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:
Artificial intelligence enabled applications in kidney disease
Sheetal Chaudhuri, Andrew Long, Hanjie Zhang, et al.
Seminars in Dialysis (2020) Vol. 34, Iss. 1, pp. 5-16
Open Access | Times Cited: 35
Sheetal Chaudhuri, Andrew Long, Hanjie Zhang, et al.
Seminars in Dialysis (2020) Vol. 34, Iss. 1, pp. 5-16
Open Access | Times Cited: 35
Showing 1-25 of 35 citing articles:
AI-Powered Renal Diet Support: Performance of ChatGPT, Bard AI, and Bing Chat
Ahmad Qarajeh, Supawit Tangpanithandee, Charat Thongprayoon, et al.
Clinics and Practice (2023) Vol. 13, Iss. 5, pp. 1160-1172
Open Access | Times Cited: 47
Ahmad Qarajeh, Supawit Tangpanithandee, Charat Thongprayoon, et al.
Clinics and Practice (2023) Vol. 13, Iss. 5, pp. 1160-1172
Open Access | Times Cited: 47
Artificial Intelligence in Kidney Disease: A Comprehensive Study and Directions for Future Research
Chieh-Chen Wu, Md. Mohaimenul Islam, Tahmina Nasrin Poly, et al.
Diagnostics (2024) Vol. 14, Iss. 4, pp. 397-397
Open Access | Times Cited: 9
Chieh-Chen Wu, Md. Mohaimenul Islam, Tahmina Nasrin Poly, et al.
Diagnostics (2024) Vol. 14, Iss. 4, pp. 397-397
Open Access | Times Cited: 9
Aristolochic acid I as an emerging biogenic contaminant involved in chronic kidney diseases: A comprehensive review on exposure pathways, environmental health issues and future challenges
Alexandra Teodora Lukinich-Gruia, Joëlle Nortier, Nikola M. Pavlović, et al.
Chemosphere (2022) Vol. 297, pp. 134111-134111
Open Access | Times Cited: 28
Alexandra Teodora Lukinich-Gruia, Joëlle Nortier, Nikola M. Pavlović, et al.
Chemosphere (2022) Vol. 297, pp. 134111-134111
Open Access | Times Cited: 28
Advancing health care via artificial intelligence: From concept to clinic
Grandhi Sandeep Ganesh, Aravinda Sai Kolusu, Prasad Konduri, et al.
European Journal of Pharmacology (2022) Vol. 934, pp. 175320-175320
Closed Access | Times Cited: 24
Grandhi Sandeep Ganesh, Aravinda Sai Kolusu, Prasad Konduri, et al.
European Journal of Pharmacology (2022) Vol. 934, pp. 175320-175320
Closed Access | Times Cited: 24
Leveraging Artificial Intelligence to Predict and Manage Complications in Patients With Multimorbidity: A Literature Review
Sai Praneeth Chaparala, Kaustubh Pathak, Raman Dugyala, et al.
Cureus (2025)
Open Access
Sai Praneeth Chaparala, Kaustubh Pathak, Raman Dugyala, et al.
Cureus (2025)
Open Access
Advancing Cardiovascular, Kidney, and Metabolic Medicine: A Narrative Review of Insights and Innovations for the Future
Kevin Fernando, Derek Connolly, Eimear Darcy, et al.
Diabetes Therapy (2025)
Open Access
Kevin Fernando, Derek Connolly, Eimear Darcy, et al.
Diabetes Therapy (2025)
Open Access
A population based optimization of convolutional neural networks for chronic kidney disease prediction
M. Priyadharshini, V. Murugesh, G. V. Samkumar, et al.
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access
M. Priyadharshini, V. Murugesh, G. V. Samkumar, et al.
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access
Application of artificial intelligence in renal disease
Lijing Yao, Hengyuan Zhang, Mengqin Zhang, et al.
Clinical eHealth (2021) Vol. 4, pp. 54-61
Open Access | Times Cited: 24
Lijing Yao, Hengyuan Zhang, Mengqin Zhang, et al.
Clinical eHealth (2021) Vol. 4, pp. 54-61
Open Access | Times Cited: 24
Prediction models used in the progression of chronic kidney disease: A scoping review
David Lim, James Boyd, Elizabeth Thomas, et al.
PLoS ONE (2022) Vol. 17, Iss. 7, pp. e0271619-e0271619
Open Access | Times Cited: 14
David Lim, James Boyd, Elizabeth Thomas, et al.
PLoS ONE (2022) Vol. 17, Iss. 7, pp. e0271619-e0271619
Open Access | Times Cited: 14
Artificial neural networks for adaptive control of profiled haemodialysis in patients with renal insufficiency
J. Fernández de Cañete, M. Roman, Raoul Santiago
Expert Systems with Applications (2023) Vol. 232, pp. 120775-120775
Closed Access | Times Cited: 6
J. Fernández de Cañete, M. Roman, Raoul Santiago
Expert Systems with Applications (2023) Vol. 232, pp. 120775-120775
Closed Access | Times Cited: 6
Integrating Innovation in Healthcare: The Evolution of “CURA’s” AI-Driven Virtual Wards for Enhanced Diabetes and Kidney Disease Monitoring
Mohammed Aljaafari, Shorouk E. El-deep, Amr A. Abohany, et al.
IEEE Access (2024) Vol. 12, pp. 126389-126414
Open Access | Times Cited: 2
Mohammed Aljaafari, Shorouk E. El-deep, Amr A. Abohany, et al.
