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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:

Prediction of complications and surgery duration in primary TKA with high accuracy using machine learning with arthroplasty-specific data
Florian Hinterwimmer, Igor Lazic, Severin Langer, et al.
Knee Surgery Sports Traumatology Arthroscopy (2022) Vol. 31, Iss. 4, pp. 1323-1333
Open Access | Times Cited: 44

Showing 1-25 of 44 citing articles:

Definitions and consequences of current alignment techniques and phenotypes in total knee arthroplasty (TKA) – there is no winner yet
Theofilos Karasavvidis, Cale A. Pagan Moldenhauer, Sébastien Lustıg, et al.
Journal of Experimental Orthopaedics (2023) Vol. 10, Iss. 1
Open Access | Times Cited: 26
A practical guide to the development and deployment of deep learning models for the orthopaedic surgeon: Part III, focus on registry creation, diagnosis, and data privacy
Jacob F. Oeding, Linjun Yang, Joaquín Sánchez‐Sotelo, et al.
Knee Surgery Sports Traumatology Arthroscopy (2024) Vol. 32, Iss. 3, pp. 518-528
Closed Access | Times Cited: 7
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
Artificial intelligence and robotics in TKA surgery: promising options for improved outcomes?
Rüdiger von Eisenhart‐Rothe, Florian Hinterwimmer, Heiko Graichen, et al.
Knee Surgery Sports Traumatology Arthroscopy (2022) Vol. 30, Iss. 8, pp. 2535-2537
Open Access | Times Cited: 28
Application of machine learning in the prevention of periprosthetic joint infection following total knee arthroplasty: a systematic review
Yuk Yee Chong, PK Chan, Vincent Wai Kwan Chan, et al.
Arthroplasty (2023) Vol. 5, Iss. 1
Open Access | Times Cited: 14
Enabling Personalized Medicine in Orthopaedic Surgery Through Artificial Intelligence
Nickelas Huffman, Ignacio Pasqualini, Shujaa T. Khan, et al.
JBJS Reviews (2024) Vol. 12, Iss. 3
Closed Access | Times Cited: 6
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: 5
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
Any technology assisting total knee arthroplasty (TKA) will fail without the correct 3D alignment and balancing target
Michael T. Hirschmann, Rüdiger von Eisenhart‐Rothe, Heiko Graichen
Knee Surgery Sports Traumatology Arthroscopy (2023) Vol. 31, Iss. 3, pp. 733-735
Open Access | Times Cited: 12
Surgical factors play a critical role in predicting functional outcomes using machine learning in robotic‐assisted total knee arthroplasty
Lisa Spahn Lundgren, Nathalie Willems, Robert Marchand, et al.
Knee Surgery Sports Traumatology Arthroscopy (2024) Vol. 32, Iss. 12, pp. 3198-3209
Closed 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
Accuracy of machine learning in identifying candidates for total knee arthroplasty (TKA) surgery: a systematic review and meta-analysis
Cong Tian, Haifeng Chen, Wenhui Shao, et al.
European journal of medical research (2025) Vol. 30, Iss. 1
Open Access
Predicting 30-day unplanned hospital readmission after revision total knee arthroplasty: machine learning model analysis of a national patient cohort
Tony Lin‐Wei Chen, Michelle Riyo Shimizu, Anirudh Buddhiraju, et al.
Medical & Biological Engineering & Computing (2024) Vol. 62, Iss. 7, pp. 2073-2086
Closed Access | Times Cited: 3
Artificial Intelligence in Surgery: A Systematic Review of Use and Validation
Nitzan Kenig, Javier Montón Echeverría, Aina Muntaner Vives
Journal of Clinical Medicine (2024) Vol. 13, Iss. 23, pp. 7108-7108
Open Access | Times Cited: 3
Hemi- Versus Total Hip Arthroplasty in Femoral Neck Fractures? Predicting Failure on a 10-Year Data Analysis of the German Arthroplasty Registry (EPRD)
Sven Hungerer, Florian Hinterwimmer, Iris Leister, et al.
Journal of Clinical Medicine (2025) Vol. 14, Iss. 5, pp. 1457-1457
Open Access
Leveraging machine learning for duration of surgery prediction in knee and hip arthroplasty – a development and validation study
Benedikt Langenberger, Daniel Schrednitzki, Andreas M. Halder, et al.
BMC Medical Informatics and Decision Making (2025) Vol. 25, Iss. 1
Open Access
Comparison of an AI-Driven Planning Tool and Manual Radiographic Measurements in Total Knee Arthroplasty
M. Heller, Günther Maderbacher, Marie Schuster, et al.
Computational and Structural Biotechnology Journal (2025) Vol. 28, pp. 148-155
Open Access
The Use of Artificial Intelligence in Orthopedics: Applications and Limitations of Machine Learning in Diagnosis and Prediction
Bernardo Innocenti, Yanislav Radyul, Edoardo Bori
Applied Sciences (2022) Vol. 12, Iss. 21, pp. 10775-10775
Open Access | Times Cited: 16
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
A multiview deep learning‐based prediction pipeline augmented with confident learning can improve performance in determining knee arthroplasty candidates
Hongzhi Liu, Xiaoyao Wang, Xinqiu Song, et al.
Knee Surgery Sports Traumatology Arthroscopy (2024) Vol. 32, Iss. 8, pp. 2107-2119
Closed Access | Times Cited: 3
Optimclm: Optimizing Clinical Language Models for Predicting Patient Outcomes Via Knowledge Distillation, Pruning and Quantization
Mohammad Junayed Hasan, Fuad Rahman, Nabeel Mohammed
(2024)
Closed Access | Times Cited: 2
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
Pre-injury performance is most important for predicting the level of match participation after Achilles tendon ruptures in elite soccer players: a study using a machine learning classifier
Pedro Diniz, Mariana Abreu, Diogo Lacerda, et al.
Knee Surgery Sports Traumatology Arthroscopy (2022) Vol. 30, Iss. 12, pp. 4225-4237
Open Access | Times Cited: 10
Effect of Combined Kinematic Chain Exercise on Physical Function, Balance Ability, and Gait in Patients with Total Knee Arthroplasty: A Single-Blind Randomized Controlled Trial
Jungae An, Young-Wan Son, Byoung‐Hee Lee
International Journal of Environmental Research and Public Health (2023) Vol. 20, Iss. 4, pp. 3524-3524
Open Access | Times Cited: 4
Optimal inputs for machine learning models in predicting total joint arthroplasty outcomes: a systematic review
Parshva A. Sanghvi, Aakash K. Shah, Christian J. Hecht, et al.
European Journal of Orthopaedic Surgery & Traumatology (2024)
Closed Access | Times Cited: 1
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