There has been rapid growth in the use of artificial intelligence analytics in medicine in recent years, including in rheumatic and musculoskeletal diseases (RMDs). Such methods represent a challenge to clinicians, patients, and researchers given the "black box" nature of most algorithms and the unfamiliarity of the terms and lack of awareness of potential issues around these analyses. Therefore, this review aims to introduce this area in a way that is relevant and meaningful to clinicians and researchers. We hope to provide some insights into relevant strengths and limitations, reporting guidelines, as well as recent examples of such analyses in key areas with a focus on lessons learned and future directions in diagnosis, phenotyping, prognosis, and precision medicine in RMDs.

中文翻译：

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面向临床医生和研究人员的风湿病和肌肉骨骼疾病机器学习的叙述性回顾：偏见、目标和未来方向。

近年来，人工智能分析在医学领域的应用迅速增长，包括风湿病和肌肉骨骼疾病 (RMD)。考虑到大多数算法的“黑匣子”性质、术语不熟悉以及对这些分析的潜在问题缺乏认识，此类方法对临床医生、患者和研究人员构成了挑战。因此，本综述旨在以对临床医生和研究人员相关且有意义的方式介绍这一领域。我们希望对相关优势和局限性、报告指南以及关键领域此类分析的最新示例提供一些见解，重点是 RMD 诊断、表型、预后和精准医学的经验教训和未来方向。