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:
Prediction of the risk of developing end-stage renal diseases in newly diagnosed type 2 diabetes mellitus using artificial intelligence algorithms
Shuo‐Ming Ou, Ming‐Tsun Tsai, Kuo‐Hua Lee, et al.
BioData Mining (2023) Vol. 16, Iss. 1
Open Access | Times Cited: 23
Shuo‐Ming Ou, Ming‐Tsun Tsai, Kuo‐Hua Lee, et al.
BioData Mining (2023) Vol. 16, Iss. 1
Open Access | Times Cited: 23
Showing 23 citing articles:
Excessive Initial Renal Function Decline Following Sodium-Glucose Cotransporter-2 Inhibitor Treatment Predicts Major Adverse Cardiorenal Outcomes
Chi‐Yu Chen, Shao‐Sung Huang, Shuo-Ming Ou, et al.
Mayo Clinic Proceedings (2025)
Closed Access | Times Cited: 1
Chi‐Yu Chen, Shao‐Sung Huang, Shuo-Ming Ou, et al.
Mayo Clinic Proceedings (2025)
Closed Access | Times Cited: 1
Machine Learning Models for Prediction of Diabetic Microvascular Complications
Sarah Kanbour, Catharine Harris, Benjamin Lalani, et al.
Journal of Diabetes Science and Technology (2024) Vol. 18, Iss. 2, pp. 273-286
Closed Access | Times Cited: 5
Sarah Kanbour, Catharine Harris, Benjamin Lalani, et al.
Journal of Diabetes Science and Technology (2024) Vol. 18, Iss. 2, pp. 273-286
Closed Access | Times Cited: 5
Predictive model and risk analysis for peripheral vascular disease in type 2 diabetes mellitus patients using machine learning and shapley additive explanation
Lianhua Liu, Bo Bi, Li Juan Cao, et al.
Frontiers in Endocrinology (2024) Vol. 15
Open Access | Times Cited: 5
Lianhua Liu, Bo Bi, Li Juan Cao, et al.
Frontiers in Endocrinology (2024) Vol. 15
Open Access | Times Cited: 5
Automated biomedical measurements analysis: Innovative models based on machine learning for predicting laboratory results in nephrology
Dawid Pawuś, Tomasz Porażko, Szczepan Paszkiel
Expert Systems with Applications (2025), pp. 126568-126568
Closed Access
Dawid Pawuś, Tomasz Porażko, Szczepan Paszkiel
Expert Systems with Applications (2025), pp. 126568-126568
Closed Access
Automation and Decision Support in Nephrology: An Expert System Based on AI and ML for the Assessment, Treatment, and Management of Focal Segmental Glomerulosclerosis
Dawid Pawuś, Tomasz Porażko, Szczepan Paszkiel
Applied Sciences (2025) Vol. 15, Iss. 3, pp. 1044-1044
Open Access
Dawid Pawuś, Tomasz Porażko, Szczepan Paszkiel
Applied Sciences (2025) Vol. 15, Iss. 3, pp. 1044-1044
Open Access
Development and nursing application of kidney disease prediction models based on machine learning
Yan Zhang, Hui Gao
Computer Methods in Biomechanics & Biomedical Engineering (2025), pp. 1-12
Closed Access
Yan Zhang, Hui Gao
Computer Methods in Biomechanics & Biomedical Engineering (2025), pp. 1-12
Closed Access
A SuperLearner approach for predicting diabetic kidney disease upon the initial diagnosis of T2DM in hospital
Xiaomeng Lin, Chao Liu, Huaiyu Wang, et al.
BMC Medical Informatics and Decision Making (2025) Vol. 25, Iss. 1
Open Access
Xiaomeng Lin, Chao Liu, Huaiyu Wang, et al.
BMC Medical Informatics and Decision Making (2025) Vol. 25, Iss. 1
Open Access
Predicting three-month fasting blood glucose and glycated hemoglobin changes in patients with type 2 diabetes mellitus based on multiple machine learning algorithms
Tao Xue, Min Jiang, Yumeng Liu, et al.
Scientific Reports (2023) Vol. 13, Iss. 1
Open Access | Times Cited: 12
Tao Xue, Min Jiang, Yumeng Liu, et al.
