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Toossi et al. Art Int Surg 2024;4:258-66                                        Artificial
               DOI: 10.20517/ais.2024.27
                                                                               Intelligence Surgery




               Review                                                                        Open Access



               Machine learning applications in adult spinal
               deformity corrective surgery: a narrative review


               Nader Toossi 1  , Ozhan Jerry 2
               1
                Musculoskeletal Education and Research Center, Clinical Research, Audubon, PA 19403, USA.
               2
                University of New England, College of Dental Medicine, Portland, ME O4103, USA.
               Correspondence to: Dr. Nader Toossi, Musculoskeletal Education and Research Center, Clinical Research, 2560 General
               Armistead Avenue, Audubon, PA 19403, USA. E-mail: nt392@drexel.edu
               How to cite this article: Toossi N, Jerry O. Machine learning applications in adult spinal deformity corrective surgery: a narrative
               review. Art Int Surg 2024;4:258-66. https://dx.doi.org/10.20517/ais.2024.27
               Received: 6 May 2024  First Decision: 25 Jul 2024  Revised: 24 Aug 2024  Accepted: 9 Sep 2024  Published: 13 Sep 2024

               Academic Editor: Andrew A. Gumbs  Copy Editor: Dong-Li Li  Production Editor: Dong-Li Li


               Abstract
               Adult spinal deformity (ASD) poses significant challenges in spinal surgery, requiring precise planning and
               execution for successful correction. Additionally, optimization of outcomes and reducing the high complication
               rates of ASD surgeries are additional challenges facing spinal deformity surgeons. The advent of machine learning
               (ML)  has  revolutionized  various  aspects  of  healthcare,  including  spinal  surgery.  This  review  provides  a
               comprehensive overview of the current state of ML applications in spinal deformity corrective surgery, highlighting
               its potential benefits and challenges.

               Keywords: Machine learning, adult spinal deformity, predictive modeling, artificial intelligence



               INTRODUCTION
               With the aging population, the incidence and prevalence of adult spinal deformity (ASD) are on the rise ,
                                                                                                        [1]
               affecting millions worldwide and significantly impacting their quality of life. This often leads to the
               necessity of complex surgical interventions. Planning ASD surgery involves evaluating not only the entire
               spinal column but also the entirety of the skeleton to ensure appropriate radiographic alignment. ASD
               patients present with a variety of heterogeneous clinical manifestations, and there is a vast array of surgical
               methods available for their treatment, making the treatment algorithm quite complex. Additionally, ASD







                           © The Author(s) 2024. Open Access This article is licensed under a Creative Commons Attribution 4.0
                           International License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, sharing,
                           adaptation, distribution and reproduction in any medium or format, for any purpose, even commercially, as
               long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and
               indicate if changes were made.

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