Artificial intelligence and machine learning in spine research

被引:151
|
作者
Galbusera, Fabio [1 ]
Casaroli, Gloria [1 ]
Bassani, Tito [1 ]
机构
[1] IRCCS Ist Ortoped Galeazzi, Lab Biol Struct Mech, Via Galeazzi 4, I-20161 Milan, Italy
来源
JOR SPINE | 2019年 / 2卷 / 01期
关键词
artificial neural networks; deep learning; ethical implications; outcome prediction; segmentation; ADOLESCENT IDIOPATHIC SCOLIOSIS; LUMBAR SPINE; NEURAL-NETWORKS; MR-IMAGES; FUNCTIONAL ARCHITECTURE; COMPRESSION FRACTURES; THORACOLUMBAR SPINE; AUTOMATED DETECTION; VERTEBRA DETECTION; RECEPTIVE-FIELDS;
D O I
10.1002/jsp2.1044
中图分类号
R826.8 [整形外科学]; R782.2 [口腔颌面部整形外科学]; R726.2 [小儿整形外科学]; R62 [整形外科学(修复外科学)];
学科分类号
摘要
Artificial intelligence (AI) and machine learning (ML) techniques are revolutionizing several industrial and research fields like computer vision, autonomous driving, natural language processing, and speech recognition. These novel tools are already having a major impact in radiology, diagnostics, and many other fields in which the availability of automated solution may benefit the accuracy and repeatability of the execution of critical tasks. In this narrative review, we first present a brief description of the various techniques that are being developed nowadays, with special focus on those used in spine research. Then, we describe the applications of AI and ML to problems related to the spine which have been published so far, including the localization of vertebrae and discs in radiological images, image segmentation, computer-aided diagnosis, prediction of clinical outcomes and complications, decision support systems, content-based image retrieval, biomechanics, and motion analysis. Finally, we briefly discuss major ethical issues related to the use of AI in healthcare, namely, accountability, risk of biased decisions as well as data privacy and security, which are nowadays being debated in the scientific community and by regulatory agencies.
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页数:20
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