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Decoding surgical proficiency and complexity: a machine learning framework for robotic herniorrhaphy
0
Zitationen
6
Autoren
2025
Jahr
Abstract
Objective performance indicators poorly predict case complexity independently, yet their temporal evolution reveals surgical skill acquisition. The concurrent stabilization of OPI stochasticity and progression to more complex cases demonstrates that surgical proficiency and complexity assessment are interdependent phenomena, establishing digital metrics as tools for understanding the dynamic relationship between surgeon learning and case difficulty.
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