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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:

Prognostic Assessment of COVID-19 in the Intensive Care Unit by Machine Learning Methods: Model Development and Validation
Pan Pan, Yichao Li, Yongjiu Xiao, et al.
Journal of Medical Internet Research (2020) Vol. 22, Iss. 11, pp. e23128-e23128
Open Access | Times Cited: 115

Showing 1-25 of 115 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
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
Deep transfer learning approaches for Monkeypox disease diagnosis
Md Manjurul Ahsan, Muhammad Ramiz Uddin, Md Shahin Ali, et al.
Expert Systems with Applications (2023) Vol. 216, pp. 119483-119483
Open Access | Times Cited: 87
Explainable Artificial Intelligence Methods in Combating Pandemics: A Systematic Review
Felipe Giuste, Wenqi Shi, Yuanda Zhu, et al.
IEEE Reviews in Biomedical Engineering (2022) Vol. 16, pp. 5-21
Open Access | Times Cited: 85
Predicting Mortality in Intensive Care Unit Patients With Heart Failure Using an Interpretable Machine Learning Model: Retrospective Cohort Study
Jili Li, Siru Liu, Yundi Hu, et al.
Journal of Medical Internet Research (2022) Vol. 24, Iss. 8, pp. e38082-e38082
Open Access | Times Cited: 79
Factors associated with mortality in patients with COVID‐19 admitted to intensive care: a systematic review and meta‐analysis
Elliott H Taylor, Ella J Marson, Muhammed Elhadi, et al.
Anaesthesia (2021) Vol. 76, Iss. 9, pp. 1224-1232
Open Access | Times Cited: 92
Extreme gradient boosting model to assess risk of central cervical lymph node metastasis in patients with papillary thyroid carcinoma: Individual prediction using SHapley Additive exPlanations
Ying Zou, Yan Shi, Fang Sun, et al.
Computer Methods and Programs in Biomedicine (2022) Vol. 225, pp. 107038-107038
Open Access | Times Cited: 41
The economics of deep and machine learning-based algorithms for COVID-19 prediction, detection, and diagnosis shaping the organizational management of hospitals
George Lăzăroiu, Tom Gedeon, Elżbieta Rogalska, et al.
Oeconomia Copernicana (2024) Vol. 15, Iss. 1, pp. 27-58
Open Access | Times Cited: 14
Prognosis of COVID-19 severity using DERGA, a novel machine learning algorithm
Panagiotis G. Asteris, Amir H. Gandomi, Danial Jahed Armaghani, et al.
European Journal of Internal Medicine (2024) Vol. 125, pp. 67-73
Closed Access | Times Cited: 11
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
E-CatBoost: An efficient machine learning framework for predicting ICU mortality using the eICU Collaborative Research Database
Nima Safaei, Babak Safaei, Seyedhouman Seyedekrami, et al.
PLoS ONE (2022) Vol. 17, Iss. 5, pp. e0262895-e0262895
Open Access | Times Cited: 37
A Comparison of XGBoost, Random Forest, and Nomograph for the Prediction of Disease Severity in Patients With COVID-19 Pneumonia: Implications of Cytokine and Immune Cell Profile
Wandong Hong, Xiaoying Zhou, Shengchun Jin, et al.
Frontiers in Cellular and Infection Microbiology (2022) Vol. 12
Open Access | Times Cited: 34
Rapid triage for ischemic stroke: a machine learning-driven approach in the context of predictive, preventive and personalised medicine
Yulu Zheng, Zheng Guo, Yanbo Zhang, et al.
The EPMA Journal (2022) Vol. 13, Iss. 2, pp. 285-298
Open Access | Times Cited: 33
A machine learning model based on ultrasound image features to assess the risk of sentinel lymph node metastasis in breast cancer patients: Applications of scikit-learn and SHAP
Gaosen Zhang, Yan Shi, Peipei Yin, et al.
Frontiers in Oncology (2022) Vol. 12
Open Access | Times Cited: 30
Ultrasound-based radiomics XGBoost model to assess the risk of central cervical lymph node metastasis in patients with papillary thyroid carcinoma: Individual application of SHAP
Yan Shi, Ying Zou, Jihua Liu, et al.
Frontiers in Oncology (2022) Vol. 12
Open Access | Times Cited: 27
Usefulness of Random Forest Algorithm in Predicting Severe Acute Pancreatitis
Wandong Hong, Yajing Lu, Xiaoying Zhou, et al.
Frontiers in Cellular and Infection Microbiology (2022) Vol. 12
Open Access | Times Cited: 26
Early prediction of COVID-19 outcome using artificial intelligence techniques and only five laboratory indices
Panagiotis G. Asteris, Styliani Kokoris, Eleni Gavriilaki, et al.
Clinical Immunology (2022) Vol. 246, pp. 109218-109218
Open Access | Times Cited: 25
The accuracy of machine learning approaches using non-image data for the prediction of COVID-19: A meta-analysis
Kuang-Ming Kuo, Paul C. Talley, Chao-Sheng Chang
International Journal of Medical Informatics (2022) Vol. 164, pp. 104791-104791
Open Access | Times Cited: 23
Comparing machine learning algorithms to predict COVID‑19 mortality using a dataset including chest computed tomography severity score data
Seyed Salman Zakariaee, Negar Naderi, Mahdi Ebrahimi, et al.
Scientific Reports (2023) Vol. 13, Iss. 1
Open Access | Times Cited: 15
Applications of laboratory findings in the prevention, diagnosis, treatment, and monitoring of COVID-19
Zirui Meng, Shuo Guo, Yanbing Zhou, et al.
Signal Transduction and Targeted Therapy (2021) Vol. 6, Iss. 1
Open Access | Times Cited: 31
A new COVID-19 intubation prediction strategy using an intelligent feature selection and K-NN method
Zahra Asghari Varzaneh, Azam Orooji, Leila Erfannia, et al.
Informatics in Medicine Unlocked (2021) Vol. 28, pp. 100825-100825
Open Access | Times Cited: 31
COVID-19 Mortality Prediction From Deep Learning in a Large Multistate Electronic Health Record and Laboratory Information System Data Set: Algorithm Development and Validation
Saranya Sankaranarayanan, Jagadheshwar Balan, Jesse R. Walsh, et al.
Journal of Medical Internet Research (2021) Vol. 23, Iss. 9, pp. e30157-e30157
Open Access | Times Cited: 30
Artificial Intelligence in COVID-19 Management: A Systematic Review
Samaneh Mohammadi, Samaneh Mohammadi, SeyedAhmad SeyedAlinaghi, et al.
Journal of Computer Science (2023) Vol. 19, Iss. 5, pp. 554-568
Open Access | Times Cited: 13
Machine learning prognosis model based on patient-reported outcomes for chronic heart failure patients after discharge
Jing Tian, Jingjing Yan, Gangfei Han, et al.
Health and Quality of Life Outcomes (2023) Vol. 21, Iss. 1
Open Access | Times Cited: 12
Artificial intelligence in acute care: A systematic review, conceptual synthesis, and research agenda
Lea Mareen Meyer, Susan Stead, Torsten Oliver Salge, et al.
Technological Forecasting and Social Change (2024) Vol. 206, pp. 123568-123568
Open Access | Times Cited: 4
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