A Federated Registration System for Artificial Intelligence in Health.
Publication
, Journal Article
Pencina, MJ; McCall, J; Economou-Zavlanos, NJ
Published in: JAMA
September 10, 2024
Duke Scholars
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Published In
JAMA
DOI
EISSN
1538-3598
Publication Date
September 10, 2024
Volume
332
Issue
10
Start / End Page
789 / 790
Location
United States
Related Subject Headings
- United States
- Risk Evaluation and Mitigation
- Registries
- Practice Guidelines as Topic
- Humans
- General & Internal Medicine
- Federal Government
- Digital Health
- Artificial Intelligence
- 42 Health sciences
Citation
APA
Chicago
ICMJE
MLA
NLM
Pencina, M. J., McCall, J., & Economou-Zavlanos, N. J. (2024). A Federated Registration System for Artificial Intelligence in Health. JAMA, 332(10), 789–790. https://doi.org/10.1001/jama.2024.14026
Pencina, Michael J., Jonathan McCall, and Nicoleta J. Economou-Zavlanos. “A Federated Registration System for Artificial Intelligence in Health.” JAMA 332, no. 10 (September 10, 2024): 789–90. https://doi.org/10.1001/jama.2024.14026.
Pencina MJ, McCall J, Economou-Zavlanos NJ. A Federated Registration System for Artificial Intelligence in Health. JAMA. 2024 Sep 10;332(10):789–90.
Pencina, Michael J., et al. “A Federated Registration System for Artificial Intelligence in Health.” JAMA, vol. 332, no. 10, Sept. 2024, pp. 789–90. Pubmed, doi:10.1001/jama.2024.14026.
Pencina MJ, McCall J, Economou-Zavlanos NJ. A Federated Registration System for Artificial Intelligence in Health. JAMA. 2024 Sep 10;332(10):789–790.
Published In
JAMA
DOI
EISSN
1538-3598
Publication Date
September 10, 2024
Volume
332
Issue
10
Start / End Page
789 / 790
Location
United States
Related Subject Headings
- United States
- Risk Evaluation and Mitigation
- Registries
- Practice Guidelines as Topic
- Humans
- General & Internal Medicine
- Federal Government
- Digital Health
- Artificial Intelligence
- 42 Health sciences