Clinical, Cultural, Computational, and Regulatory Considerations to Deploy AI in Radiology: Perspectives of RSNA and MICCAI Experts-Reference-Cited by-同舟云学术

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Clinical, Cultural, Computational, and Regulatory Considerations to Deploy AI in Radiology: Perspectives of RSNA and MICCAI Experts

Published:2024-07-01 Issue:4 Volume:6 Page:
ISSN:2638-6100
Container-title:Radiology: Artificial Intelligence
language:en
Short-container-title:Radiology: Artificial Intelligence

Author:

Linguraru Marius George^ORCID,Bakas Spyridon^ORCID,Aboian Mariam^ORCID,Chang Peter D.^ORCID,Flanders Adam E.^ORCID,Kalpathy-Cramer Jayashree^ORCID,Kitamura Felipe C.^ORCID,Lungren Matthew P.^ORCID,Mongan John^ORCID,Prevedello Luciano M.^ORCID,Summers Ronald M.^ORCID,Wu Carol C.^ORCID,Adewole Maruf^ORCID,Kahn Charles E.^ORCID

Publisher

Radiological Society of North America (RSNA)

Link

http://pubs.rsna.org/doi/pdf/10.1148/ryai.240225

Reference82 articles.

1. RSNA-MICCAI Panel Discussion: Machine Learning for Radiology from Challenges to Clinical Applications

2. RSNA-MICCAI Panel Discussion: 2. Leveraging the Full Potential of AI—Radiologists and Data Scientists Working Together

3. Code and Data Sharing Practices in the Radiology Artificial Intelligence Literature: A Meta-Research Study

4. Data Sharing of Imaging in an Evolving Health Care World: Report of the ACR Data Sharing Workgroup, Part 1: Data Ethics of Privacy, Consent, and Anonymization

5. Data Sharing of Imaging in an Evolving Health Care World: Report of the ACR Data Sharing Workgroup, Part 2: Annotation, Curation, and Contracting

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