Artificial intelligence in spine surgery
- PMID: 35902390
- DOI: 10.1007/s00264-022-05517-8
Artificial intelligence in spine surgery
Abstract
The continuous progress of research and clinical trials has offered a wide variety of information concerning the spine and the treatment of the different spinal pathologies that may occur. Planning the best therapy for each patient could be a very difficult and challenging task as it often requires thorough processing of the patient's history and individual characteristics by the clinician. Clinicians and researchers also face problems when it comes to data availability due to patients' personal information protection policies. Artificial intelligence refers to the reproduction of human intelligence via special programs and computers that are trained in a way that simulates human cognitive functions. Artificial intelligence implementations to daily clinical practice such as surgical robots that facilitate spine surgery and reduce radiation dosage to medical staff, special algorithms that can predict the possible outcomes of conservative versus surgical treatment in patients with low back pain and disk herniations, and systems that create artificial populations with great resemblance and similar characteristics to real patients are considered to be a novel breakthrough in modern medicine. To enhance the body of the related literature and inform the readers on the clinical applications of artificial intelligence, we performed this review to discuss the contribution of artificial intelligence in spine surgery and pathology.
Keywords: Artificial intelligence; Machine learning; Spine; Surgery; Surgical robots.
© 2022. The Author(s) under exclusive licence to SICOT aisbl.
References
-
- Russell S, Norvig P (2005) AI a modern approach. Learning 2(3):4
-
- Samuel AL (1959) Some studies in machine learning using game of checkers. J Res Dev 3(3):210–229
-
- Foley KT, Gupta SK (2002) Percutaneous pedicle screw fixation of the lumbar spine: preliminary clinical results. J Neurosurg Spine 97:7–12 - DOI
-
- Winder MJ, Gilhooly PM (2017) Accuracy of minimally invasive percutaneous thoracolumbar pedicle screws using 2D fluoroscopy: a retrospective review through 3D CT analysis. J Spine Surg 3:193–203 - DOI
-
- Verma R, Krishan S, Haendlmayer K, Mohsen A (2010) Functional outcome of computer-assisted spinal pedicle screw placement: a systematic review and meta-analysis of 23 studies including 5,992 pedicle screws. Eur Spine J 19:370–375 - DOI
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