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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:

Comparison of different machine learning algorithms to classify patients suspected of having sepsis infection in the intensive care unit
Marsa Gholamzadeh, Hamidreza Abtahi, Reza Safdari
Informatics in Medicine Unlocked (2023) Vol. 38, pp. 101236-101236
Open Access | Times Cited: 9

Showing 9 citing articles:

Machine Learning-Based Early Prediction of Sepsis Using Electronic Health Records: A Systematic Review
Khandaker Reajul Islam, Johayra Prithula, Jaya Kumar, et al.
Journal of Clinical Medicine (2023) Vol. 12, Iss. 17, pp. 5658-5658
Open Access | Times Cited: 27
Fabrication of chitosan-coated ciprofloxacin drug nanocomposite for combating antibacterial and respiratory infection leading to sepsis
Haoguang Li, Zhiguo Su
Journal of materials research/Pratt's guide to venture capital sources (2025)
Closed Access
Sepsis in liver failure patients: Diagnostic challenges and recent advancements
Ramesh Kumar, Abhishek Kumar, Sudhir Kumar
World Journal of Critical Care Medicine (2025) Vol. 14, Iss. 2
Closed Access
Machine learning allows robust classification of lung neoplasm tissue using an electronic biopsy through minimally-invasive electrical impedance spectroscopy
Georgina Company-Se, Virginia Pajares, A Rafecas, et al.
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access
Forecasting readmission in COVID-19 patients utilizing blood biomarkers and machine learning in the Hospital-at-Home program
Maria Glòria Bonet-Papell, Georgina Company-Se, María Delgado-Capel, et al.
Frontiers in Medicine (2025) Vol. 12
Open Access
Analysis of the most influential factors affecting outcomes of lung transplant recipients: a multivariate prediction model based on UNOS Data
Marsa Gholamzadeh, Reza Safdari, Mehrnaz Asadi Gharabaghi, et al.
BMJ Open (2025) Vol. 15, Iss. 5, pp. e089796-e089796
Open Access
Early detection of sepsis using machine learning algorithms: a systematic review and network meta-analysis
Mikhail Yadgarov, Giovanni Landoni, Levan Berikashvili, et al.
Frontiers in Medicine (2024) Vol. 11
Open Access | Times Cited: 2
Designing a hybrid stack ensemble model to enhance sepsis classification using data triangulation approach
Safiya Parvin A., B. Saleena
Results in Engineering (2024) Vol. 25, pp. 103748-103748
Open Access | Times Cited: 1
Sepsis Prediction Using CNNBDLSTM and Temporal Derivatives Feature Extraction in the IoT Medical Environment
Sapiah Sakri, Shakila Basheer, Zuhaira Muhammad Zain, et al.
Computers, materials & continua/Computers, materials & continua (Print) (2024) Vol. 79, Iss. 1, pp. 1157-1185
Open Access
A Comparative Analysis of Logistic Regression and Decision Trees for Mortality Risk Prediction using Laboratory Data
Tessy Badriyah, Selvia Ferdiana Kusuma, Rosiyah Faradisa, et al.
(2024), pp. 433-438
Closed Access
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