IEEE Access (2024) Vol. 12, pp. 126389-126414
Open Access | Times Cited: 2
A Comprehensive Review of Biomarkers for Chronic Kidney Disease in Older Individuals: Current Perspectives and Future Directions
Aman Gupta, Tushar Sontakke, Sourya Acharya, et al.
Cureus (2024)
Open Access | Times Cited: 2
Aman Gupta, Tushar Sontakke, Sourya Acharya, et al.
Cureus (2024)
Open Access | Times Cited: 2
A Simpler Machine Learning Model for Acute Kidney Injury Risk Stratification in Hospitalized Patients
Yirui Hu, Kunpeng Liu, Kevin Ho, et al.
Journal of Clinical Medicine (2022) Vol. 11, Iss. 19, pp. 5688-5688
Open Access | Times Cited: 8
Yirui Hu, Kunpeng Liu, Kevin Ho, et al.
Journal of Clinical Medicine (2022) Vol. 11, Iss. 19, pp. 5688-5688
Open Access | Times Cited: 8
Artificial intelligence and machine learning in peritoneal dialysis: a systematic review of clinical outcomes and predictive modeling
Muhammad Muaz Mushtaq, Maham Mushtaq, Husnain Ali, et al.
International Urology and Nephrology (2024) Vol. 56, Iss. 12, pp. 3857-3867
Closed Access | Times Cited: 1
Muhammad Muaz Mushtaq, Maham Mushtaq, Husnain Ali, et al.
International Urology and Nephrology (2024) Vol. 56, Iss. 12, pp. 3857-3867
Closed Access | Times Cited: 1
Predicting early mortality in hemodialysis patients: a deep learning approach using a nationwide prospective cohort in South Korea
Junhyug Noh, Sun Young Park, Wonho Bae, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 1
Junhyug Noh, Sun Young Park, Wonho Bae, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 1
Predictors of shorter- and longer-term mortality after COVID-19 presentation among dialysis patients: parallel use of machine learning models in Latin and North American countries
Adrián Guinsburg, Yue Jiao, María Inés Díaz Bessone, et al.
BMC Nephrology (2022) Vol. 23, Iss. 1
Open Access | Times Cited: 6
Adrián Guinsburg, Yue Jiao, María Inés Díaz Bessone, et al.
BMC Nephrology (2022) Vol. 23, Iss. 1
Open Access | Times Cited: 6
Kidney Disease Detection and Identification Using Artificial Intelligence
Tanya Saraswat, Savita Pathak, Sanya Sachdeva, et al.
2022 12th International Conference on Cloud Computing, Data Science & Engineering (Confluence) (2023), pp. 537-543
Closed Access | Times Cited: 3
Tanya Saraswat, Savita Pathak, Sanya Sachdeva, et al.
2022 12th International Conference on Cloud Computing, Data Science & Engineering (Confluence) (2023), pp. 537-543
Closed Access | Times Cited: 3
Artificial Intelligence Applications in Decision Making for Disease Management
Mohammadhiwa Abdekhoda, Fatemeh Ranjbaran
Research Square (Research Square) (2023)
Open Access | Times Cited: 2
Mohammadhiwa Abdekhoda, Fatemeh Ranjbaran
Research Square (Research Square) (2023)
Open Access | Times Cited: 2
Predicting mortality risk in dialysis: Assessment of risk factors using traditional and advanced modeling techniques within the Monitoring Dialysis Outcomes initiative
Sheetal Chaudhuri, John W. Larkin, Murilo Guedes, et al.
Hemodialysis International (2022) Vol. 27, Iss. 1, pp. 62-73
Open Access | Times Cited: 4
Sheetal Chaudhuri, John W. Larkin, Murilo Guedes, et al.
Hemodialysis International (2022) Vol. 27, Iss. 1, pp. 62-73
Open Access | Times Cited: 4
The Impact of Machine Learning on Chronic Kidney Disease: Analysis and Insights
K. P. Swain, Rabindra Kumar Nayak, Ayusee Swain, et al.
(2024), pp. 121-148
Closed Access
K. P. Swain, Rabindra Kumar Nayak, Ayusee Swain, et al.
(2024), pp. 121-148
Closed Access
Synthetic data as an investigative tool in hypertension and renal diseases research
Aleena Jamal, Som Singh, Fawad Qureshi
World Journal of Methodology (2024) Vol. 15, Iss. 1
Closed Access
Aleena Jamal, Som Singh, Fawad Qureshi
World Journal of Methodology (2024) Vol. 15, Iss. 1
Closed Access
Artificial intelligence in the prognosis of Chronic Kidney Disease
Chaiwe Mumba, Vivek Kumar Garg
AIP conference proceedings (2024) Vol. 3232, pp. 050004-050004
Closed Access
Chaiwe Mumba, Vivek Kumar Garg
AIP conference proceedings (2024) Vol. 3232, pp. 050004-050004
Closed Access
A Conceptual IoT Framework Based on Anova-F Feature Selection for Chronic Kidney Disease Detection Using Deep Learning Approach
M Ali, Saiful Islam, Mohammed Nasir Uddin, et al.
Intelligence-Based Medicine (2024), pp. 100170-100170
Open Access
M Ali, Saiful Islam, Mohammed Nasir Uddin, et al.
Intelligence-Based Medicine (2024), pp. 100170-100170
Open Access
Proceedings of a membrane update symposium: advancements, scientific insights, and future trends for dialysis membranes for enhanced clinical outcomes in end stage kidney disease patients
C. Wanner, Raymond Vanholder, Alberto Ortíz, et al.
Frontiers in Nephrology (2024) Vol. 4
Open Access
C. Wanner, Raymond Vanholder, Alberto Ortíz, et al.
Frontiers in Nephrology (2024) Vol. 4
Open Access
