The application of artificial intelligence in the acute and sub-acute phases of spinal cord injury- a systematic review.

Authors

• Teleale F Gebeyehu
• Mohammad Amin Sabbaghalvani
• Giovanna Failla
• Ashmal S Kabani
• Yashvi Shah
• Alexander Kharichev
• Joshua A Dian
• Stavros Matsoukas
• Alexander R Vaccaro
• Gregory D Schroeder
• Srinivas K Prasad
• Jack Jallo
• Joshua E Heller
• Michael G Fehlings
• James S Harrop

Publication/Presentation Date

1-1-2026

Abstract

STUDY DESIGN: Systematic Review.

OBJECTIVE: To describe applications of AI for traumatic SCI management with focus on diagnostics, prognostication, and therapeutic interventions.

METHODS: PubMed, Scopus and Cochrane libraries were searched (March 2025). Studies published in English between January 1

RESULTS: 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.

CONCLUSION: 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. These functions complement clinical judgement.

Volume

64

Issue

1

First Page

3

Last Page

13

ISSN

1476-5624

Published In/Presented At

Gebeyehu, T. F., Sabbaghalvani, M. A., Failla, G., Kabani, A. S., Shah, Y., Kharichev, A., Dian, J. A., Matsoukas, S., Vaccaro, A. R., Schroeder, G. D., Prasad, S. K., Jallo, J., Heller, J. E., Fehlings, M. G., & Harrop, J. S. (2026). The application of artificial intelligence in the acute and sub-acute phases of spinal cord injury- a systematic review. Spinal cord, 64(1), 3–13. https://doi.org/10.1038/s41393-025-01155-0

Disciplines

Business Administration, Management, and Operations | Health and Medical Administration | Management Sciences and Quantitative Methods

PubMedID

41345782

Department(s)

Administration and Leadership

Document Type

Article