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Simulating workload reduction with an AI-based prostate cancer detection pathway using a prediction uncertainty metric
4
Zitationen
8
Autoren
2025
Jahr
Abstract
Question AI can autonomously assess prostate MRI scans with high certainty at a non-inferior performance compared to radiologists, potentially reducing the workload of radiologists. Findings The optimal ratio of AI-model and radiologist readings is institute-dependent and requires calibration. Clinical relevance Semi-autonomous AI-based prostate cancer detection with variational UQ scores shows promise in reducing the number of scans radiologists need to read.
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