A preliminary examination of the diagnostic value of deep learning in hip osteoarthritis
Open accessAbstract
Hip Osteoarthritis (OA) is a common disease among the middle-aged and elderly people. Conventionally, hip OA is diagnosed by manually assessing X-ray images. This study took the hip joint as the object of observation and explored the diagnostic value of deep learning in hip osteoarthritis. A deep convolutional neural network (CNN) was trained and tested on 420 hip X-ray images to automatically diagnose hip OA. This CNN model achieved a balance of high sensitivity of 95.0% and high specificity of 90.7%, as well as an accuracy of 92.8% compared to the chief physicians. The CNN model performance is comparable to an attending physician with 10 years of experience. The results of this study indicate that deep learning has promising potential in the field of intelligent medical image diagnosis practice.
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Applications of deep learning in musculoskeletal imaging remain limited.
“While a survey on deep learning in medical image analysis has shown a wide variety of applications in all imaging subspecialties (13), applications in musculoskeletal imaging remain limited (14–17).”
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References 24 · Cited by 198
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- Authors
- Xue, Y., Zhang, R., Deng, Y., Chen, K., & Jiang, T.
- Affiliations
- Capital Medical University (CN)
- InferVision (China) (CN)
- Corresponding author
- Deng, Yufeng
- Jiang, Tao
- Venue
- PLOS ONE
- Publisher
- Public Library of Science (PLoS)
- Published
- 2017-06-02
- Volume
- 12
- Issue
- 6
- Pages
- e0178992
- ISSN
- 1932-6203 (ISSN-L)
- PMC
- PMC5456368
- OpenAlex
- W2621007086
- Cited by
- 198
- References
- 24
- Citations by year
- 2026: 11 · 2025: 22 · 2024: 37 · 2023: 32 · 2022: 24 · 2021: 23 · 2020: 28 · 2019: 12 · 2018: 9
- FWCI
- 6.03
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- PLoS ONE (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Topics
- Physical Sciences › Engineering › Biomedical Engineering › Medical Imaging and Analysis
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Health Sciences › Medicine › Surgery › Hip disorders and treatments
- Keywords
- hip osteoarthritis, deep learning, convolutional neural networks, X-ray images, automated diagnosis, diagnostic accuracy, radiographic evaluation, artificial intelligence in medical imaging
- MeSH terms
- Hip Joint, Humans, Image Processing, Computer-Assisted, Radiography, Osteoarthritis, Hip, Neural Networks, Computer
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