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4/28/2022 12:02:15 PM | Browse: 324 | Download: 989
Publication Name Artificial Intelligence in Medical Imaging
Manuscript ID 74264
Country/Territory Italy
Received
2021-12-19 13:20
Peer-Review Started
2021-12-19 13:21
To Make the First Decision
Return for Revision
2022-02-10 17:38
Revised
2022-02-22 09:30
Second Decision
2022-04-26 02:16
Accepted by Journal Editor-in-Chief
Accepted by Company Editor-in-Chief
2022-04-26 22:05
Articles in Press
2022-04-26 22:05
Publication Fee Transferred
Edit the Manuscript by Language Editor
Typeset the Manuscript
2022-04-28 07:31
Publish the Manuscript Online
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
Permissions For details, please visit: http://www.wjgnet.com/bpg/gerinfo/207
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
Manuscript Source Invited Manuscript
All Author List Laura De Rosa, Serena L'Abbate, Claudia Kusmic and Francesco Faita
Funding Agency and Grant Number
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. kusmic@ifc.cnr.it., Pisa 56124, Italy. kusmic@ifc.cnr.it
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
Full Article (PDF) AIMI-3-42.pdf
Full Article (Word) AIMI-3-42.docx
Manuscript File 74264_Auto_Edited-LJH.docx
Answering Reviewers 74264-Answering reviewers.pdf
Audio Core Tip 74264-Audio core tip.mp3
Biostatistics Review Certificate 74264-Biostatistics statement.pdf
Conflict-of-Interest Disclosure Form 74264-Conflict-of-interest statement.pdf
Copyright License Agreement 74264-Copyright license agreement.pdf
Non-Native Speakers of English Editing Certificate 74264-Language certificate.pdf
Peer-review Report 74264-Peer-review(s).pdf
Scientific Misconduct Check 74264-Bing-Liu JH-2.jpg
Scientific Misconduct Check 74264-CrossCheck.jpg
Scientific Editor Work List 74264-Scientific editor work list.pdf