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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:

Using Machine Learning to Predict Antimicrobial Resistance of Acinetobacter Baumannii, Klebsiella Pneumoniae and Pseudomonas Aeruginosa Strains
Georgios Feretzakis, Aikaterini Sakagianni, Evangelos Loupelis, et al.
Studies in health technology and informatics (2021)
Open Access | Times Cited: 21

Showing 21 citing articles:

Using Machine Learning to Predict Antimicrobial Resistance―A Literature Review
Aikaterini Sakagianni, Christina Koufopoulou, Georgios Feretzakis, et al.
Antibiotics (2023) Vol. 12, Iss. 3, pp. 452-452
Open Access | Times Cited: 65
Current and Future Technologies for the Detection of Antibiotic-Resistant Bacteria
Dina Yamin, Vuk Uskoković, Abubakar Muhammad Wakil, et al.
Diagnostics (2023) Vol. 13, Iss. 20, pp. 3246-3246
Open Access | Times Cited: 42
Machine learning in predicting antimicrobial resistance: a systematic review and meta-analysis
Rui Tang, Rui Luo, Shiwei Tang, et al.
International Journal of Antimicrobial Agents (2022) Vol. 60, Iss. 5-6, pp. 106684-106684
Closed Access | Times Cited: 34
Machine learning to predict antimicrobial resistance: future applications in clinical practice?
Yousra Kherabi, Michaël Thy, Donia Bouzid, et al.
Infectious Diseases Now (2024) Vol. 54, Iss. 3, pp. 104864-104864
Closed Access | Times Cited: 6
Artificial intelligence-driven approaches in antibiotic stewardship programs and optimizing prescription practices: A systematic review
Hamid Harandi, Maryam Shafaati, Mohammadreza Salehi, et al.
Artificial Intelligence in Medicine (2025), pp. 103089-103089
Closed Access
Early prediction of carbapenem-resistant Gram-negative bacterial carriage in intensive care units using machine learning
Qiqiang Liang, Qinyu Zhao, Xin Xu, et al.
Journal of Global Antimicrobial Resistance (2022) Vol. 29, pp. 225-231
Open Access | Times Cited: 19
Exploring the synergy of artificial intelligence in microbiology: Advancements, challenges, and future prospects
P Mohseni, Abozar Ghorbani
Deleted Journal (2024) Vol. 1, pp. 100005-100005
Open Access | Times Cited: 2
Predicting Antibiotic Resistance in ICUs Patients by Applying Machine Learning in Vietnam
Viet Tran Quoc, Dung Nguyen Thi Ngoc, Trung Nguyen Hoang, et al.
Infection and Drug Resistance (2023) Vol. Volume 16, pp. 5535-5546
Open Access | Times Cited: 5
Development and validation of machine learning-based models for predicting healthcare-associated bacterial/fungal infections among COVID-19 inpatients: a retrospective cohort study
Min Wang, Wenjuan Li, Hui Wang, et al.
Antimicrobial Resistance and Infection Control (2024) Vol. 13, Iss. 1
Open Access | Times Cited: 1
Artificial Intelligence-Clinical Decision Support System in Infectious Disease Control: Combatting Multidrug-Resistant Klebsiella pneumoniae with Machine Learning
Ming-Jr Jian, Tai-Han Lin, Hsing-Yi Chung, et al.
Infection and Drug Resistance (2024) Vol. Volume 17, pp. 2899-2912
Open Access | Times Cited: 1
Retrospective validation study of a machine learning-based software for empirical and organism-targeted antibiotic therapy selection
Maria Isabel Tejeda, Javier Fernández, Pablo Valledor, et al.
Antimicrobial Agents and Chemotherapy (2024) Vol. 68, Iss. 10
Open Access | Times Cited: 1
A novel approach to antimicrobial resistance: Machine learning predictions for carbapenem-resistant Klebsiella in intensive care units
Volkan Alparslan, Özgür Güler, B İnner, et al.
International Journal of Medical Informatics (2024) Vol. 195, pp. 105751-105751
Closed Access | Times Cited: 1
Machine Learning Prediction of Resistance to Subinhibitory Antimicrobial Concentrations from Escherichia coli Genomes
Sam Benkwitz-Bedford, Martin Palm, Talip Yasir Demirtas, et al.
mSystems (2021) Vol. 6, Iss. 4
Open Access | Times Cited: 11
Machine learning for identifying resistance features of Klebsiella pneumoniae using whole-genome sequence single nucleotide polymorphisms
Wenjia Liu, Nanjiao Ying, Qiusi Mo, et al.
Journal of Medical Microbiology (2021) Vol. 70, Iss. 11
Closed Access | Times Cited: 6
Discovering Association Rules in Antimicrobial Resistance in Intensive Care Unit
Aikaterini Sakagianni, Georgios Feretzakis, Dimitris Kalles, et al.
Studies in health technology and informatics (2022)
Open Access | Times Cited: 4
Development and application of a risk nomogram for the prediction of risk of carbapenem-resistant Acinetobacter baumannii infections in neuro-intensive care unit: a mixed method study
Yuping Li, Xianru Gao, Haiqing Diao, et al.
Antimicrobial Resistance and Infection Control (2024) Vol. 13, Iss. 1
Open Access
Machine learning-based antibiotic resistance prediction models: An updated systematic review and meta-analysis
Guodong Lv, Yuntao Wang
Technology and Health Care (2024), pp. 1-18
Closed Access
Machine learning risk prediction model for bloodstream infections related to totally implantable venous access ports in patients with cancer
Fan Wang, Yanyi Zhu, Lijuan Wang, et al.
Asia-Pacific Journal of Oncology Nursing (2024) Vol. 11, Iss. 8, pp. 100546-100546
Open Access
Proof of concept study on early forecasting of antimicrobial resistance in hospitalized patients using machine learning and simple bacterial ecology data
Raquel Ureña, Sabine Camiade, Yasser Baalla, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access
PerSceptoMed 1.0: An advanced machine learning model for demographic-based antibiotic susceptibility prediction in Pseudomonas aeruginosa infections
Sweta Padma Routray, Saswati Mahapatra, Debasish Swapnesh Kumar Nayak, et al.
Engineering Applications of Artificial Intelligence (2024) Vol. 141, pp. 109773-109773
Closed Access
Bacterial Infection of Burn Patients and Their Drug-resistance in South Jiangsu China During 2012-2016
Jie Zhu, Xingrong Wu, Kewei Wang, et al.
International Journal of Clinical and Experimental Medicine Research (2024) Vol. 8, Iss. 2, pp. 232-238
Open Access
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