Deep learning for chest radiograph diagnosis: A retrospective comparison of the CheXNeXt algorithm t...
Deep learning for chest radiograph diagnosis: A retrospective comparison of the CheXNeXt algorithm to practicing radiologists
About this item
Full title
Author / Creator
Rajpurkar, Pranav , Irvin, Jeremy , Ball, Robyn L. , Zhu, Kaylie , Yang, Brandon , Mehta, Hershel , Duan, Tony , Ding, Daisy , Bagul, Aarti , Langlotz, Curtis P. , Patel, Bhavik N. , Yeom, Kristen W. , Shpanskaya, Katie , Blankenberg, Francis G. , Seekins, Jayne , Amrhein, Timothy J. , Mong, David A. , Halabi, Safwan S. , Zucker, Evan J. , Ng, Andrew Y. and Lungren, Matthew P.
Publisher
United States: Public Library of Science
Journal title
Language
English
Formats
Publication information
Publisher
United States: Public Library of Science
Subjects
More information
Scope and Contents
Contents
Chest radiograph interpretation is critical for the detection of thoracic diseases, including tuberculosis and lung cancer, which affect millions of people worldwide each year. This time-consuming task typically requires expert radiologists to read the images, leading to fatigue-based diagnostic error and lack of diagnostic expertise in areas of th...
Alternative Titles
Full title
Deep learning for chest radiograph diagnosis: A retrospective comparison of the CheXNeXt algorithm to practicing radiologists
Authors, Artists and Contributors
Author / Creator
Irvin, Jeremy
Ball, Robyn L.
Zhu, Kaylie
Yang, Brandon
Mehta, Hershel
Duan, Tony
Ding, Daisy
Bagul, Aarti
Langlotz, Curtis P.
Patel, Bhavik N.
Yeom, Kristen W.
Shpanskaya, Katie
Blankenberg, Francis G.
Seekins, Jayne
Amrhein, Timothy J.
Mong, David A.
Halabi, Safwan S.
Zucker, Evan J.
Ng, Andrew Y.
Lungren, Matthew P.
Identifiers
Primary Identifiers
Record Identifier
TN_cdi_plos_journals_2252256310
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_plos_journals_2252256310
Other Identifiers
ISSN
1549-1676,1549-1277
E-ISSN
1549-1676
DOI
10.1371/journal.pmed.1002686