Scientific Reports (2023) Vol. 13, Iss. 1
Open Access | Times Cited: 12
A survey of explainable artificial intelligence in healthcare: Concepts, applications, and challenges
Ibomoiye Domor Mienye, George Obaido, Nobert Jere, et al.
Informatics in Medicine Unlocked (2024), pp. 101587-101587
Open Access | Times Cited: 2
Ibomoiye Domor Mienye, George Obaido, Nobert Jere, et al.
Informatics in Medicine Unlocked (2024), pp. 101587-101587
Open Access | Times Cited: 2
Value of radiomics-based two-dimensional ultrasound for diagnosing early diabetic nephropathy
Xuee Su, Lin Shu, Yinqiong Huang
Scientific Reports (2023) Vol. 13, Iss. 1
Open Access | Times Cited: 5
Xuee Su, Lin Shu, Yinqiong Huang
Scientific Reports (2023) Vol. 13, Iss. 1
Open Access | Times Cited: 5
User-cloud-based ensemble framework for type-2 diabetes prediction with diet plan suggestion
Ganga Prabhakar, Vaishnavi Reddy Chintala, Trishala Reddy, et al.
e-Prime - Advances in Electrical Engineering Electronics and Energy (2024) Vol. 7, pp. 100423-100423
Open Access | Times Cited: 1
Ganga Prabhakar, Vaishnavi Reddy Chintala, Trishala Reddy, et al.
e-Prime - Advances in Electrical Engineering Electronics and Energy (2024) Vol. 7, pp. 100423-100423
Open Access | Times Cited: 1
A knowledge-based decision support system to support family doctors in personalizing type-2 diabetes mellitus medical nutrition therapy
Daniele Spoladore, Francesco Stella, Martina Tosi, et al.
Computers in Biology and Medicine (2024) Vol. 180, pp. 109001-109001
Open Access | Times Cited: 1
Daniele Spoladore, Francesco Stella, Martina Tosi, et al.
Computers in Biology and Medicine (2024) Vol. 180, pp. 109001-109001
Open Access | Times Cited: 1
Unveiling the utility of artificial intelligence for prediction, diagnosis, and progression of diabetic kidney disease: an evidence-based systematic review and meta-analysis
Sagar Dholariya, Siddhartha Dutta, Amit Sonagra, et al.
Current Medical Research and Opinion (2024), pp. 1-31
Closed Access | Times Cited: 1
Sagar Dholariya, Siddhartha Dutta, Amit Sonagra, et al.
Current Medical Research and Opinion (2024), pp. 1-31
Closed Access | Times Cited: 1
Improved Survival Analyses Based on Characterized Time-Dependent Covariates to Predict Individual Chronic Kidney Disease Progression
Chen-Mao Liao, Chuan‐Tsung Su, Hao-Che Huang, et al.
Biomedicines (2023) Vol. 11, Iss. 6, pp. 1664-1664
Open Access | Times Cited: 3
Chen-Mao Liao, Chuan‐Tsung Su, Hao-Che Huang, et al.
Biomedicines (2023) Vol. 11, Iss. 6, pp. 1664-1664
Open Access | Times Cited: 3
Optimizing age-related hearing risk predictions: an advanced machine learning integration with HHIE-S
Tzong‐Hann Yang, Yu-Fu Chen, Yen‐Fu Cheng, et al.
BioData Mining (2023) Vol. 16, Iss. 1
Open Access | Times Cited: 3
Tzong‐Hann Yang, Yu-Fu Chen, Yen‐Fu Cheng, et al.
BioData Mining (2023) Vol. 16, Iss. 1
Open Access | Times Cited: 3
Machine learning prediction models for diabetic kidney disease: systematic review and meta-analysis
Lianqin Chen, Xian Shao, Pei Yu
Endocrine (2023) Vol. 84, Iss. 3, pp. 890-902
Closed Access | Times Cited: 2
Lianqin Chen, Xian Shao, Pei Yu
Endocrine (2023) Vol. 84, Iss. 3, pp. 890-902
Closed Access | Times Cited: 2
A SuperLearner approach for predicting diabetic kidney disease upon the initial diagnosis of T2DM in hospital
Xiaomeng Lin, Chao Liu, Huaiyu Wang, et al.
