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Background: Breast cancer diagnoses are limited in low- and middle-income settings due to lack of medical resources. In these settings, point-of-care ultrasound (POCUS) combined with artificial intelligence (AI)-based interpretation could be a suitable approach. Purpose: To compare the performance of an AI-based breast cancer classification algorithm with radiologists and assess whether POCUS perf
