Can we reduce the workload of mammographic screening by automatic identification of normal exams wit...
Can we reduce the workload of mammographic screening by automatic identification of normal exams with artificial intelligence? A feasibility study
About this item
Full title
Author / Creator
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. , Faculty of Medicine , Medicinska fakulteten , Lund University , Radiology Diagnostics, Malmö , Diagnostisk radiologi, Malmö , Department of Translational Medicine , Lunds universitet and Institutionen för translationell medicin
Publisher
Berlin/Heidelberg: Springer Berlin Heidelberg
Journal title
Language
English
Formats
Publication information
Publisher
Berlin/Heidelberg: Springer Berlin Heidelberg
Subjects
More information
Scope and Contents
Contents
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 gathered from nine previously performed multi-...
Alternative Titles
Full title
Can we reduce the workload of mammographic screening by automatic identification of normal exams with artificial intelligence? A feasibility study
Authors, Artists and Contributors
Author / Creator
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.
Faculty of Medicine
Medicinska fakulteten
Lund University
Radiology Diagnostics, Malmö
Diagnostisk radiologi, Malmö
Department of Translational Medicine
Lunds universitet
Institutionen för translationell medicin
Identifiers
Primary Identifiers
Record Identifier
TN_cdi_proquest_journals_2210255965
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2210255965
Other Identifiers
ISSN
0938-7994,1432-1084
E-ISSN
1432-1084
DOI
10.1007/s00330-019-06186-9
How to access this item
ERROR: Invalid URL specified.
