Chest Radiograph Interpretation with Deep Learning Models: Assessment with Radiologist-adjudicated Reference Standards and Population-adjusted Evaluation-Reference-Cited by-同舟云学术

Chest Radiograph Interpretation with Deep Learning Models: Assessment with Radiologist-adjudicated Reference Standards and Population-adjusted Evaluation

Published:2020-02 Issue:2 Volume:294 Page:421-431
ISSN:0033-8419
Container-title:Radiology
language:en
Short-container-title:Radiology

Author:

Majkowska Anna¹^ORCID,Mittal Sid¹^ORCID,Steiner David F.¹^ORCID,Reicher Joshua J.¹^ORCID,McKinney Scott Mayer¹^ORCID,Duggan Gavin E.¹^ORCID,Eswaran Krish¹^ORCID,Cameron Chen Po-Hsuan¹^ORCID,Liu Yun¹^ORCID,Kalidindi Sreenivasa Raju¹^ORCID,Ding Alexander¹^ORCID,Corrado Greg S.¹^ORCID,Tse Daniel¹^ORCID,Shetty Shravya¹^ORCID

Affiliation:

1. From Google Health, 1600 Amphitheatre Pkwy, Mountain View, CA 94043 (A.M., S.M., D.F.S., S.M.M., G.E.D., K.E., P.H.C.C., Y.L., G.S.C., D.T., S.S.); Stanford Healthcare and Palo Alto Veterans Affairs, Palo Alto, Calif (J.J.R.); Apollo Radiology International, Hyderabad, India (S.R.K.); and California Advanced Imaging, Novato, Calif (A.D.).

Publisher

Radiological Society of North America (RSNA)

Subject

Radiology Nuclear Medicine and imaging

Link

http://pubs.rsna.org/doi/pdf/10.1148/radiol.2019191293

Reference33 articles.

1. Deep learning in radiology: An overview of the concepts and a survey of the state of the art with focus on MRI

2. Deep Learning in Radiology

3. Automated Triaging of Adult Chest Radiographs with Deep Artificial Neural Networks

4. Deep learning for chest radiograph diagnosis: A retrospective comparison of the CheXNeXt algorithm to practicing radiologists

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