Diagnostic Accuracy of Carebot AI MMG in Mammography Screening: Multicenter MRMC Study

This study evaluates the diagnostic performance of Carebot AI MMG, an artificial intelligence (AI)-enabled medical device for evaluating mammograms. The software analyzes standard full-field digital mammography (FFDM) images and classifies each examination as having no suspicious finding ("Low Risk"), a probably benign mass ("Medium Risk"), or a suspicious malignant mass ("High Risk"). The study is retrospective and observational. It uses anonymized mammography examinations from four screening centers, without any additional imaging or contact with patients. Three experienced breast radiologists independently read the same set of cases, and their assessments are used as the human benchmark. A histopathology-based reference standard, supplemented by radiologist consensus and follow-up information for negative cases, is used to determine whether cancer is present. The main goal is to compare the AI system with human radiologists in terms of sensitivity and specificity for detecting breast cancer, and to assess whether the AI can achieve non-inferior performance at two predefined operating points: one favoring higher sensitivity and negative predictive value (rule-out) and one favoring higher specificity and positive predictive value (rule-in).