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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.

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Showing 1-25 of 34 citing articles:

Unveiling the Influence of AI Predictive Analytics on Patient Outcomes: A Comprehensive Narrative Review
Diny Dixon, Hina Sattar, Natalia Moros, et al.
Cureus (2024)
Open Access | Times Cited: 46
Use of machine learning algorithms to construct models of symptom burden cluster risk in breast cancer patients undergoing chemotherapy
Qingmei Huang, Yang Yang, Zhaohui Geng, et al.
Supportive Care in Cancer (2025) Vol. 33, Iss. 3
Open Access | Times Cited: 1
Prediction of successful weaning from renal replacement therapy in critically ill patients based on machine learning
Qiqiang Liang, Xin Xu, Shuo Ding, et al.
Renal Failure (2024) Vol. 46, Iss. 1
Open Access | Times Cited: 4
Machine learning for prediction of acute kidney injury in patients diagnosed with sepsis in critical care
Jianshan Shi, Huirui Han, Song Chen, et al.
PLoS ONE (2024) Vol. 19, Iss. 4, pp. e0301014-e0301014
Open Access | Times Cited: 4
Development and validation of a nomogram for predicting in-hospital mortality of elderly patients with persistent sepsis-associated acute kidney injury in intensive care units: a retrospective cohort study using the MIMIC-IV database
Wei Jiang, Chuanqing Zhang, Jiangquan Yu, et al.
BMJ Open (2023) Vol. 13, Iss. 3, pp. e069824-e069824
Open Access | Times Cited: 10
Prediction of Acute Kidney Injury for Critically Ill Cardiogenic Shock Patients with Machine Learning Algorithms
Xiaofei Zhang, Yan Q. Xiong, Huilan Liu, et al.
International Journal of General Medicine (2025) Vol. Volume 18, pp. 33-42
Open Access
The new era of risk assessment for hypertension in pregnancy: From clinical to biochemical markers in a comprehensive predictive model
Liju Nie, Ziyu Zhang, Qi Yao, et al.
Taiwanese Journal of Obstetrics and Gynecology (2025) Vol. 64, Iss. 2, pp. 253-264
Open Access
Prediction Model for Risk of Death in Elderly Critically Ill Patients with Kidney Failure
Jinping Zeng, Feng Ye, Jiaolan Du, et al.
Medicina (2025) Vol. 61, Iss. 4, pp. 640-640
Open Access
Comparison between logistic regression and machine learning algorithms on prediction of noise-induced hearing loss and investigation of SNP loci
Jie Lü, Xiqun Lu, Yixiao Wang, et al.
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access
Prediction of endoscopic restenosis after endoscopic balloon dilation in patients with Crohn’s disease: a machine learning approach
Tao Su, Yi Lü, Nan Lan, et al.
Surgical Endoscopy (2025)
Closed Access
KIM-1, IL-18, and NGAL, in the Machine Learning Prediction of Kidney Injury among Children Undergoing Hematopoietic Stem Cell Transplantation—A Pilot Study
Kinga Musiał, Jakub Stojanowski, Justyna Miśkiewicz‐Bujna, et al.
International Journal of Molecular Sciences (2023) Vol. 24, Iss. 21, pp. 15791-15791
Open Access | Times Cited: 9
Prediction of tumor lysis syndrome in childhood acute lymphoblastic leukemia based on machine learning models: a retrospective study
Yao Xiao, Li Xiao, Yang Zhang, et al.
Frontiers in Oncology (2024) Vol. 14
Open Access | Times Cited: 3
Predicting the Severity and Discharge Prognosis of Traumatic Brain Injury Based on Intracranial Pressure Data Using Machine Learning Algorithms
Jun Zhu, Yingchi Shan, Yihua Li, et al.
World Neurosurgery (2024) Vol. 185, pp. e1348-e1360
Closed Access | Times Cited: 3
A clinical score to predict recovery in end-stage kidney disease due to acute kidney injury
Silvi Shah, Jia Hwei Ng, Anthony C. Leonard, et al.
Clinical Kidney Journal (2024) Vol. 17, Iss. 5
Open Access | Times Cited: 3
Machine learning-based models for prediction of the risk of stroke in coronary artery disease patients receiving coronary revascularization
Lu‐Lu Lin, Ding Li, Zhong-guo Fu, et al.
PLoS ONE (2024) Vol. 19, Iss. 2, pp. e0296402-e0296402
Open Access | Times Cited: 2
Assessment of Risk Factors for Acute Kidney Injury with Machine Learning Tools in Children Undergoing Hematopoietic Stem Cell Transplantation
Kinga Musiał, Jakub Stojanowski, Monika Augustynowicz, et al.
Journal of Clinical Medicine (2024) Vol. 13, Iss. 8, pp. 2266-2266
Open Access | Times Cited: 2
A machine learning-based approach for predicting renal function recovery in general ward patients with acute kidney injury
Namjun Cho, Inyong Jeong, Y.H. Kim, et al.
Kidney Research and Clinical Practice (2024) Vol. 43, Iss. 4, pp. 538-547
Open Access | Times Cited: 2
Construction and evaluation of a mortality prediction model for patients with acute kidney injury undergoing continuous renal replacement therapy based on machine learning algorithms
Yongbin Wang, Xu Sun, Jianhong Lu, et al.
Annals of Medicine (2024) Vol. 56, Iss. 1
Open Access | Times Cited: 2
Ensemble Learning, Deep Learning-Based and Molecular Descriptor-Based Quantitative Structure–Activity Relationships
Yasunari Matsuzaka, Yoshihiro Uesawa
Molecules (2023) Vol. 28, Iss. 5, pp. 2410-2410
Open Access | Times Cited: 6
Random forest-based prediction of intracranial hypertension in patients with traumatic brain injury
Jun Zhu, Yingchi Shan, Yihua Li, et al.
Intensive Care Medicine Experimental (2024) Vol. 12, Iss. 1
Open Access | Times Cited: 2
Machine learning-based prediction model of acute kidney injury in patients with acute respiratory distress syndrome
Shuxing Wei, Yongsheng Zhang, Hongmeng Dong, et al.
BMC Pulmonary Medicine (2023) Vol. 23, Iss. 1
Open Access | Times Cited: 5
Toxicity evaluation of processing Evodiae fructus based on intestinal microbiota
Xuejuan Liang, Jing Liu, Jiaxin Di, et al.
Frontiers in Microbiology (2024) Vol. 15
Open Access | Times Cited: 1
Association Between IV Contrast Media Exposure and Acute Kidney Injury in Patients Requiring Emergency Admission: A Nationwide Observational Study in Japan
Ryo Hisamune, Kazuma Yamakawa, Yutaka Umemura, et al.
Critical Care Explorations (2024) Vol. 6, Iss. 9, pp. e1142-e1142
Open Access | Times Cited: 1
Acute Kidney Injury Prognosis Prediction Using Machine Learning Methods: A Systematic Review
Yu Lin, Tongyang Shi, Guilan Kong
Kidney Medicine (2024) Vol. 7, Iss. 1, pp. 100936-100936
Open Access | Times Cited: 1
Distinguishing Malignant Melanoma and Benign Nevus of Human Skin by Retardance Using Mueller Matrix Imaging Polarimeter
Wen’ai Wang, Guoqiang Chen, Yanqiu Li
Applied Sciences (2023) Vol. 13, Iss. 11, pp. 6514-6514
Open Access | Times Cited: 2
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