Content area
Abstract
Using AI to Interpret Medical Images
The authors examine the advantages and limitations of current clinical radiologic AI systems, new clinical workflows, and the potential effect of generative AI and large multimodal foundation models.
Details
Title
The Current and Future State of AI Interpretation of Medical Images
Author
Rajpurkar, Pranav
; Lungren, Matthew P 1
1 From the Department of Biomedical Informatics, Harvard Medical School, Boston (P.R.); the Center for Artificial Intelligence in Medicine and Imaging, Stanford University, Stanford, and the Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco — both in California (M.P.L.); and Microsoft, Redmond, Washington (M.P.L.).
; Lungren, Matthew P 1 1 From the Department of Biomedical Informatics, Harvard Medical School, Boston (P.R.); the Center for Artificial Intelligence in Medicine and Imaging, Stanford University, Stanford, and the Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco — both in California (M.P.L.); and Microsoft, Redmond, Washington (M.P.L.).
Pages
1981-1990
Section
Review Article
Publication year
2023
Publication date
May 25, 2023
Website
ISSN
00284793
e-ISSN
15334406
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2818870035
Copyright
Copyright © 2023 Massachusetts Medical Society. All rights reserved.