Artificial intelligence: radiologists’ expectations and opinions gleaned from a nationwide online survey-Reference-Cited by-同舟云学术

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Artificial intelligence: radiologists’ expectations and opinions gleaned from a nationwide online survey

Published:2020-04-29 Issue:1 Volume:126 Page:63-71
ISSN:0033-8362
Container-title:La radiologia medica
language:en
Short-container-title:Radiol med

Author:

Coppola Francesca,Faggioni Lorenzo,Regge Daniele,Giovagnoni Andrea,Golfieri Rita,Bibbolino Corrado,Miele Vittorio,Neri Emanuele,Grassi Roberto

Publisher

Springer Science and Business Media LLC

Subject

Radiology, Nuclear Medicine and imaging,General Medicine

Link

https://link.springer.com/content/pdf/10.1007/s11547-020-01205-y.pdf

Reference30 articles.

1. Yu KH, Beam AL, Kohane IS (2018) Artificial intelligence in healthcare. Nat Biomed Eng 2:719–731. https://doi.org/10.1038/s41551-018-0305-z

2. Chartrand G, Cheng PM, Vorontsov E, Drozdzal M, Turcotte S, Pal CJ, Kadoury S, Tang A (2017) Deep learning: a primer for radiologists. Radiographics 37:2113–2131. https://doi.org/10.1148/rg.2017170077

3. Kohli M, Prevedello LM, Filice RW, Geis JR (2017) Implementing machine learning in radiology practice and research. AJR Am J Roentgenol 208:754–760. https://doi.org/10.2214/AJR.16.17224

4. European Society of Radiology (ESR) (2019) What the radiologist should know about artificial intelligence—an ESR white paper. Insights Imaging 10:44. https://doi.org/10.1186/s13244-019-0738-2

5. Pesapane F, Codari M, Sardanelli F (2018) Artificial intelligence in medical imaging: threat or opportunity? Radiologists again at the forefront of innovation in medicine. Eur Radiol Exp 2:35. https://doi.org/10.1186/s41747-018-0061-6

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