University of Aberdeen, Aberdeen, UK.
Aberdeen Royal Infirmary, Aberdeen, UK.
Bone Joint J. 2021 Dec;103-B(12):1754-1758. doi: 10.1302/0301-620X.103B12.BJJ-2021-0851.R1.
There is increasing popularity in the use of artificial intelligence and machine-learning techniques to provide diagnostic and prognostic models for various aspects of Trauma & Orthopaedic surgery. However, correct interpretation of these models is difficult for those without specific knowledge of computing or health data science methodology. Lack of current reporting standards leads to the potential for significant heterogeneity in the design and quality of published studies. We provide an overview of machine-learning techniques for the lay individual, including key terminology and best practice reporting guidelines. Cite this article: 2021;103-B(12):1754-1758.
人工智能和机器学习技术在创伤骨科各个方面的诊断和预后模型的应用越来越受到欢迎。然而，对于那些没有计算或健康数据科学方法特定知识的人来说，正确解释这些模型是很困难的。缺乏当前的报告标准导致已发表研究的设计和质量存在显著异质性的可能性。我们为非专业人士概述了机器学习技术，包括关键术语和最佳实践报告指南。引用本文：2021；103-B（12）：1754-1758.
