Applications of Machine Learning to Imaging of Spinal Disorders: Current Status and Future Directions

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.