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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:

Development of a Machine Learning Algorithm to Predict Nonroutine Discharge Following Unicompartmental Knee Arthroplasty
Yining Lu, Zain Khazi, Avinesh Agarwalla, et al.
The Journal of Arthroplasty (2020) Vol. 36, Iss. 5, pp. 1568-1576
Closed Access | Times Cited: 25

Showing 25 citing articles:

Artificial intelligence in orthopedic surgery: evolution, current state and future directions
Andrew P. Kurmis, Jamie R. Ianunzio
Arthroplasty (2022) Vol. 4, Iss. 1
Open Access | Times Cited: 74
Internal and External Validation of the Generalizability of Machine Learning Algorithms in Predicting Non-home Discharge Disposition Following Primary Total Knee Joint Arthroplasty
Tony Lin‐Wei Chen, Anirudh Buddhiraju, Henry Hojoon Seo, et al.
The Journal of Arthroplasty (2023) Vol. 38, Iss. 10, pp. 1973-1981
Closed Access | Times Cited: 16
Efficacy and Applications of Artificial Intelligence and Machine Learning Analyses in Total Joint Arthroplasty
Evan M. Polce, Kyle N. Kunze, Matthew S. Dooley, et al.
Journal of Bone and Joint Surgery (2022) Vol. 104, Iss. 9, pp. 821-832
Closed Access | Times Cited: 22
The Utility of Machine Learning Algorithms for the Prediction of Early Revision Surgery After Primary Total Hip Arthroplasty
Christian Klemt, Samuel Laurencin, Kyle Alpaugh, et al.
Journal of the American Academy of Orthopaedic Surgeons (2022)
Closed Access | Times Cited: 21
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: 19
Developing a decision support tool to predict delayed discharge from hospitals using machine learning
Mahsa Pahlevani, Enayat Rajabi, Majid Taghavi, et al.
BMC Health Services Research (2025) Vol. 25, Iss. 1
Open Access
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
Utilization of machine learning methods for predicting surgical outcomes after total knee arthroplasty
Hina Mohammed, Yihe Huang, Stavros G. Memtsoudis, et al.
PLoS ONE (2022) Vol. 17, Iss. 3, pp. e0263897-e0263897
Open Access | Times Cited: 18
The Impact of Machine Learning on Total Joint Arthroplasty Patient Outcomes: A Systemic Review
Elan Karlin, Charles C. Lin, Morteza Meftah, et al.
The Journal of Arthroplasty (2022) Vol. 38, Iss. 10, pp. 2085-2095
Open Access | Times Cited: 16
Predicting Venous Thrombosis in Osteoarthritis Using a Machine Learning Algorithm: A Population-Based Cohort Study
Chao Lu, Jiayin Song, Hui Li, et al.
Journal of Personalized Medicine (2022) Vol. 12, Iss. 1, pp. 114-114
Open Access | Times Cited: 15
Health and Socioeconomic Risk Factors for Unplanned Hospitalization Following Ambulatory Unicompartmental Knee Arthroplasty: Development of a Patient Selection Tool Using Machine Learning
Joshua R. Labott, Yining Lu, Harold I. Salmons, et al.
The Journal of Arthroplasty (2023) Vol. 38, Iss. 10, pp. 1982-1989
Closed Access | Times Cited: 9
The Risk Assessment and Prediction Tool (RAPT) Score Predicts Discharge Destination, Length of Stay, and Postoperative Mobility After Total Joint Arthroplasty
Drake G. LeBrun, Joseph Nguyen, Charles Fisher, et al.
The Journal of Arthroplasty (2023) Vol. 38, Iss. 7, pp. S121-S129
Closed Access | Times Cited: 9
A role for artificial intelligence applications inside and outside of the operating theatre: a review of contemporary use associated with total knee arthroplasty
Andrew P. Kurmis
Arthroplasty (2023) Vol. 5, Iss. 1
Open Access | Times Cited: 9
Challenges of Integrating New Technologies for Orthopedic Doctors to Face up to Difficulties during the Pandemic Era
Marius Niculescu, Octavia-Sorina Honțaru, George Popescu, et al.
Healthcare (2023) Vol. 11, Iss. 11, pp. 1524-1524
Open Access | Times Cited: 8
Machine-learning vs. logistic regression for preoperative prediction of medical morbidity after fast-track hip and knee arthroplasty—a comparative study
Christian Michelsen, Christoffer Calov Jørgensen, Mathias L. Heltberg, et al.
BMC Anesthesiology (2023) Vol. 23, Iss. 1
Open Access | Times Cited: 6
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
Editorial Commentary: Knowledge is Power: A Primer for Machine Learning
Ian J. Wellington, James C. Messina, Mark P. Cote
Arthroscopy The Journal of Arthroscopic and Related Surgery (2023) Vol. 39, Iss. 2, pp. 159-160
Closed Access | Times Cited: 4
Learning curve of Persona Partial Knee (PPK) arthroplasty: a clinical trial
Riccardo D’Ambrosi, Danko Dan Milinkovic, Filippo Migliorini, et al.
BMC Musculoskeletal Disorders (2024) Vol. 25, Iss. 1
Open Access | Times Cited: 1
A systematic literature review of predicting patient discharges using statistical methods and machine learning
Mahsa Pahlevani, Majid Taghavi, Peter T. Vanberkel
Health Care Management Science (2024) Vol. 27, Iss. 3, pp. 458-478
Open Access | Times Cited: 1
Implementation of Machine Learning to Predict Cost of Care Associated with Ambulatory Single-Level Lumbar Decompression
Harold I. Salmons, Yining Lu, Ryder R. Reed, et al.
World Neurosurgery (2022) Vol. 167, pp. e1072-e1079
Closed Access | Times Cited: 3
Machine learning model outperforms the ACS Risk Calculator in predicting non‐home discharge following primary total knee arthroplasty
Blake M. Bacevich, Tony Lin‐Wei Chen, Anirudh Buddhiraju, et al.
Knee Surgery Sports Traumatology Arthroscopy (2024)
Closed Access
Risk assessment model used to predict discharge care after total hip and total knee arthroplasty: A population-based study
Hélio Ricardo Nogueira Alves, Sébastien Di Tommaso, Julien Wegrzyn, et al.
Journal of Orthopaedics (2024) Vol. 63, pp. 1-7
Open Access
Utilizing AI to Improve Orthopedic Care

(2024), pp. 105-131
Closed Access
Machine-learning vs. logistic regression for preoperative prediction of medical morbidity after fast-track hip and knee arthroplasty - a comparative study
Christian Michelsen, Christoffer Calov Jørgensen, Mathias L. Heltberg, et al.
Research Square (Research Square) (2023)
Open Access
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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