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Studies published in English between January 1\n                      <jats:sup>st<\/jats:sup>\n                      , 2020, and March 18, 2025, dealing with clinical aspects in the acute, post-injury rehabilitative and first year phases of SCI were included. Studies on brain computer interface, robotics and non-neurologic aspects of SCI were excluded. Extracted were country of study, study design, focus of study, total participants, American Spinal Injury Association (ASIA) Impairment Scale (AIS), machine learning (ML) models, inputs, outcomes and performance metrices.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>A total of 23 studies with 120,931 individuals were identified. Classical Machine Learning Models, Ensemble Learning Models and Deep Learning Models were the most used ML families. Age, AIS, neurologic level of injury, sex, mechanism of injury and motor score were the most common inputs. Predictions of neurologic status, functionality status, Hospital\/ICU utilizations, complications, survival, discharge destination and results of image segmentation and patient grouping were the outputs of interest. The performance metrices were satisfactory in most and higher than humans in some studies.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>AI can facilitate personalized approach to diagnosis of SCI, prediction of outcomes like neurological improvement, complications, functionality indicators like walking, selfcare and independence, re-admissions, prolonged length of stays, discharge destination and mortality after injury. It was also useful to suggest specific MAP goals and time of surgical intervention. 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Gebeyehu - None; Mohammad Amin Sabbaghalvani - None; Giovanna Failla - None; Ashmal S. Kabani - None; Yashvi Shah - None; Alexander Kharichev - None; Joshua Dian - None; Stavros Matsoukas - None Alexander R. Vaccaro - Receives royalties from Stryker, Globus, Medtronic, Atlas Spine, Alphatec Spine, SpineWave, Spinal Elements, Curiteva, Elsevier, Jaypee, Stout Medical, Taylor Francis\/Hodder and Stoughton, Wolters Kluwer, Wheel House Medical, and Thieme; has stock or stock options in Accelus, Advanced Spinal Intellectual Properties, Atlas Spine, Avaz Surgical, AVKN Patient Driven Care, Cytonics, Deep Health, Dimension Orthotics LLC, Electrocore, Flagship Surgical, FlowPharma, Rothman Institute and Related Properties, Globus, Harvard MedTech, Innovative Surgical Design, Jushi (Haywood), Orthobullets, Parvizi Surgical Innovation, Progressive Spinal Technologies, Sentryx, Stout Medical, See All AI, and ViewFi Health; is a consultant for Curiteva, Medcura, Stryker, Globus, Spinal Elements, Accelus, Wheel House Medical, and Ferring Pharmaceutical; Serves on Scientific Advisory Board \/ Board of Directors \/ Committee for National Spine Health Foundation (NSHF), Sentryx, and Accelus; and is a member in good standing\/independent contractor for AO Spine Gregory D. Schroeder - Consults for camber spine, AO Spine; Research support from AO Spine; Editor in Chief Clinical Spine surgery; Royalties for camber spine; Ownership in Rothman institute, Rothman ASCs, Harmoni Neuromonitoring, comprehensive spinal solutions; Family member with ownership in Altus Spine. Srinivas K. Prasad \u2013 Received grants from AO Spine and NREF for spine fellowship funding; Royalties from Striker Spine; Consulting Fees from MiRUS Spine, Stryker Spine and Depuy Synthes; Received Honoraria from Depuy Synthes and Striker Spine. Jack Jallo - None; Joshua Heller - None; James Harrop \u2013 None. Michael G. Fehlings \u2013 Co-author of this study and editor-in-Chief of Spinal Cord. He was not involved in handling this manuscript during the submission and review processes.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}]}}