Emerging Artificial Intelligence Innovations in Rheumatoid Arthritis and Challenges to Clinical Adoption.

IF 5.7 2区 医学 Q1 RHEUMATOLOGY
Vinit J Gilvaz, Aishwarya Sudheer, Anthony M Reginato
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Abstract

Purpose of review: This review was written to inform practicing clinical rheumatologists about recent advances in artificial intelligence (AI) based research in rheumatoid arthritis (RA), using accessible and practical language. We highlight developments from 2023 to early 2025 across diagnostic imaging, treatment prediction, drug discovery, and patient-facing tools. Given the increasing clinical interest in AI and its potential to augment care delivery, this article aims to bridge the gap between technical innovation and real-world rheumatology practice.

Recent findings: Several AI models have demonstrated high accuracy in early RA detection using imaging modalities such as thermal imaging and nuclear scans. Predictive models for treatment response have leveraged routinely collected electronic health record (EHR) data, moving closer to practical application in clinical workflows. Patient-facing tools like mobile symptom checkers and large language models (LLMs) such as ChatGPT show promise in enhancing education and engagement, although accuracy and safety remain variable. AI has also shown utility in identifying novel biomarkers and accelerating drug discovery. Despite these advances, as of early 2025, no AI-based tools have received FDA approval for use in rheumatology, in contrast to other specialties. Artificial intelligence holds tremendous promise to enhance clinical care in RA-from early diagnosis to personalized therapy. However, clinical adoption remains limited due to regulatory, technical, and implementation challenges. A streamlined regulatory framework and closer collaboration between clinicians, researchers, and industry partners are urgently needed. With thoughtful integration, AI can serve as a valuable adjunct in addressing clinical complexity and workforce shortages in rheumatology.

类风湿性关节炎的新兴人工智能创新和临床应用的挑战。
综述的目的:本综述旨在使用易于理解和实用的语言,向临床风湿病医生介绍基于人工智能(AI)的类风湿性关节炎(RA)研究的最新进展。我们重点介绍了从2023年到2025年初在诊断成像、治疗预测、药物发现和面向患者的工具方面的发展。鉴于临床对人工智能的兴趣日益增加,以及人工智能在增加护理服务方面的潜力,本文旨在弥合技术创新与现实世界风湿病学实践之间的差距。最近的发现:一些人工智能模型在使用热成像和核扫描等成像方式的早期RA检测中表现出很高的准确性。治疗反应的预测模型利用了常规收集的电子健康记录(EHR)数据,更接近临床工作流程中的实际应用。面向患者的工具,如移动症状检查器和大型语言模型(llm),如ChatGPT,在加强教育和参与方面表现出了希望,尽管准确性和安全性仍然存在差异。人工智能在识别新的生物标志物和加速药物发现方面也显示出效用。尽管取得了这些进展,但截至2025年初,与其他专业相比,还没有基于人工智能的工具获得FDA批准用于风湿病。从早期诊断到个性化治疗,人工智能在增强ra的临床护理方面有着巨大的前景。然而,由于监管、技术和实施方面的挑战,临床应用仍然有限。迫切需要精简的监管框架以及临床医生、研究人员和行业合作伙伴之间更密切的合作。经过深思熟虑的整合,人工智能可以作为解决风湿病临床复杂性和劳动力短缺问题的宝贵辅助手段。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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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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