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Cited by in F6Publishing
For: Sandino CM, Cole EK, Alkan C, Chaudhari AS, Loening AM, Hyun D, Dahl J, Imran AA, Wang AS, Vasanawala SS. Upstream Machine Learning in Radiology. Radiol Clin North Am 2021;59:967-85. [PMID: 34689881 DOI: 10.1016/j.rcl.2021.07.009] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 0.5] [Reference Citation Analysis]
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1 Perchik JD, Rothenberg SA, Tridandapani S, Perchik LM, Smith AD. Artificial Intelligence in Body Imaging: An Overview of Commercially Available Tools. Seminars in Roentgenology 2023. [DOI: 10.1053/j.ro.2023.02.007] [Reference Citation Analysis]
2 Hirvonen J, Heikkinen J, Nyman M, Happonen T, Velhonoja J, Irjala H, Soukka T, Mattila K, Nurminen J. MRI of acute neck infections: evidence summary and pictorial review. Insights Imaging 2023;14:5. [PMID: 36617619 DOI: 10.1186/s13244-022-01347-9] [Reference Citation Analysis]
3 Irmici G, Cè M, Caloro E, Khenkina N, Della Pepa G, Ascenti V, Martinenghi C, Papa S, Oliva G, Cellina M. Chest X-ray in Emergency Radiology: What Artificial Intelligence Applications Are Available? Diagnostics (Basel) 2023;13. [PMID: 36673027 DOI: 10.3390/diagnostics13020216] [Reference Citation Analysis]
4 Imran A, Pal D, Wang S, Dutta S, Zucker E, Wang A. Personalized CT organ noise estimation from scout images. Medical Imaging 2022: Physics of Medical Imaging 2022. [DOI: 10.1117/12.2610986] [Reference Citation Analysis]