Preoperative Rotator Cuff Tear Prediction from Shoulder Radiographs using a Convolutional Block Attention Module-Integrated Neural Network Article Swipe
Chris Hyunchul Jo
,
Jiwoong Yang
,
Byunghwan Jeon
,
Hackjoon Shim
,
Ikbeom Jang
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2408.09894
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2408.09894
Research question: We test whether a plane shoulder radiograph can be used together with deep learning methods to identify patients with rotator cuff tears as opposed to using an MRI in standard of care. Findings: By integrating convolutional block attention modules into a deep neural network, our model demonstrates high accuracy in detecting patients with rotator cuff tears, achieving an average AUC of 0.889 and an accuracy of 0.831. Meaning: This study validates the efficacy of our deep learning model to accurately detect rotation cuff tears from radiographs, offering a viable pre-assessment or alternative to more expensive imaging techniques such as MRI.
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Metadata
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2408.09894
- https://arxiv.org/pdf/2408.09894
- OA Status
- green
- Cited By
- 1
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4402502495
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4402502495Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.48550/arxiv.2408.09894Digital Object Identifier
- Title
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Preoperative Rotator Cuff Tear Prediction from Shoulder Radiographs using a Convolutional Block Attention Module-Integrated Neural NetworkWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
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2024Year of publication
- Publication date
-
2024-08-19Full publication date if available
- Authors
-
Chris Hyunchul Jo, Jiwoong Yang, Byunghwan Jeon, Hackjoon Shim, Ikbeom JangList of authors in order
- Landing page
-
https://arxiv.org/abs/2408.09894Publisher landing page
- PDF URL
-
https://arxiv.org/pdf/2408.09894Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://arxiv.org/pdf/2408.09894Direct OA link when available
- Concepts
-
Rotator cuff, Convolutional neural network, Radiography, Block (permutation group theory), Medicine, Computer science, Artificial intelligence, Orthodontics, Radiology, Mathematics, GeometryTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
1Total citation count in OpenAlex
- Citations by year (recent)
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2025: 1Per-year citation counts (last 5 years)
- Related works (count)
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10Other works algorithmically related by OpenAlex
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