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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:

Re-tear after arthroscopic rotator cuff tear surgery: risk analysis using machine learning
Issei Shinohara, Yutaka Mifune, Atsuyuki Inui, et al.
Journal of Shoulder and Elbow Surgery (2023) Vol. 33, Iss. 4, pp. 815-822
Closed Access | Times Cited: 10

Showing 10 citing articles:

Predictors of Early Functional Improvement after Arthroscopic Rotator Cuff Repair
Justin Turcotte, Jane C Brennan, Daniel Boudani, et al.
JSES International (2025)
Open Access
Tendon Stump Change as a Risk Factor for Structural Failure of Arthroscopic Rotator Cuff Repair
Jun Kawamata, Shoji Fukuta, Masashi Kano, et al.
JSES International (2025)
Open Access
Artificial intelligence applications in the management of musculoskeletal disorders of the shoulder: A systematic review
Umile Giuseppe Longo, Martina Marino, Guido Nicodemi, et al.
Journal of Experimental Orthopaedics (2025) Vol. 12, Iss. 2
Open Access
Re-tear after arthroscopic rotator cuff repair can be predicted using deep learning algorithm
Zhewei Zhang, Chunhai Ke, Zhibin Zhang, et al.
Frontiers in Artificial Intelligence (2024) Vol. 7
Open Access | Times Cited: 2
Machine-learning models for diagnosis of rotator cuff tears in osteoporosis patients based on anteroposterior X-rays of the shoulder joint
Yu Zhao, Jingjing Qiu, Yang Li, et al.
SLAS TECHNOLOGY (2024) Vol. 29, Iss. 4, pp. 100149-100149
Open Access | Times Cited: 2
Shoulder arthroscopy: Where we come from, where we are now and what is ahead. How artificial intelligence and machine‐learning technologies will transform our field
Emílio Calvo, Elena T. Calvo
Knee Surgery Sports Traumatology Arthroscopy (2024) Vol. 32, Iss. 8, pp. 1923-1925
Closed Access | Times Cited: 1
Clinical Outcomes and Re-Tear Rates for Partial Arthroscopic Rotator Cuff Repair With or Without Biceps Augmentation for Large-to-Massive Tears: A Systematic Review and Meta-analysis
Anthony N. Baumann, Andrew Fiorentino, Katelyn Sidloski, et al.
Orthopedics (2024) Vol. 47, Iss. 5
Open Access | Times Cited: 1
Preoperative Increases in T2-Weighted Fat-Suppressed MRI Signal Intensities Associated with Advanced Tissue Degeneration and Mitochondrial Dysfunction in Rotator Cuff Tears
Masaya Kusunose, Yutaka Mifune, Atsuyuki Inui, et al.
Arthroscopy The Journal of Arthroscopic and Related Surgery (2024)
Closed Access | Times Cited: 1
Anwendungen und Zukunftsperspektiven von künstlicher Intelligenz in der Schulter- und Ellenbogenchirurgie
David A. Back, Rony-Orijit Dey Hazra, Doruk Akgün
Obere Extremität (2024) Vol. 19, Iss. 3, pp. 218-220
Closed Access
Study on Shoulder Joint Parameters and Available Supraspinatus Outlet Area Using Three-Dimensional Computed Tomography Reconstruction
Xi Chen, Tangzhao Liang, Xiaopeng Yin, et al.
Tomography (2024) Vol. 10, Iss. 9, pp. 1331-1341
Open Access
Posture Estimation Model Combined With Machine Learning Estimates the Radial Abduction Angle of the Thumb With High Accuracy
Issei Shinohara, Atsuyuki Inui, Yutaka Mifune, et al.
Cureus (2024)
Open Access
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