A Primer on the Use of Artificial Intelligence in Spine Surgery
- PMID: 34050043
- DOI: 10.1097/BSD.0000000000001211
A Primer on the Use of Artificial Intelligence in Spine Surgery
Abstract
Design: This was a narrative review.
Purpose: Summarize artificial intelligence (AI) fundamentals as well as current and potential future uses in spine surgery.
Summary of background data: Although considered futuristic, the field of AI has already had a profound impact on many industries, including health care. Its ability to recognize patterns and self-correct to improve over time mimics human cognitive function, but on a much larger scale.
Methods: Review of literature on AI fundamentals and uses in spine pathology.
Results: Machine learning (ML), a subset of AI, increases in hierarchy of complexity from classic ML to unsupervised ML to deep leaning, where Language Processing and Computer Vision are possible. AI-based tools have been developed to segment spinal structures, acquire basic spinal measurements, and even identify pathology such as tumor or degeneration. AI algorithms could have use in guiding clinical management through treatment selection, patient-specific prognostication, and even has the potential to power neuroprosthetic devices after spinal cord injury.
Conclusion: While the use of AI has pitfalls and should be adopted with caution, future use is promising in the field of spine surgery and medicine as a whole.
Level of evidence: Level IV.
Copyright © 2021 Wolters Kluwer Health, Inc. All rights reserved.
Conflict of interest statement
Y.K.: Ownership Interest in Radius. T.J.A.: Royalties from Zimmer Biomet, DePuy Synthes Spine; Consulting Fees from Nuvasive, DePuy Synthes; Book Royalties from JP Medical Publishers, Thieme Medical Publishers, Springer, Elsevier Inc.; Ownership Interests in Innovative Surgical Designs Inc., Bonovo Orthopedics Inc., InVivo Therapeutics, Spinicity, CytoDyn Inc., Paradigm Spine, HS2 LLC, Strathspey Crown, Surg.IO LLC, Augmedics, Morphogenesis, Precision Orthopedics, Pulse Equity, Physician Recommended Neutriceuticals, Parvizi Surgical Innovations; Board member/Other office: Back Story LLC, Scoliosis Research Society, Spine Universe, American Orthopaedic Association. S.A.Q.: Consulting: Globus Medical Inc., Stryker K2M, Paradigm Spine (Past relationship); Royalties: Globus Medical Inc., Stryker K2M; Private Investments: Tissue Differentiation Intelligence, Vital 5 (Past relationship); Scientific Advisory Board: Healthgrades (Past relationship), Lifelink.Com Inc., Spinal Simplicity, LLC; Speaking and/or Teaching Arrangements: AMopportunities, Globus Medical Inc., RTI Surgical Inc.; Trips/Travel: Globus Medical Inc., Integrity Implants Inc., Medical Device Business Services, Medtronic USA Inc., Nuvasive Inc., Paradigm Spine, Stryker K2M; Board of Directors: Society Of Minimally Invasive Spine Surgery; Other Office: Annals Of Translational Medicine (Editorial Board Member), Association Of Bone And Joint Surgeons (Committee Member), Cervical Spine Research Society (Committee Member), Contemporary Spine Surgery (Editorial Board Member), International Society For The Advancement Of Spine Surgery (Committee Member), Lumbar Spine Research Society (Committee Member), Minimally Invasive Spine Study Group (Board Member), North American Spine Society (Committee Member), Simplify Medical Inc. (Clinical Events Committee Member), Society Of Minimally Invasive Spine Surgery (Committee Member, Board Member). The remaining authors declare no conflict of interest.
References
-
- Jiang F, Jiang Y, Zhi H, et al. Artificial intelligence in healthcare: past, present and future. Stroke Vasc Neurol. 2017;2:230–243.
-
- Hashimoto DA, Rosman G, Rus D, et al. Artificial intelligence in surgery: promises and perils. Ann Surg. 2018;268:70–76.
-
- Myers TG, Ramkumar PN, Ricciardi BF, et al. Artificial intelligence and orthopaedics: an introduction for clinicians. J Bone Joint Surg. 2020;102:830–840.
-
- Somashekhar SP, Sepúlveda M-J, Puglielli S, et al. Watson for Oncology and breast cancer treatment recommendations: agreement with an expert multidisciplinary tumor board. Ann Oncol. 2018;29:418–423.
-
- Gulshan V, Peng L, Coram M, et al. Development and validation of a deep learning algorithm for detection of diabetic retinopathy in retinal fundus photographs. JAMA. 2016;316:2402–2410.
Publication types
MeSH terms
LinkOut - more resources
Full Text Sources