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For: Sideris GA, Nikolakea M, Karanikola AE, Konstantinopoulou S, Giannis D, Modahl L. Imaging in the COVID-19 era: Lessons learned during a pandemic. World J Radiol 2021; 13(6): 192-222 [PMID: 34249239 DOI: 10.4329/wjr.v13.i6.192] [Cited by in CrossRef: 6] [Cited by in F6Publishing: 6] [Article Influence: 3.0] [Reference Citation Analysis]
Number Citing Articles
1 Giansanti D. The Regulation of Artificial Intelligence in Digital Radiology in the Scientific Literature: A Narrative Review of Reviews. Healthcare 2022;10:1824. [DOI: 10.3390/healthcare10101824] [Reference Citation Analysis]
2 Giansanti D, Di Basilio F. The Artificial Intelligence in Digital Radiology: Part 1: The Challenges, Acceptance and Consensus. Healthcare 2022;10:509. [DOI: 10.3390/healthcare10030509] [Cited by in Crossref: 5] [Cited by in F6Publishing: 5] [Article Influence: 5.0] [Reference Citation Analysis]
3 Glüer C, Krekiehn N, Yilmaz EB, Both M. Radiologische Diagnostik und Prognostik von COVID-19: Einsatz von künstlicher Intelligenz und Zusammenhang mit muskulo-skelettaler Bildgebung. Osteologie 2022;31:17-25. [DOI: 10.1055/a-1717-0955] [Reference Citation Analysis]
4 Orlandi D, Battaglini D, Lanza E, Bergamaschi G. Radiological Patterns and Lung Ultrasound. COVID-19 Critical and Intensive Care Medicine Essentials 2022. [DOI: 10.1007/978-3-030-94992-1_3] [Reference Citation Analysis]
5 Ali JK, Riches JC. The Impact of the COVID-19 Pandemic on Oncology Care and Clinical Trials. Cancers (Basel) 2021;13:5924. [PMID: 34885038 DOI: 10.3390/cancers13235924] [Cited by in Crossref: 7] [Cited by in F6Publishing: 7] [Article Influence: 3.5] [Reference Citation Analysis]