Predicting Rotator Cuff Tear Severity Using Radiographic Images and Machine Learning Techniques-Reference-Cited by-同舟云学术

Predicting Rotator Cuff Tear Severity Using Radiographic Images and Machine Learning Techniques

Published:2021-10-15 Issue: Volume: Page:
ISSN:
Container-title:2021 10th International Conference on Computing and Pattern Recognition
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Author:

Cho Yusik¹,Jalics Alena²,Lv Ding²,Gilbert Marissa²,Dickson Kathy²,Chen Dawei²,Nguyen Thomas¹,Joines Hannah³,Kakos Brandon¹,Chen Chaoyang³,Lemos Stephen¹

Affiliation:

1. Department of Orthopaedic Surgery and Sports Medicine Detroit, Detroit Medical Center, USA

2. Department of Biomedical Engineering, Wayne State University, USA

3. Department of Orthopaedic Surgery and Sports Medicine Detroit, Detroit Medical Center, USA and Department of Biomedical Engineering, Wayne State University, USA

Funder

Wayne State University UPTF Professional Development Grant

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3497623.3497661

Reference21 articles.

1. Surgical Anatomy of the Rotator Cuff and the Natural History of Degenerative Periarthritis

2. Rupture of the Rotator Cuff of the Shoulder:Experiences of Surgical Treatment

3. Radiographic findings associated with symptomatic rotator cuff tears

4. Correlation of radiographic and arthroscopic findings with rotator cuff tears and degenerative joint disease

5. SUPERIOR MIGRATION OF THE HUMERAL HEAD

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