Open AccessApplications of Machine Learning to Imaging of Spinal Disorders: Current Status and Future Directions
Author(s) -
Zamir Merali,
Errol Colak,
Jefferson R. Wilson
Publication year - 2021
Publication title -
global spine journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.398
H-Index - 26
eISSN - 2192-5690
pISSN - 2192-5682
DOI - 10.1177/2192568220961353
Subject(s) - medicine , spinal deformity , narrative review , artificial intelligence , machine learning , medical physics , physical medicine and rehabilitation , deformity , surgery , computer science , intensive care medicine
Study Design: Narrative review.Objectives: We aim to describe current progress in the application of artificial intelligence and machine learning technology to provide automated analysis of imaging in patients with spinal disorders.Methods: A literature search utilizing the PubMed database was performed. Relevant studies from all the evidence levels have been included.Results: Within spine surgery, artificial intelligence and machine learning technologies have achieved near-human performance in narrow image classification tasks on specific datasets in spinal degenerative disease, spinal deformity, spine trauma, and spine oncology.Conclusion: Although substantial challenges remain to be overcome it is clear that artificial intelligence and machine learning technology will influence the practice of spine surgery in the future.