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Articles Published Processes
12/17/2024 9:21:50 AM | Browse: 59 | Download: 125
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Received |
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2024-07-19 15:27 |
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Peer-Review Started |
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2024-07-19 15:27 |
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To Make the First Decision |
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Return for Revision |
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2024-10-09 03:02 |
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Revised |
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2024-10-21 15:57 |
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Second Decision |
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2024-11-26 02:41 |
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Accepted by Journal Editor-in-Chief |
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Accepted by Executive Editor-in-Chief |
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2024-11-26 08:58 |
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Articles in Press |
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2024-11-26 08:58 |
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Publication Fee Transferred |
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2024-10-24 17:21 |
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Edit the Manuscript by Language Editor |
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Typeset the Manuscript |
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2024-12-10 00:47 |
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Publish the Manuscript Online |
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2024-12-17 09:21 |
| ISSN |
2218-5836 (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: https://creativecommons.org/Licenses/by-nc/4.0/ |
| Copyright |
© The Author(s) 2024. 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 |
Computer Science, Artificial Intelligence |
| Manuscript Type |
Case Control Study |
| Article Title |
Utilization of artificial intelligence in the diagnosis of pes planus and pes cavus with a smartphone camera
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| Manuscript Source |
Unsolicited Manuscript |
| All Author List |
Samir Ghandour, Anton Lebedev, Wei-Shao Tung, Konstantin Semianov, Artem Semjanow, Christopher W DiGiovanni, Soheil Ashkani-Esfahani and Lorena Bejarano Pineda |
| ORCID |
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| Funding Agency and Grant Number |
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| Corresponding Author |
Christopher W DiGiovanni, MD, Department of Orthopaedic Surgery, Massachusetts General Hospital, 55 Fruit Street, Boston, MA 02114, United States. samir.g.ghandour@gmail.com |
| Key Words |
Artificial intelligence; Computer vision; Three-dimensional scanning; Lower extremity; High-arch; Flatfoot |
| Core Tip |
The study demonstrates the integration of a deep convolutional neural network (CNN) with smartphone cameras to diagnose pes planus and pes cavus, common foot deformities, with high accuracy. By utilizing a non-invasive and accessible screening tool, this method eliminates the need for traditional radiographic assessments, making it particularly beneficial for underserved communities. The CNN model showed high specificity and sensitivity, suggesting its potential for early detection and management of foot arch deformities, ultimately enhancing patient care and reducing healthcare costs. |
| Publish Date |
2024-12-17 09:21 |
| Citation |
<p>Ghandour S, Lebedev A, Tung WS, Semianov K, Semjanow A, DiGiovanni CW, Ashkani-Esfahani S, Pineda LB. Utilization of artificial intelligence in the diagnosis of pes planus and pes cavus with a smartphone camera. <i>World J Orthop</i> 2024; 15(12): 1146-1154</p> |
| URL |
https://www.wjgnet.com/2218-5836/full/v15/i12/1146.htm |
| DOI |
https://dx.doi.org/10.5312/wjo.v15.i12.1146 |
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