Validation of a new fully automated software for 2D digital mammographic breast density evaluation in predicting breast cancer risk

Abstract 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...

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Autores principales:	Paolo Giorgi Rossi, Olivera Djuric, Valerie Hélin, Susan Astley, Paola Mantellini, Andrea Nitrosi, Elaine F. Harkness, Emilien Gauthier, Donella Puliti, Corinne Balleyguier, Camille Baron, Fiona J. Gilbert, André Grivegnée, Pierpaolo Pattacini, Stefan Michiels, Suzette Delaloge
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/2ae46de7556848ca9eefd8ac6c0d1149
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Validation of a new fully automated software for 2D digital mammographic breast density evaluation in predicting breast cancer risk

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