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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:

A Novel, Potentially Universal Machine Learning Algorithm to Predict Complications in Total Knee Arthroplasty
Sai K. Devana, Akash Shah, Changhee Lee, et al.
Arthroplasty Today (2021) Vol. 10, pp. 135-143
Open Access | Times Cited: 21

Showing 21 citing articles:

Chat Generative Pretrained Transformer (ChatGPT) and Bard: Artificial Intelligence Does not yet Provide Clinically Supported Answers for Hip and Knee Osteoarthritis
JaeWon Yang, Kyle S. Ardavanis, Katherine Slack, et al.
The Journal of Arthroplasty (2024) Vol. 39, Iss. 5, pp. 1184-1190
Closed Access | Times Cited: 26
Artificial Intelligence and Machine Learning in Prediction of Surgical Complications: Current State, Applications, and Implications
Abbas M. Hassan, Aashish Rajesh, Malke Asaad, et al.
The American Surgeon (2022) Vol. 89, Iss. 1, pp. 25-30
Closed Access | Times Cited: 37
AutoPrognosis 2.0: Democratizing diagnostic and prognostic modeling in healthcare with automated machine learning
Fergus Imrie, Bogdan Cebere, Eoin McKinney, et al.
PLOS Digital Health (2023) Vol. 2, Iss. 6, pp. e0000276-e0000276
Open Access | Times Cited: 20
Artificial intelligence in total and unicompartmental knee arthroplasty
Umile Giuseppe Longo, Sergio De Salvatore, F Valente, et al.
BMC Musculoskeletal Disorders (2024) Vol. 25, Iss. 1
Open Access | Times Cited: 4
Artificial intelligence and machine learning in knee arthroplasty
Hugo C. Rodriguez, Brandon Rust, Martin W. Roche, et al.
The Knee (2025) Vol. 54, pp. 28-49
Closed Access
Concerns surrounding application of artificial intelligence in hip and knee arthroplasty
Teja S. Polisetty, Samagra Jain, Michael Pang, et al.
The Bone & Joint Journal (2022) Vol. 104-B, Iss. 12, pp. 1292-1303
Closed Access | Times Cited: 18
Construction of Prediction Model of Deep Vein Thrombosis Risk after Total Knee Arthroplasty Based on XGBoost Algorithm
Yuhuan Chen, Yingqing Jiang
Computational and Mathematical Methods in Medicine (2022) Vol. 2022, pp. 1-6
Open Access | Times Cited: 12
An orthopaedic intelligence application successfully integrates data from a smartphone-based care management platform and a robotic knee system using a commercial database
Jess H. Lonner, Mike B. Anderson, Roberta E. Redfern, et al.
International Orthopaedics (2022) Vol. 47, Iss. 2, pp. 485-494
Closed Access | Times Cited: 10
Improved performance of machine learning models in predicting length of stay, discharge disposition, and inpatient mortality after total knee arthroplasty using patient-specific variables
Abdul K. Zalikha, Tannor Court, Fong H. Nham, et al.
Arthroplasty (2023) Vol. 5, Iss. 1
Open Access | Times Cited: 5
Machine Learning Algorithm to Predict Worsening of Flexion Range of Motion After Total Knee Arthroplasty
Yoshitomo Saiki, Tamon Kabata, Tomohiro Ojima, et al.
Arthroplasty Today (2022) Vol. 17, pp. 66-73
Open Access | Times Cited: 8
Prediction model of deep vein thrombosis risk after lower extremity orthopedic surgery
Jiannan Zhang, Yang Shao, Hongmei Zhou, et al.
Heliyon (2024) Vol. 10, Iss. 9, pp. e29517-e29517
Open Access | Times Cited: 1
Assessing the Value of Imaging Data in Machine Learning Models to Predict Patient-Reported Outcome Measures in Knee Osteoarthritis Patients
Abhinav Nair, M. Abdulhadi Alagha, Justin Cobb, et al.
Bioengineering (2024) Vol. 11, Iss. 8, pp. 824-824
Open Access | Times Cited: 1
Comparative Analysis of the Ability of Machine Learning Models in Predicting In-hospital Postoperative Outcomes After Total Hip Arthroplasty
Mouhanad M. El-Othmani, Abdul K. Zalikha, Roshan P. Shah
Journal of the American Academy of Orthopaedic Surgeons (2022)
Closed Access | Times Cited: 7
Artificial intelligence's role in vascular surgery decision-making
Devin S. Zarkowsky, David P. Stonko
Seminars in Vascular Surgery (2021) Vol. 34, Iss. 4, pp. 260-267
Closed Access | Times Cited: 8
Modern Applications of Machine Learning in Shoulder Arthroplasty
Akshar V. Patel, Andrew Stevens, Noah Mallory, et al.
JBJS Reviews (2023) Vol. 11, Iss. 7
Closed Access | Times Cited: 3
Predictive capacity of four machine learning models for in-hospital postoperative outcomes following total knee arthroplasty
Abdul K. Zalikha, Mouhanad M. El-Othmani, Roshan P. Shah
Journal of Orthopaedics (2022) Vol. 31, pp. 22-28
Open Access | Times Cited: 5
A Novel Machine Learning Model to Predict Revision ACL Reconstruction Failure in the MARS Cohort
Kinjal Vasavada, Vrinda Vasavada, Jay Moran, et al.
Orthopaedic Journal of Sports Medicine (2024) Vol. 12, Iss. 11
Open Access
Bedeutung von künstlicher Intelligenz für die Risikoerkennung vor chirurgischen Eingriffen
Guillermo Sánchez Rosenberg, Christian Egloff
Arthroskopie (2024) Vol. 37, Iss. 3, pp. 153-158
Open Access
Comparable performance of machine learning algorithms in predicting readmission and complications following total joint arthroplasty with external validation
Hashim Shaikh, Mina Botros, Gabriel Ramirez, et al.
Arthroplasty (2023) Vol. 5, Iss. 1
Open Access | Times Cited: 1
Machine learning for real-time prediction of complications induced by flexible uretero-renoscopy with laser lithotripsy
Chafik Baidada, Hamid Hrimech, Mustapha Aatila, et al.
International Journal of Power Electronics and Drive Systems/International Journal of Electrical and Computer Engineering (2023) Vol. 14, Iss. 1, pp. 971-971
Open Access | Times Cited: 1
Artificial Intelligence, Deep Learning, and Machine Learning Applications in Total Knee Arthroplasty
Emre Tokgöz, Sarah Levitt, Diana Sosa, et al.
(2023), pp. 215-245
Closed Access
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