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Epistemic Uncertainty-Aware Defect Detection for Quality Control in Medical Device Manufacturing
Objective: We investigate whether accounting for epistemic uncertainty can improve the reliability of automated defect detection in medical device manufacturing. Methods: We consider a machine learning framework that operates on heterogeneous manufacturing and device-report data represented with Kno
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