Myths and facts about artificial intelligence: why machine- and deep-learning will not replace interventional radiologists-Reference-Cited by-同舟云学术

Myths and facts about artificial intelligence: why machine- and deep-learning will not replace interventional radiologists

Published:2020-04-03 Issue:5 Volume:37 Page:
ISSN:1357-0560
Container-title:Medical Oncology
language:en
Short-container-title:Med Oncol

Author:

Pesapane Filippo^ORCID,Tantrige Priyan,Patella Francesca^ORCID,Biondetti Pierpaolo,Nicosia Luca,Ianniello Andrea,Rossi Umberto G.,Carrafiello Gianpaolo,Ierardi Anna Maria

Publisher

Springer Science and Business Media LLC

Subject

Cancer Research,Oncology,Hematology,General Medicine

Link

http://link.springer.com/content/pdf/10.1007/s12032-020-01368-8.pdf

Reference81 articles.

1. Pesapane F. How scientific mobility can help current and future radiology research: a radiology trainee's perspective. Insights Imaging. 2019;10(1):85. https://doi.org/10.1186/s13244-019-0773-z.

2. Langlotz CP, Allen B, Erickson BJ, Kalpathy-Cramer J, Bigelow K, Cook TS, et al. A roadmap for foundational research on artificial intelligence in medical imaging: from the 2018 NIH/RSNA/ACR/The Academy Workshop. Radiology. 2019;291(3):781–91. https://doi.org/10.1148/radiol.2019190613.

3. Ranschaert ER, Sergey M, Algra PR. Artificial intelligence in medical imaging. Berlin: Springer; 2019.

4. Russell S, Bohannon J. Artificial intelligence. Fears of an AI pioneer. Science. 2015;349(6245):252. https://doi.org/10.1126/science.349.6245.252.

5. Pizzini FB, Pesapane F, Niessen W, Geerts-Ossevoort L, Broeckx N. ESMRMB Round table report on "Can Europe Lead in Machine Learning of MRI-Data?". MAGMA. 2020. https://doi.org/10.1007/s10334-019-00821-8.

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