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:

Leveraging large, real-world data through machine-learning to increase efficiency in robotic-assisted total knee arthroplasty
Sietske Witvoet, Daniele De Massari, Sarah Shi, et al.
Knee Surgery Sports Traumatology Arthroscopy (2023) Vol. 31, Iss. 8, pp. 3160-3171
Closed Access | Times Cited: 8

Showing 8 citing articles:

Artificial intelligence (AI) and large data registries: Understanding the advantages and limitations of contemporary data sets for use in AI research
Kyle N. Kunze, Riley J. Williams, Anil S. Ranawat, et al.
Knee Surgery Sports Traumatology Arthroscopy (2024) Vol. 32, Iss. 1, pp. 13-18
Closed Access | Times Cited: 6

Abandon the mean value thinking: Personalized medicine an intuitive way for improved outcomes in orthopaedics
Michael T. Hirschmann, M. Bonnin
Knee Surgery Sports Traumatology Arthroscopy (2024)
Closed Access | Times Cited: 5

Artificial Intelligence in Commercial Industry: Serving the End-to-End Patient Experience Across the Digital Ecosystem
Michael J. Ormond, Eric H Garling, J. Woo, et al.
Arthroscopy The Journal of Arthroscopic and Related Surgery (2025)
Closed Access

Trends of robotic total joint arthroplasty utilization in the United States from 2010 to 2022: a nationwide assessment
Adam M. Gordon, Patrick P. Nian, Joydeep Baidya, et al.
Journal of Robotic Surgery (2025) Vol. 19, Iss. 1
Closed Access

AI may enable robots to make a clinical impact in total knee arthroplasty, where navigation has not!
Michael T. Hirschmann, Rüdiger von Eisenhart‐Rothe, Heiko Graichen, et al.
Journal of Experimental Orthopaedics (2024) Vol. 11, Iss. 4
Open Access | Times Cited: 2

Machine learning models to predict surgical case duration compared to current industry standards: scoping review
Christopher Spence, Owais A. Shah, A Cebula, et al.
BJS Open (2023) Vol. 7, Iss. 6
Open Access | Times Cited: 4

Adverse events related to robotic-assisted knee arthroplasty: a cross-sectional study from the MAUDE database
Wei Zheng, Binghua Wu, Tao Cheng
Archives of Orthopaedic and Trauma Surgery (2024) Vol. 144, Iss. 9, pp. 4151-4161
Closed Access | Times Cited: 1

Lack of Validity of Absolute Percentage Errors in Estimated Operating Room Case Durations as a Measure of Operating Room Performance: A Focused Narrative Review
Franklin Dexter, Richard H. Epstein
Anesthesia & Analgesia (2024) Vol. 139, Iss. 3, pp. 555-561
Closed Access

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