Overview of Noninterpretive Artificial Intelligence Models for Safety, Quality, Workflow, and Education Applications in Radiology Practice-Reference-Cited by-同舟云学术

Overview of Noninterpretive Artificial Intelligence Models for Safety, Quality, Workflow, and Education Applications in Radiology Practice

Published:2022-03-01 Issue:2 Volume:4 Page:
ISSN:2638-6100
Container-title:Radiology: Artificial Intelligence
language:en
Short-container-title:Radiology: Artificial Intelligence

Author:

Tadavarthi Yasasvi¹^ORCID,Makeeva Valeria¹^ORCID,Wagstaff William¹^ORCID,Zhan Henry¹,Podlasek Anna¹^ORCID,Bhatia Neil¹^ORCID,Heilbrun Marta¹^ORCID,Krupinski Elizabeth¹^ORCID,Safdar Nabile¹^ORCID,Banerjee Imon¹^ORCID,Gichoya Judy¹^ORCID,Trivedi Hari¹^ORCID

Affiliation:

1. From the Department of Medicine, Medical College of Georgia, Augusta, Ga (Y.T.); Department of Radiology and Imaging Sciences (V.M., W.W., H.Z., M.H., E.K., N.S., J.G., H.T.), School of Medicine (N.B.), and Department of Biomedical Informatics (I.B.), Emory University, 1364 E Clifton Rd NE, Atlanta, GA 30322; and Southend University Hospital NHS Foundation Trust, Westcliff-on-Sea, UK (A.P.).

Publisher

Radiological Society of North America (RSNA)

Subject

Artificial Intelligence,Radiology, Nuclear Medicine and imaging,Radiological and Ultrasound Technology

Link

http://pubs.rsna.org/doi/pdf/10.1148/ryai.210114

Reference127 articles.

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4. Radiologists’ Variation of Time to Read Across Different Procedure Types

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