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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 image-based machine learning model with superior accuracy and predictability for knee arthroplasty loosening detection and clinical decision making
Lawrence Chun‐Man Lau, Elvis Chun‐Sing Chui, Gene Chi Wai Man, et al.
Journal of Orthopaedic Translation (2022) Vol. 36, pp. 177-183
Open Access | Times Cited: 22

Showing 22 citing articles:

Identifying Severity Grading of Knee Osteoarthritis from X-ray Images Using an Efficient Mixture of Deep Learning and Machine Learning Models
Sozan Mohammed Ahmed, Ramadhan J. Mstafa
Diagnostics (2022) Vol. 12, Iss. 12, pp. 2939-2939
Open Access | Times Cited: 43
A systematic review and meta-analysis comparing outcomes following total knee arthroplasty for rheumatoid arthritis versus for osteoarthritis
Yongjie Qiao, Feng Li, Lvdan Zhang, et al.
BMC Musculoskeletal Disorders (2023) Vol. 24, 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: 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
Predicting periprosthetic joint infection in primary total knee arthroplasty: a machine learning model integrating preoperative and perioperative risk factors
Yuk Yee Chong, Lawrence Chun‐Man Lau, Tianshu Jiang, et al.
BMC Musculoskeletal Disorders (2025) Vol. 26, Iss. 1
Open Access
Machine Learning for Detecting Total Knee Arthroplasty Implant Loosening on Plain Radiographs
Man Soo Kim, Ryu-Kyoung Cho, Sung-Cheol Yang, et al.
Bioengineering (2023) Vol. 10, Iss. 6, pp. 632-632
Open Access | Times Cited: 9
Knee Osteoarthritis Classification Using X-Ray Images Based on Optimal Deep Neural Network
Abdul Haseeb, Muhammad Attique Khan, Faheem Shehzad, et al.
Computer Systems Science and Engineering (2023) Vol. 47, Iss. 2, pp. 2397-2415
Open Access | Times Cited: 6
Understanding the use of artificial intelligence for implant analysis in total joint arthroplasty: a systematic review
Aakash K. Shah, Monish S. Lavu, Christian J. Hecht, et al.
Arthroplasty (2023) Vol. 5, Iss. 1
Open Access | Times Cited: 6
Reliability of artificial intelligence in predicting total knee arthroplasty component sizes: a systematic review
Loay A. Salman, Harman Khatkar, Abdallah Al‐Ani, et al.
European Journal of Orthopaedic Surgery & Traumatology (2023) Vol. 34, Iss. 2, pp. 747-756
Open Access | Times Cited: 6
Detection of Prosthetic Loosening in Hip and Knee Arthroplasty Using Machine Learning: A Systematic Review and Meta-Analysis
Man Soo Kim, Jae-Jung Kim, Kiho Kang, et al.
Medicina (2023) Vol. 59, Iss. 4, pp. 782-782
Open Access | Times Cited: 5
Development of Hallux Valgus Classification Using Digital Foot Images with Machine Learning
M. Hida, Shinji Eto, Chikamune Wada, et al.
Life (2023) Vol. 13, Iss. 5, pp. 1146-1146
Open Access | Times Cited: 5
Artificial Intelligence in Revision Total Knee Arthroplasty
E. Carlos Rodríguez‐Merchán
(2024), pp. 141-147
Closed Access
Deep Learning Applications in Orthopaedics: A Systematic Review and Future Directions
Ramón González Pola, Alberto Herrera Lozano, Luis Felipe Graham Nieto, et al.
Research Square (Research Square) (2024)
Open Access
Accurate crop disease identification and classification in smart agriculture using a three-tier model and optimized fully conventional network
Ruchika Rai, Pratosh Bansal
Multimedia Tools and Applications (2024)
Closed Access
Leveraging transfer learning for predicting total knee arthroplasty failure from post‐operative radiographs
Anna Corti, Sarah Galante, Robert F. Rauch, et al.
Journal of Experimental Orthopaedics (2024) Vol. 11, Iss. 4
Open Access
Enhancing knee osteoarthritis diagnosis with DMS: a novel dense multi-scale convolutional neural network approach
Di Zhang, Yuting Dong, Yao Xu, et al.
Journal of Orthopaedic Surgery and Research (2024) Vol. 19, Iss. 1
Open Access
The Impacts of the Analysis, Debate, and Finding Models on Learning Natural Sciences
Apdoludin Apdoludin, Megawati Megawati, Randi Eka Putra, et al.
Qubahan Academic Journal (2024) Vol. 4, Iss. 3, pp. 166-174
Open Access
Artificial Intelligence in Knee Arthroplasty
Enrico Bertugli, Sébastien Lustıg, Sébastien Parratte, et al.
(2024), pp. 55-63
Closed Access
Automatic detection of Cryptosporidium in optical microscopy images using YOLOv5x: a comparative study
Johan Sebastian Lopez Salguero, Melissa Rodríguez Rendón, Jessica Triviño-Valencia, et al.
Biochemistry and Cell Biology (2023) Vol. 101, Iss. 6, pp. 538-549
Closed Access
A multi-branch network to detect post-operative complications following hip arthroplasty on X-ray images
Sijia Guo, Jiping Zhang, Huiwu Li, et al.
Frontiers in Bioengineering and Biotechnology (2023) Vol. 11
Open Access
Deep learning based methodologies applied to industrial electromechanical systems monitoring
Francisco Arellano-Espitia
(2023)
Open Access
Deep Learning-Based Partial Transfer Fault Diagnosis Methodology for Electromechanical Systems
Francisco Arellano-Espitia, Miguel Delgado-Prieto, Joan Valls-Perez, et al.
2022 IEEE 27th International Conference on Emerging Technologies and Factory Automation (ETFA) (2023), pp. 1-6
Closed Access
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