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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 58 citing articles:

Interpretable predictive modelling of outlet temperatures in Central Alberta’s hydrothermal system using boosting-based ensemble learning incorporating Shapley Additive exPlanations (SHAP) approach
Ruyang Yu, Kai Zhang, Tao Li, et al.
Energy (2025), pp. 134738-134738
Closed Access | Times Cited: 2
Predicting structural deterioration of large-scale building clusters using snapshot data: an integrated Markov-LSTM model
Jie Liu, Guiwen Liu, Neng Wang, et al.
Building Research & Information (2025), pp. 1-17
Closed Access | Times Cited: 2
An interpretable machine learning model for predicting in-hospital mortality in ICU patients with ventilator-associated pneumonia
Jian‐Jun Wei, Heshan Cao, Mingling Peng, et al.
PLoS ONE (2025) Vol. 20, Iss. 1, pp. e0316526-e0316526
Open Access | Times Cited: 1
Decoding China’s new-type industrialization: Insights from an XGBoost-SHAP analysis
Yawen Lai, Guochao Wan, Xiaoxia Qin
Journal of Cleaner Production (2024) Vol. 478, pp. 143927-143927
Open Access | Times Cited: 6
Sex-specific Prediction of Cardiogenic Shock After Acute Coronary Syndromes: The SEX-SHOCK Score
Yifan Wang, Marianne Zeller, Vincent Auffret, et al.
European Heart Journal (2024) Vol. 45, Iss. 43, pp. 4564-4578
Open Access | Times Cited: 5
Development and validation of a machine learning‐based model of ischemic stroke risk in the Chinese elderly hypertensive population
Xiaoyue Lyu, Jie Liu, Yu Gou, et al.
View (2024)
Open Access | Times Cited: 5
Quantification of the Influencing Factors of Stand Productivity of Subtropical Natural Broadleaved Forests in Eastern China Using an Explainable Machine Learning Framework
Qun Du, Chenghao Zhu, Biyong Ji, et al.
Forests (2025) Vol. 16, Iss. 1, pp. 95-95
Open Access
Developing an interpretable machine learning model for diagnosing gout using clinical and ultrasound features
Lishan Xiao, Yizhe Zhao, Yuchen Li, et al.
European Journal of Radiology (2025) Vol. 184, pp. 111959-111959
Closed Access
Development and multi-center cross-setting validation of an explainable prediction model for sarcopenic obesity: a machine learning approach based on readily available clinical features
Rongna Lian, Huiyu Tang, Zecong Chen, et al.
Aging Clinical and Experimental Research (2025) Vol. 37, Iss. 1
Open Access
Evaluation of a novel ensemble model for preoperative ovarian cancer diagnosis: Clinical factors, O-RADS, and deep learning radiomics
Yimin Wu, Lifang Fan, Haixin Shao, et al.
Translational Oncology (2025) Vol. 54, pp. 102335-102335
Closed Access
Predicting Neoplastic Polyp in Patients With Gallbladder Polyps Using Interpretable Machine Learning Models: Retrospective Cohort Study
Zhaobin He, Sheng‐Shun Yang, Jianqiang Cao, et al.
Cancer Medicine (2025) Vol. 14, Iss. 5
Open Access
Pharmacist-led surgical medicines prescription optimization and prediction service improves patient outcomes - a machine learning based study
Xianlin Li, Xiunan Yue, Lan Zhang, et al.
Frontiers in Pharmacology (2025) Vol. 16
Open Access
Using machine learning for predicting cancer-specific mortality in bladder cancer patients undergoing radical cystectomy: a SEER-based study
Lei Dai, Kun Ye, G YAO, et al.
BMC Cancer (2025) Vol. 25, Iss. 1
Open Access
Network-based predictive models for artificial intelligence: an interpretable application of machine learning techniques in the assessment of depression in stroke patients
Wenwei Zuo, Xuelian Yang
BMC Geriatrics (2025) Vol. 25, Iss. 1
Open Access
Multi-cohort study in gastric cancer to develop CT-based radiomic models to predict pathological response to neoadjuvant immunotherapy
Ze‐Ning Huang, Haoxiang Zhang, Yuqin Sun, et al.
Journal of Translational Medicine (2025) Vol. 23, Iss. 1
Open Access
Machine learning in lymphocyte and immune biomarker analysis for childhood thyroid diseases in China
Rong Yang, Wei Li, Qi Niu, et al.
BMC Pediatrics (2025) Vol. 25, Iss. 1
Open Access
Identification of key feature variables and prediction of harmful algal blooms in a water diversion lake based on interpretable machine learning
Yundong Wu, Bo Xian, Xiaowei Xiang, et al.
Environmental Research (2025), pp. 121491-121491
Closed Access
Web-Based Explainable Machine Learning-Based Drug Surveillance for Predicting Sunitinib- and Sorafenib-Associated Thyroid Dysfunction: Model Development and Validation Study
Fan-Ying Chan, Y. Y. Ku, Wen‐Nung Lie, et al.
JMIR Formative Research (2025) Vol. 9, pp. e67767-e67767
Open Access
Interpretable Machine Learning Model for Predicting Anastomotic Leak After Esophageal Cancer Surgery via LightGBM
Xiaodong Yang, Fulin Dou, Guanfeng Tang, et al.
(2025)
Closed Access
Noninvasive Oral Hyperspectral Imaging–Driven Digital Diagnosis of Heart Failure With Preserved Ejection Fraction: Model Development and Validation Study
Xiaomeng Yang, Zeyan Li, Lei Lei, et al.
Journal of Medical Internet Research (2025) Vol. 27, pp. e67256-e67256
Open Access
Serum magnesium levels and the risk of acute kidney injury in ICU patients with acute pancreatitis: A MIMIC-IV cohort study
Xue-hong Zhou, Shijiu Jin, Dong Wu, et al.
Science Progress (2025) Vol. 108, Iss. 1
Open Access
Development and Internal-External Validation of Interpretable Machine Learning Models to Predict the Risk of Postoperative Complications after Cranioplasty: A Multicenter, Cohort Study
Wen Li, Bao Wang, T. Li, et al.
(2025)
Closed Access
Research on the development of an intelligent prediction model for blood pressure variability during hemodialysis
Zhijian Ren, Minqiao Zhang, Pingping Wang, et al.
BMC Nephrology (2025) Vol. 26, Iss. 1
Open Access
Leveraging Large Language Models for Predicting Postoperative Acute Kidney Injury in Elderly Patient
Hanfei Zhu, Ruojiang Wang, Jun Qian, et al.
BME Frontiers (2025) Vol. 6
Open Access
An interpretable machine learning-assisted diagnostic model for Kawasaki disease in children
Mengyu Duan, Zhimin Geng, Lichao Gao, et al.
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access
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