Applications of Machine Learning to Imaging of Spinal Disorders: Current Status and Future Directions. Issue 1 (April 2021)

• Record Type: Journal Article
• Authors: Merali, Zamir A.; Colak, Errol; Wilson, Jefferson R.
• Is Part Of: Global spine journal. Volume 11:Issue 1(2021)Supplement
• Page Start: 23S
• Page End: 29S
• Publication Date: 2021-04
• Subjects: cervical -- lumbar -- thoracic -- MRI -- degenerative; Spine -- Diseases -- Periodicals; Spine -- Diseases -- Treatment -- Periodicals; Spine -- Abnormalities -- Periodicals; Spine -- Surgery -- Periodicals; 616.73
• DOI: 10.1177/2192568220961353
• Languages: English
• ISSNs: 2192-5682

Abstract

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.