl 1)
Open Access | Times Cited: 37
COVID-19 mortality prediction in the intensive care unit with deep learning based on longitudinal chest X-rays and clinical data
Jianhong Cheng, John Sollee, Celina Hsieh, et al.
European Radiology (2022) Vol. 32, Iss. 7, pp. 4446-4456
Open Access | Times Cited: 34
Gut Microbiota Disruption in COVID-19 or Post-COVID Illness Association with severity biomarkers: A Possible Role of Pre / Pro-biotics in manipulating microflora
Khalid Saad Alharbi, Yogendra Singh, Waleed Hassan Almalki, et al.
Chemico-Biological Interactions (2022) Vol. 358, pp. 109898-109898
Open Access | Times Cited: 33
Using Machine Learning to Predict Mortality for COVID-19 Patients on Day 0 in the ICU
Elham Jamshidi, Amirhossein Asgary, Nader Tavakoli, et al.
Frontiers in Digital Health (2022) Vol. 3
Open Access | Times Cited: 32
Effect of ferritin, INR, and D-dimer immunological parameters levels as predictors of COVID-19 mortality: A strong prediction with the decision trees
Mehmet Tahir Huyut, Zübeyir Huyut
Heliyon (2023) Vol. 9, Iss. 3, pp. e14015-e14015
Open Access | Times Cited: 23
Dynamics of Inflammatory Markers in Predicting Mortality in COVID-19
Aditi Parimoo, Ashutosh Biswas, Upendra Baitha, et al.
Cureus (2021)
Open Access | Times Cited: 37
The association of viral load and disease severity in children with COVID‐19
Kübra Aykaç, Burcu Ceylan Cura Yayla, Yasemin Özsürekçi, et al.
Journal of Medical Virology (2021) Vol. 93, Iss. 5, pp. 3077-3083
Open Access | Times Cited: 35
Blood Urea Nitrogen to Serum Albumin Ratio (BAR) Predicts Critical Illness in Patients with Coronavirus Disease 2019 (COVID-19)
Dong Huang, Huan Yang, Yu He, et al.
International Journal of General Medicine (2021) Vol. Volume 14, pp. 4711-4721
Open Access | Times Cited: 33
A Comprehensive Review of Machine Learning Used to Combat COVID-19
Rahul Gomes, Connor Kamrowski, Jordan Langlois, et al.
Diagnostics (2022) Vol. 12, Iss. 8, pp. 1853-1853
Open Access | Times Cited: 27
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