Editorial
Copyright ©The Author(s) 2024. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Orthop. Feb 18, 2024; 15(2): 105-109
Published online Feb 18, 2024. doi: 10.5312/wjo.v15.i2.105
Deep learning automation of radiographic patterns for hallux valgus diagnosis
Angela Hussain, Cadence Lee, Eric Hu, Farid Amirouche
Angela Hussain, Cadence Lee, Eric Hu, Department of Orthopaedic Surgery, University of Illinois College of Medicine, Chicago, IL 60612, United States
Farid Amirouche, Department of Orthopaedics Surgery, University of Illinois at Chicago, Chicago, IL 60612, United States
Farid Amirouche, Department of Orthopaedic Surgery, Northshore University Health System, Skokie, IL 6007, United States
Co-first authors: Angela Hussain and Cadence Lee.
Author contributions: Hussain A and Lee C contributed equally to this work as co-first authors; Hussain A, Lee C, Hu E, and Amirouche F contributed to this paper; Amirouche F and Lee C designed the concept and outline; Hussain A, Hu E, and Lee C contributed to the writing and review of literature; Amirouche F was responsible for oversight and coordination; and all authors contributed to the editing of the manuscript.
Conflict-of-interest statement: The authors have declared that no conflicts of interest exist.
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/
Corresponding author: Farid Amirouche, PhD, Professor, Department of Orthopedics Surgery, University of Illinois at Chicago, 835 S. Wolcott Ave, Room E270, Chicago, IL 60612, United States. amirouch@uic.edu
Received: November 30, 2023
Peer-review started: November 30, 2023
First decision: December 7, 2023
Revised: December 22, 2023
Accepted: January 4, 2024
Article in press: January 4, 2024
Published online: February 18, 2024
Processing time: 68 Days and 5.4 Hours
Core Tip

Core Tip: This editorial summarizes and outlines the original paper “Automated decision support for Hallux valgus treatment options using anteroposterior foot radiographs”. We summarize the scope of the deep learning process and compare it to existing artificial intelligence studies used in clinical diagnostic studies. We additionally describe its limitations and impact in the field of automated diagnostic tools.