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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 to Predict Mortality and Critical Events in a Cohort of Patients With COVID-19 in New York City: Model Development and Validation
Akhil Vaid, Sulaiman Somani, Adam Russak, et al.
Journal of Medical Internet Research (2020) Vol. 22, Iss. 11, pp. e24018-e24018
Open Access | Times Cited: 208

Showing 1-25 of 208 citing articles:

Adoption of Digital Technologies in Health Care During the COVID-19 Pandemic: Systematic Review of Early Scientific Literature
Davide Golinelli, Erik Boetto, Gherardo Carullo, et al.
Journal of Medical Internet Research (2020) Vol. 22, Iss. 11, pp. e22280-e22280
Open Access | Times Cited: 436
Applications of artificial intelligence in battling against covid-19: A literature review
Mohammad-H. Tayarani N.
Chaos Solitons & Fractals (2020) Vol. 142, pp. 110338-110338
Open Access | Times Cited: 194
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: 193
Time series prediction of COVID-19 transmission in America using LSTM and XGBoost algorithms
Junling Luo, Zhong-Liang Zhang, Yao Fu, et al.
Results in Physics (2021) Vol. 27, pp. 104462-104462
Open Access | Times Cited: 109
Machine Learning Based Clinical Decision Support System for Early COVID-19 Mortality Prediction
A. Karthikeyan, Akshit Garg, P. K. Vinod, et al.
Frontiers in Public Health (2021) Vol. 9
Open Access | Times Cited: 95
Leveraging artificial intelligence for pandemic preparedness and response: a scoping review to identify key use cases
Ania Syrowatka, Masha Kuznetsova, Ava Alsubai, et al.
npj Digital Medicine (2021) Vol. 4, Iss. 1
Open Access | Times Cited: 87
Artificial intelligence in clinical care amidst COVID-19 pandemic: A systematic review
Eleni S. Adamidi, Konstantinos Mitsis, Konstantina S. Nikita
Computational and Structural Biotechnology Journal (2021) Vol. 19, pp. 2833-2850
Open Access | Times Cited: 79
Using Automated Machine Learning to Predict the Mortality of Patients With COVID-19: Prediction Model Development Study
Kenji Ikemura, Eran Bellin, Yukako Yagi, et al.
Journal of Medical Internet Research (2021) Vol. 23, Iss. 2, pp. e23458-e23458
Open Access | Times Cited: 77
Explainable Machine Learning for Early Assessment of COVID-19 Risk Prediction in Emergency Departments
Elena Casiraghi, Dario Malchiodi, Gabriella Trucco, et al.
IEEE Access (2020) Vol. 8, pp. 196299-196325
Open Access | Times Cited: 73
Application of a data-driven XGBoost model for the prediction of COVID-19 in the USA: a time-series study
Zheng-gang Fang, Shuqin Yang, Cai-Xia Lv, et al.
BMJ Open (2022) Vol. 12, Iss. 7, pp. e056685-e056685
Open Access | Times Cited: 64
Survival Regression with Accelerated Failure Time Model in XGBoost
Avinash Barnwal, Hyunsu Cho, Toby Dylan Hocking
Journal of Computational and Graphical Statistics (2022) Vol. 31, Iss. 4, pp. 1292-1302
Open Access | Times Cited: 47
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
Mortality Prediction Utilizing Blood Biomarkers to Predict the Severity of COVID-19 Using Machine Learning Technique
Tawsifur Rahman, Fajer Al‐Ishaq, Fatima S. Al-Mohannadi, et al.
Diagnostics (2021) Vol. 11, Iss. 9, pp. 1582-1582
Open Access | Times Cited: 42
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
Using machine learning in prediction of ICU admission, mortality, and length of stay in the early stage of admission of COVID-19 patients
Sara Saadatmand, Khodakaram Salimifard, Reza Mohammadi, et al.
Annals of Operations Research (2022) Vol. 328, Iss. 1, pp. 1043-1071
Open Access | Times Cited: 31
Optimized fuzzy K-nearest neighbor approach for accurate lung cancer prediction based on radial endobronchial ultrasonography
Jie Xing, Chengye Li, Peiliang Wu, et al.
Computers in Biology and Medicine (2024) Vol. 171, pp. 108038-108038
Closed Access | Times Cited: 5
Machine-learning based risk prediction of outcomes in patients hospitalised with COVID-19 in Australia: the AUS-COVID score
H. Sritharan, Harrison Nguyen, W. van Gaal, et al.
Journal of the American Medical Informatics Association (2025)
Closed Access
ПРОГНОЗУВАННЯ РИЗИКУ ТЯЖКОГО ПЕРЕБІГУ COVID-19 У ДІТЕЙ
Halyna Pavlyshyn, О. В. Лабівка
Актуальні питання педіатрії акушерства та гінекології (2025), Iss. 2, pp. 88-94
Open Access
Adaptable graph neural networks design to support generalizability for clinical event prediction
Amara Tariq, Gaganpreet Kaur, Leon Su, et al.
Journal of Biomedical Informatics (2025) Vol. 163, pp. 104794-104794
Closed Access
Prediction and Feature Importance Analysis for Severity of COVID-19 in South Korea Using Artificial Intelligence: Model Development and Validation
Heewon Chung, Hoon Ko, Wu Seong Kang, et al.
Journal of Medical Internet Research (2021) Vol. 23, Iss. 4, pp. e27060-e27060
Open Access | Times Cited: 38
Classification Models for COVID-19 Test Prioritization in Brazil: Machine Learning Approach
Íris Viana dos Santos Santana, Andressa CM da Silveira, Álvaro Sobrinho, et al.
Journal of Medical Internet Research (2021) Vol. 23, Iss. 4, pp. e27293-e27293
Open Access | Times Cited: 38
Predicting Mechanical Ventilation and Mortality in COVID-19 Using Radiomics and Deep Learning on Chest Radiographs: A Multi-Institutional Study
Joseph Bae, Saarthak Kapse, Gagandeep Singh, et al.
Diagnostics (2021) Vol. 11, Iss. 10, pp. 1812-1812
Open Access | Times Cited: 36
Prognostic model to identify and quantify risk factors for mortality among hospitalised patients with COVID-19 in the USA
Devin Incerti, Shemra Rizzo, Xiao Li, et al.
BMJ Open (2021) Vol. 11, Iss. 4, pp. e047121-e047121
Open Access | Times Cited: 33
Predicting in-Hospital Mortality of Patients with COVID-19 Using Machine Learning Techniques
Fabiana Tezza, Giulia Lorenzoni, Danila Azzolina, et al.
Journal of Personalized Medicine (2021) Vol. 11, Iss. 5, pp. 343-343
Open Access | Times Cited: 33
Prediction of in‐hospital mortality with machine learning for COVID‐19 patients treated with steroid and remdesivir
Toshiki Kuno, Yuki Sahashi, Shinpei Kawahito, et al.
Journal of Medical Virology (2021) Vol. 94, Iss. 3, pp. 958-964
Open Access | Times Cited: 33
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