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Can a machine learning approach contribute to monitoring post-market surveillance of total knee arthroplasty prostheses?
0
Zitationen
7
Autoren
2025
Jahr
Abstract
Machine learning may offer a supplementary approach for the identification of prosthesis outliers. However, further analysis is required to fully comprehend the effect of confounding factors and the potential contribution of ML to the early identification of outliers.
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