Helm J Matthew, Swiergosz Andrew M, Haeberle Heather S, Karnuta Jaret M, Schaffer Jonathan L, Krebs Viktor E, Spitzer Andrew I, Ramkumar Prem N
Machine Learning Arthroplasty Laboratory, Cleveland Clinic, 2049 E 100th St., Cleveland, OH, 44195, USA.
Baylor College of Medicine, Department of Orthopaedic Surgery, Houston, TX, USA.
Curr Rev Musculoskelet Med. 2020 Feb;13(1):69-76. doi: 10.1007/s12178-020-09600-8.
With the unprecedented advancement of data aggregation and deep learning algorithms, artificial intelligence (AI) and machine learning (ML) are poised to transform the practice of medicine. The field of orthopedics, in particular, is uniquely suited to harness the power of big data, and in doing so provide critical insight into elevating the many facets of care provided by orthopedic surgeons. The purpose of this review is to critically evaluate the recent and novel literature regarding ML in the field of orthopedics and to address its potential impact on the future of musculoskeletal care.
Recent literature demonstrates that the incorporation of ML into orthopedics has the potential to elevate patient care through alternative patient-specific payment models, rapidly analyze imaging modalities, and remotely monitor patients. Just as the business of medicine was once considered outside the domain of the orthopedic surgeon, we report evidence that demonstrates these emerging applications of AI warrant ownership, leverage, and application by the orthopedic surgeon to better serve their patients and deliver optimal, value-based care.
随着数据聚合和深度学习算法取得前所未有的进展，人工智能（AI）和机器学习（ML）有望改变医学实践。特别是骨科领域，非常适合利用大数据的力量，从而为深入了解提升骨科医生提供的多方面护理提供关键见解。本综述的目的是批判性地评估骨科领域中有关机器学习的最新和新颖文献，并探讨其对肌肉骨骼护理未来的潜在影响。
最近的文献表明，将机器学习纳入骨科有潜力通过替代针对患者的支付模式、快速分析成像方式以及远程监测患者来提升患者护理水平。正如医学业务曾一度被认为不属于骨科医生的范畴一样，我们报告的证据表明，这些人工智能的新兴应用值得骨科医生拥有、利用和应用，以便更好地服务患者并提供最佳的、基于价值的护理。
