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Page 252                                                         Elhage et al. Art Int Surg. 2025;5:247-53  https://dx.doi.org/10.20517/ais.2024.87

               analysis, image analysis, and generative AI, and we encourage AWR surgeons to pursue future AI research.


               DECLARATIONS
               Authors’ contributions
               Involved in study designs, critically drafting, and editing the manuscript: Elhage SA, Terry PH, Villavisanis
               D, Fischer JP, Percec I

               Availability of data and materials
               Publicly available.


               Financial support and sponsorship
               None.


               Conflicts of interest
               Fischer JP reports receiving funding from 3M, Becton, Dickinson, Integra, Gore, and Allergan for speaking
               and teaching, honoraria, and consulting fees, as well as National Center for Advancing Translational
               Sciences of the National Institutes of Health, R01 grant. Percec I is a consultant and trainer for Allergan and
               Galderma and a consultant for AlumierMD and Pierre Fabre Dermocosmetique. The other authors declared
               that there are no conflicts of interest.

               Ethical approval and consent to participate
               Not applicable.

               Consent for publication
               Not applicable.

               Copyright
               © The Author(s) 2025.

               REFERENCES
               1.       Lima DL, Kasakewitch J, Nguyen DQ, et al. Machine learning, deep learning and hernia surgery. Are we pushing the limits of
                   abdominal core health? A qualitative systematic review. Hernia. 2024;28:1405-12.  DOI  PubMed
               2.       Chilamkurthy S, Ghosh R, Tanamala S, et al. Deep learning algorithms for detection of critical findings in head CT scans: a
                   retrospective study. Lancet. 2018;392:2388-96.  DOI  PubMed
               3.       Gong D, Wu L, Zhang J, et al. Detection of colorectal adenomas with a real-time computer-aided system (ENDOANGEL): a
                   randomised controlled study. Lancet Gastroenterol Hepatol. 2020;5:352-61.  DOI  PubMed
               4.       Gulshan V, Peng L, Coram M, et al. Development and validation of a deep learning algorithm for detection of diabetic retinopathy in
                   retinal fundus photographs. JAMA. 2016;316:2402-10.  DOI  PubMed
               5.       Esteva A, Kuprel B, Novoa RA, et al. Dermatologist-level classification of skin cancer with deep neural networks. Nature.
                   2017;542:115-8.  DOI  PubMed  PMC
               6.       Hassan AM, Biaggi-Ondina A, Asaad M, et al. Artificial intelligence modeling to predict periprosthetic infection and explantation
                   following implant-based reconstruction. Plast Reconstr Surg. 2023;152:929-38.  DOI  PubMed
               7.       Mavioso C, Araújo RJ, Oliveira HP, et al. Automatic detection of perforators for microsurgical reconstruction. Breast. 2020;50:19-24.
                   DOI  PubMed  PMC
               8.       Kenig N, Monton Echeverria J, De la Ossa L. Identification of key breast features using a neural network: applications of machine
                   learning in the clinical setting of plastic surgery. Plast Reconstr Surg. 2024;153:273e-80e.  DOI  PubMed
               9.       Loftus TJ, Tighe PJ, Filiberto AC, et al. Artificial intelligence and surgical decision-making. JAMA Surg. 2020;155:148-58.  DOI
                   PubMed  PMC
               10.     Gumbs AA, Parretta S, d’Allemagne B, Chouillard E. What is artificial intelligence surgery? Artif Intell Surg. 2021;1:1-10.  DOI
               11.      Choi RY, Coyner AS, Kalpathy-Cramer J, Chiang MF, Campbell JP. Introduction to machine learning, neural networks, and deep
                   learning. Transl Vis Sci Technol. 2020;9:14. Available from: https://www.researchgate.net/publication/344419928_Introduction_to_
                   Machine_Learning_Neural_Networks_and_Deep_Learning. [Last accessed on 22 May 2025]
               12.      TerKonda SP, TerKonda AA, Sacks JM, et al. Artificial intelligence: singularity approaches. Plast Reconstr Surg. 2024;153:204e-17e.
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