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AI in the Loop: functionalizing fold performance disagreement to monitor automated medical image segmentation workflows
1
Zitationen
4
Autoren
2023
Jahr
Abstract
Comparing interfold sub-model disagreement against human interobserver values is an effective and efficient way to assess automated predictions when a reference standard is not available. This functionality provides a necessary safeguard to patient care important to safely implement automated medical image segmentation workflows.
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