Can we reduce the workload of mammographic screening by automatic identification of normal exams with artificial intelligence? A feasibility study.

Purpose: To study the feasibility of automatically identifying normal digital mammography (DM) exams with artificial intelligence (AI) to reduce the breast cancer screening reading workload.Methods and Materials: A total of 2652 DM exams (653 cancer) and interpretations by 101 radiologists were gath...

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Bibliographic Details

Published in:	European Radiology Vol. 29; no. 9; pp. 4825 - 4833
Main Authors:	Rodriguez-Ruiz, Alejandro, Lång, Kristina, Gubern-Merida, Albert, Teuwen, Jonas, Broeders, Mireille, Gennaro, Gisella, Clauser, Paola, Helbich, Thomas H., Chevalier, Margarita, Mertelmeier, Thomas, Wallis, Matthew G., Andersson, Ingvar, Zackrisson, Sophia, Sechopoulos, Ioannis, Mann, Ritse M.
Format:	diagnostic images research tables/charts Journal Article
Published:	Springer Nature Sep2019
Online Access:	View this record in EBSCOhost