Machine Learning Approaches to the Prediction of Osteoarthritis Phenotypes and Outcomes.

IF 5.7 2区 医学 Q1 RHEUMATOLOGY
Current Rheumatology Reports Pub Date : 2023-11-01 Epub Date: 2023-08-10 DOI:10.1007/s11926-023-01114-9
Liubov Arbeeva, Mary C Minnig, Katherine A Yates, Amanda E Nelson
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引用次数: 0

Abstract

Purpose of review: Osteoarthritis (OA) is a complex heterogeneous disease with no effective treatments. Artificial intelligence (AI) and its subfield machine learning (ML) can be applied to data from different sources to (1) assist clinicians and patients in decision making, based on machine-learned evidence, and (2) improve our understanding of pathophysiology and mechanisms underlying OA, providing new insights into disease management and prevention. The purpose of this review is to improve the ability of clinicians and OA researchers to understand the strengths and limitations of AI/ML methods in applications to OA research.

Recent findings: AI/ML can assist clinicians by prediction of OA incidence and progression and by providing tailored personalized treatment. These methods allow using multidimensional multi-source data to understand the nature of OA, to identify different OA phenotypes, and for biomarker discovery. We described the recent implementations of AI/ML in OA research and highlighted potential future directions and associated challenges.

预测骨关节炎表型和结果的机器学习方法。
综述目的:骨关节炎(OA)是一种复杂的异质性疾病,尚无有效的治疗方法。人工智能(AI)及其子领域机器学习(ML)可以应用于来自不同来源的数据,以(1)基于机器学习证据帮助临床医生和患者做出决策,以及(2)提高我们对OA的病理生理学和机制的理解,为疾病管理和预防提供新的见解。这篇综述的目的是提高临床医生和OA研究人员了解AI/ML方法在OA研究中应用的优势和局限性的能力。最近的发现:AI/ML可以通过预测OA的发病率和进展以及提供量身定制的个性化治疗来帮助临床医生。这些方法允许使用多维多源数据来了解OA的性质,识别不同的OA表型,并用于生物标志物的发现。我们描述了AI/ML在OA研究中的最新实现,并强调了潜在的未来方向和相关挑战。
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来源期刊
CiteScore
11.20
自引率
0.00%
发文量
41
期刊介绍: This journal aims to review the most important, recently published research in the field of rheumatology. By providing clear, insightful, balanced contributions by international experts, the journal intends to serve all those involved in the care and prevention of rheumatologic conditions. We accomplish this aim by appointing international authorities to serve as Section Editors in key subject areas such as the many forms of arthritis, osteoporosis and metabolic bone disease, and systemic lupus erythematosus. Section Editors, in turn, select topics for which leading experts contribute comprehensive review articles that emphasize new developments and recently published papers of major importance, highlighted by annotated reference lists. An international Editorial Board reviews the annual table of contents, suggests articles of special interest to their country/region, and ensures that topics are current and include emerging research. Commentaries from well-known figures in the field are also occasionally provided.
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