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4/28/2022 12:02:15 PM | Browse: 372 | Download: 1137
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2021-12-19 13:20 |
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Peer-Review Started |
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2021-12-19 13:21 |
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2022-02-10 17:38 |
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Revised |
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2022-02-22 09:30 |
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Second Decision |
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2022-04-26 02:16 |
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Accepted by Journal Editor-in-Chief |
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2022-04-26 22:05 |
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Articles in Press |
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2022-04-26 22:05 |
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2022-04-28 07:31 |
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Publish the Manuscript Online |
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2022-04-28 11:54 |
ISSN |
2644-3260 (online) |
Open Access |
This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/ |
Copyright |
©The Author(s) 2022. Published by Baishideng Publishing Group Inc. All rights reserved. |
Article Reprints |
For details, please visit: http://www.wjgnet.com/bpg/gerinfo/247
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Permissions |
For details, please visit: http://www.wjgnet.com/bpg/gerinfo/207
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Publisher |
Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA |
Website |
http://www.wjgnet.com |
Category |
Radiology, Nuclear Medicine & Medical Imaging |
Manuscript Type |
Systematic Reviews |
Article Title |
Applications of artificial intelligence in lung ultrasound: Review of deep learning methods for COVID-19 fighting
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Manuscript Source |
Invited Manuscript |
All Author List |
Laura De Rosa, Serena L'Abbate, Claudia Kusmic and Francesco Faita |
Funding Agency and Grant Number |
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Corresponding Author |
Claudia Kusmic, MSc, PhD, Research Scientist, Institute of Clinical Physiology, National Research Council (CNR), Consiglio Nazionale delle Ricerche, Institute of Clinical Physiology,Via Giuseppe Moruzzi 1, Pisa 56124, Italy. [email protected]., Pisa 56124, Italy. [email protected] |
Key Words |
Lung ultrasound; Deep learning; Neural network; COVID-19 pneumonia; Medical imaging |
Core Tip |
Challenging coronavirus disease 2019 (COVID-19) pandemic through the identification of effective diagnostic and prognostic tools is of outstanding importance to tackle the healthcare system burdening and improve clinical outcomes. Application of deep learning (DL) in medical lung ultrasound may offer the advantage of combining non-invasiveness and wide accessibility of ultrasound imaging techniques with higher diagnostic performance and classification accuracy. This paper overviews the current applications of DL models in medical lung ultrasound imaging in COVID-19 patients, and highlight the existing challenges associated with the effective clinical application of automated systems in the medical imaging field. |
Publish Date |
2022-04-28 11:54 |
Citation |
De Rosa L, L'Abbate S, Kusmic C, Faita F. Applications of artificial intelligence in lung ultrasound: Review of deep learning methods for COVID-19 fighting. Artif Intell Med Imaging 2022; 3(2): 42-54 |
URL |
https://www.wjgnet.com/2644-3260/full/v3/i2/42.htm |
DOI |
https://dx.doi.org/10.35711/aimi.v3.i2.42 |
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