Keywords: Diagnosis/Prediction, Screening
Motivation: Full MRI breast cancer screening protocols are time-intensive and abbreviated protocols have relatively high recall. An AI-driven hybrid protocol could combine the strengths of both protocols.
Goal(s): To determine the theoretical bounds of time and recall for an adaptive protocol.
Approach: We calculated the maximum and minimum overlap between cases identified by radiologists and AI for the abbreviated protocol.
Results: An AI driven protocol could improve MRI screening by reducing acquisition time and recall rates, compared to the full and abbreviated protocol respectively.
Impact: The AI-based hybrid protocol could improve MRI screening by reducing acquisition time and recall rates, enhancing patient-centric care, improving MRI availability and achieving better breast cancer screening.
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