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An ASER AI/ML expert panel formative user research study for an interpretable interactive splenic AAST grading graphical user interface prototype.
Emerg Radiol. 2024 Apr;31(2):167-178. doi: 10.1007/s10140-024-02202-8. Epub 2024 Feb 2.
Emerg Radiol. 2024.
PMID: 38302827
Free PMC article.
Artificial intelligence in emergency and trauma radiology: ASER AI/ML expert panel Delphi consensus statement on research guidelines, practices, and priorities.
Dreizin D, Khatri G, Staziaki PV, Buch K, Underbath M, Mohammed M, Sodickson A, Khurana B, Agrawal A, Spann JS, Beckmann N, DelProposto Z, LeBedis CA, Davis M, Dickerson G, Lev M.
Dreizin D, et al.
Emerg Radiol. 2024 Dec 23. doi: 10.1007/s10140-024-02306-1. Online ahead of print.
Emerg Radiol. 2024.
PMID: 39714735
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