Assessing the Accuracy of a Deep Learning Method to Risk Stratify Indeterminate Pulmonary Nodules-Reference-Cited by-同舟云学术

Assessing the Accuracy of a Deep Learning Method to Risk Stratify Indeterminate Pulmonary Nodules

Published:2020-07-15 Issue:2 Volume:202 Page:241-249
ISSN:1073-449X
Container-title:American Journal of Respiratory and Critical Care Medicine
language:en
Short-container-title:Am J Respir Crit Care Med

Author:

Massion Pierre P.¹²^ORCID,Antic Sanja¹,Ather Sarim³,Arteta Carlos⁴,Brabec Jan⁵,Chen Heidi⁶,Declerck Jerome⁴,Dufek David⁵,Hickes William³,Kadir Timor⁴,Kunst Jonas⁵,Landman Bennett A.⁷,Munden Reginald F.⁸,Novotny Petr⁴,Peschl Heiko³,Pickup Lyndsey C.⁴,Santos Catarina⁴,Smith Gary T.⁹¹⁰,Talwar Ambika³,Gleeson Fergus³

Affiliation:

1. Cancer Early Detection and Prevention Initiative, Vanderbilt Ingram Cancer Center, Division of Allergy, Pulmonary and Critical Care Medicine

2. Pulmonary and Critical Care Section, Medical Service, Veterans Affairs, and

3. Oxford University Hospitals NHS Foundation Trust, Oxford, United Kingdom

4. Optellum Ltd., Oxford, United Kingdom

5. Faculty of Medicine, Masaryk University, Brno, Czech Republic

6. Department of Biostatistics, and

7. Department of Electrical Engineering, Vanderbilt University, Nashville, Tennessee; and

8. Department of Radiology, Wake Forest Baptist Health, Winston Salem, North Carolina

9. Department of Radiology, Vanderbilt University School of Medicine, Nashville, Tennessee

10. Department of Radiology, Tennessee Valley Healthcare System, Nashville, Tennessee

Publisher

American Thoracic Society

Subject

Critical Care and Intensive Care Medicine,Pulmonary and Respiratory Medicine

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4. Recent Trends in the Identification of Incidental Pulmonary Nodules

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