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Articles Published Processes
6/17/2022 3:54:26 AM | Browse: 503 | Download: 1030
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Received |
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2021-11-30 12:14 |
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Peer-Review Started |
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2021-11-30 12:17 |
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To Make the First Decision |
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Return for Revision |
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2022-01-11 02:37 |
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Revised |
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2022-01-20 10:56 |
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Second Decision |
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2022-05-10 02:52 |
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Accepted by Journal Editor-in-Chief |
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Accepted by Executive Editor-in-Chief |
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2022-05-14 08:26 |
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Articles in Press |
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2022-05-14 08:26 |
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Publication Fee Transferred |
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Edit the Manuscript by Language Editor |
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Typeset the Manuscript |
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2022-06-08 23:50 |
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Publish the Manuscript Online |
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2022-06-17 03:54 |
| 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) 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 |
Orthopedics |
| Manuscript Type |
Retrospective Study |
| Article Title |
Evaluation of artificial intelligence models for osteoarthritis of the knee using deep learning algorithms for orthopedic radiographs
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| Manuscript Source |
Invited Manuscript |
| All Author List |
Anjali Tiwari, Murali Poduval and Vaibhav Bagaria |
| ORCID |
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| Funding Agency and Grant Number |
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| Corresponding Author |
Vaibhav Bagaria, FCPS, MBBS, MS, Director, Director, Department of Orthopedics, Sir H. N. Reliance Foundation Hospital and Research Centre, Raja Rammohan Roy Road, Prarthana Samaj, Mumbai 400004, India. bagariavaibhav@gmail.com |
| Key Words |
Osteoarthritis; Artificial intelligence; Knee; Computer vision; Machine leaning; Deep learning |
| Core Tip |
In this study, we evaluated different machine learning models to determine which model is best to suited classify the severity of osteoarthritis of the knee using the Kellgren Lawrence (KL) grading system. The image set was a radiograph of native knee in AP and lateral view. The radiographic images don’t include common visual disturbances such as implants, casts and other pathologies in medical images. All the radiographic images with clinical signs of osteoarthritis according to KL grades were selected. These radiographic exams were annotated by experts and tagged as per different classes according to KL grades. This study will pave the way for future development in the field with the development of more accurate models and tools which can improve medical image classification by Machines and will give valuable insight into orthopedic disease pathology. |
| Publish Date |
2022-06-17 03:54 |
| Citation |
Tiwari A, Poduval M, Bagaria V. Evaluation of artificial intelligence models for osteoarthritis of the knee using deep learning algorithms for orthopedic radiographs. World J Orthop 2022; 13(6): 603-614 |
| URL |
https://www.wjgnet.com/2218-5836/full/v13/i6/603.htm |
| DOI |
https://dx.doi.org/10.5312/wjo.v13.i6.603 |
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