Publication Name	World Journal of Orthopedics
Manuscript ID	99286
Country	United States

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
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
Funding Agency and Grant Number
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.
Citation	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. World J Orthop 2024; In press

Received	2024-07-19 15:27
Peer-Review Started	2024-07-19 15:27
To Make the First Decision
Return for Revision	2024-10-09 03:02
Revised	2024-10-21 15:57
Second Decision	2024-11-26 02:41
Accepted by Journal Editor-in-Chief
Accepted by Executive Editor-in-Chief	2024-11-26 08:58
Articles in Press	2024-11-26 08:58
Publication Fee Transferred	2024-10-24 17:21
Edit the Manuscript by Language Editor
Typeset the Manuscript

ISSN	2218-5836 (online)
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