Machine learning is a rapidly evolving field that offers physicians an innovative and comprehensive mechanism to examine various aspects of patient data. Cervical and lumbar degenerative spine disorders are commonly age-related disease processes that can utilize machine learning to improve patient outcomes with careful patient selection and intervention. The aim of this study is to examine the current applications of machine learning in cervical and lumbar degenerative spine disease. A systematic review was conducted using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. A search of PubMed, Embase, Medline, and Cochrane was conducted through May 31st, 2020, using the following terms: “artificial intelligence” OR “machine learning” AND “neurosurgery” AND “spine.” Studies were included if original research on machine learning was utilized in patient care for degenerative spine disease, including radiographic machine learning applications. Studies focusing on robotic applications in neurosurgery, navigation, or stereotactic radiosurgery were excluded. The literature search identified 296 papers, with 35 articles meeting inclusion criteria. There were nine studies involving cervical degenerative spine disease and 26 studies on lumbar degenerative spine disease. The majority of studies for both cervical and lumbar spines utilized machine learning for the prediction of postoperative outcomes, with 5 (55.6%) and 15 (61.5%) studies, respectively. Machine learning applications focusing on degenerative lumbar spine greatly outnumber the current volume of cervical spine studies. The current research in lumbar spine also demonstrates more advanced clinical applications of radiographic, diagnostic, and predictive machine learning models.

机器学习是一个快速发展的领域，它为医生提供了一种创新而全面的机制来检查患者数据的各个方面。颈椎和腰椎退行性脊柱疾病通常是与年龄相关的疾病过程，可以利用机器学习通过仔细的患者选择和干预来改善患者的预后。本研究的目的是检查机器学习在颈椎和腰椎退行性脊柱疾病中的当前应用。使用系统评价和元分析的首选报告项目 (PRISMA) 指南进行了系统评价。在 2020 年 5 月 31 日之前对 PubMed、Embase、Medline 和 Cochrane 进行了搜索，使用以下术语：“人工智能”或“机器学习”和“神经外科”和“脊柱”。” 如果机器学习的原始研究用于退行性脊柱疾病的患者护理，包括放射学机器学习应用，则纳入研究。专注于机器人在神经外科、导航或立体定向放射外科中的应用的研究被排除在外。文献检索确定了 296 篇论文，其中 35 篇符合纳入标准。有 9 项研究涉及颈椎退行性脊柱疾病，26 项研究涉及腰椎退行性脊柱疾病。大多数颈椎和腰椎研究使用机器学习来预测术后结果，分别有 5 项（55.6%）和 15 项（61.5%）研究。专注于退行性腰椎的机器学习应用大大超过了当前颈椎研究的数量。