Research Square (Research Square) (2024)
Open Access
Xiaomeng Lin, Chao Liu, Huaiyu Wang, et al.
Research Square (Research Square) (2024)
Open Access
Kidney Disease Prediction using ML techniques
Bishnu Pada Saha, Satya Ranjan Dash, Nikunj Kishore Rout, et al.
(2024) Vol. 38, pp. 314-318
Closed Access
Bishnu Pada Saha, Satya Ranjan Dash, Nikunj Kishore Rout, et al.
(2024) Vol. 38, pp. 314-318
Closed Access
Setting Ranges in Potential Biomarkers for Type 2 Diabetes Mellitus Patients Early Detection By Sex—An Approach with Machine Learning Algorithms
Jorge A. Morgan-Benita, José M. Celaya-Padilla, Huizilopoztli Luna-García, et al.
Diagnostics (2024) Vol. 14, Iss. 15, pp. 1623-1623
Open Access
Jorge A. Morgan-Benita, José M. Celaya-Padilla, Huizilopoztli Luna-García, et al.
Diagnostics (2024) Vol. 14, Iss. 15, pp. 1623-1623
Open Access
Safety evaluation of bi‐layered allogenic keratinocyte and fibroblast skin substitute for diabetic foot ulcers—SAFESKIN ‐DFU : A Phase 1 clinical trial
Shayan Farzanbakhsh, Mohammad Reza Amini, Hoda Madani, et al.
Diabetes Obesity and Metabolism (2024) Vol. 26, Iss. 11, pp. 5078-5086
Closed Access
Shayan Farzanbakhsh, Mohammad Reza Amini, Hoda Madani, et al.
Diabetes Obesity and Metabolism (2024) Vol. 26, Iss. 11, pp. 5078-5086
Closed Access
A Survey of Explainable Artificial Intelligence in Healthcare: Concepts, Applications, and Challenges
Ibomoiye Domor Mienye, George Obaido, Nobert Jere, et al.
(2024)
Open Access
Ibomoiye Domor Mienye, George Obaido, Nobert Jere, et al.
(2024)
Open Access
Risk factors for developing osteoporosis in diabetic kidney disease and its correlation with calcium-phosphorus metabolism, FGF23, and Klotho
Fan Yang, Yan Wu, Wei Zhang
World Journal of Diabetes (2024) Vol. 16, Iss. 1
Closed Access
Fan Yang, Yan Wu, Wei Zhang
World Journal of Diabetes (2024) Vol. 16, Iss. 1
Closed Access
Using artificial intelligence algorithms to predict the overall survival of hemodialysis patients during the COVID-19 pandemic: A prospective cohort study
Shaoyu Tang, Tz‐Heng Chen, Ko‐Lin Kuo, et al.
Journal of the Chinese Medical Association (2023) Vol. 86, Iss. 11, pp. 1020-1027
Open Access | Times Cited: 1
Shaoyu Tang, Tz‐Heng Chen, Ko‐Lin Kuo, et al.
Journal of the Chinese Medical Association (2023) Vol. 86, Iss. 11, pp. 1020-1027
Open Access | Times Cited: 1
Identifying Biomarkers for Diabetic Kidney Disease Using GraphSAGE Neural Network
Sesugh Gabriel Abenga, Kehinde Seyi Olalekan, Francis Akogwu Alu, et al.
Journal of Computer and Communications (2023) Vol. 11, Iss. 10, pp. 51-63
Open Access | Times Cited: 1
Sesugh Gabriel Abenga, Kehinde Seyi Olalekan, Francis Akogwu Alu, et al.
Journal of Computer and Communications (2023) Vol. 11, Iss. 10, pp. 51-63
Open Access | Times Cited: 1
A SuperLearner approach to predicting diabetic kidney disease upon the initial diagnosis of T2DM in hospital
Xiaomeng Lin, Chao Liu, Huaiyu Wang, et al.
Research Square (Research Square) (2023)
Open Access
Xiaomeng Lin, Chao Liu, Huaiyu Wang, et al.
Research Square (Research Square) (2023)
Open Access
