Machine Learning-Based Classification of Shoulder Implant X-Rays for Manufacturer Identification

Authors

  • Sayyed Hasanoddin, Bilavath Shiva, Bashaboyina Sai Gagan, Vugge Pallavi, Macharla Sai Kiran

Keywords:

Keywords: Shoulder implant classification, X-ray image analysis, Support vector machine, Random Forest classifier, Data balancing.

Abstract

Recent advancements in medical imaging and machine learning have facilitated automatedclassification of orthopaedic implants, improving accuracy and efficiency. Shoulder implants are usedin orthopaedic surgeries, and their identification is crucial for revision procedures and post-operativeassessments. Studies show that over 250,000 shoulder replacements are performed annually in the U.S.,with implant misidentification contributing to 30% of revision complications.

References

AI-driven optimization in healthcare: the diagnostic process. Lyon J, Bogodistov Y, Moormann J. Eur J Manage Issues. 2021; 29:218–231

Evolving scenario of big data and artificial intelligence (AI) in drug discovery. Tripathi MK, Nath A, Singh TP, Ethayathulla AS, Kaur P. Mol Divers. 2021;25:1439–1460

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Published

2025-04-08

How to Cite

Sayyed Hasanoddin, Bilavath Shiva, Bashaboyina Sai Gagan, Vugge Pallavi, Macharla Sai Kiran. (2025). Machine Learning-Based Classification of Shoulder Implant X-Rays for Manufacturer Identification . Journal of Computational Analysis and Applications (JoCAAA), 34(4), 110–120. Retrieved from https://eudoxuspress.com/index.php/pub/article/view/2280

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