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编者按:骨科中的机器学习:踏入绝望之谷。

Editorial Commentary: Machine Learning in Orthopaedics: Venturing Into the Valley of Despair.

作者信息

Wellington Ian J, Cote Mark P

机构信息

University of Connecticut.

出版信息

Arthroscopy. 2022 Sep;38(9):2767-2768. doi: 10.1016/j.arthro.2022.05.010.

Abstract

Machine learning, a subset of artificial intelligence, has become increasingly common in the analysis of orthopaedic data. The resources needed to utilize machine-learning approaches for data analysis have become increasingly accessible to researchers, contributing to a recent influx of research using these techniques. As machine learning becomes increasingly available, misapplication owing to a lack of competence becomes more common. Sensationalized titles, misused vernacular, and a failure to fully vet machine learning-derived algorithms are just a few issues that warrant attention. As the orthopaedic community's knowledge on this topic grows, the flaws in our understanding of this field will likely become apparent, allowing for rectification and ultimately improvement of how machine learning is utilized in research.

摘要

机器学习作为人工智能的一个子集,在骨科数据分析中已变得越来越普遍。研究人员越来越容易获得利用机器学习方法进行数据分析所需的资源,这促使近期使用这些技术的研究大量涌现。随着机器学习的应用越来越广泛,由于缺乏相关能力而导致的误用也变得更加常见。耸人听闻的标题、误用的术语以及未能充分审查机器学习衍生算法等问题只是其中几个值得关注的方面。随着骨科界对这一主题的了解不断增加,我们对该领域理解中的缺陷可能会变得明显,从而得以纠正,并最终改进机器学习在研究中的应用方式。

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