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Validation of a new fully automated software for 2D digital mammographic breast density evaluation in predicting breast cancer risk
We compared accuracy for breast cancer (BC) risk stratification of a new fully automated system (DenSeeMammo-DSM) for breast density (BD) assessment to a non-inferiority threshold based on radiologists' visual assessment. Pooled analysis was performed on 14,267 2D mammograms collected from women aged 48-55 years who underwent BC screening within three studies: RETomo, Florence study and PROCAS. BD was expressed through clinical Breast Imaging Reporting and Data System (BI-RADS) densitydoi:10.17863/cam.76885 fatcat:whfis5b3erabpcsp6wgfpovvk4