Artificial intelligence in osteoarthritis research: summary of the 2025 OARSI pre-congress workshop

IF 2.8
Matthew S. Harkey , Kerry E. Costello , Bella Mehta , Chunyi Wen , Anne-Marie Malfait , Henning Madry , Brooke Patterson
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引用次数: 0

Abstract

Objective

Artificial intelligence (AI) is transforming musculoskeletal research, offering new approaches to diagnosis, prognosis, and patient management in osteoarthritis (OA). However, implementation and ethical challenges persist. This manuscript summarizes insights from the OARSI 2025 Pre-Congress Workshop on Artificial Intelligence in Osteoarthritis Research, highlighting opportunities and challenges in applying AI across biomechanics, imaging, and clinical research domains.

Design

The workshop, organized by the OARSI Early Career Investigator Committee and co-chaired by Drs. Matthew Harkey and Brooke Patterson, convened experts to discuss the use of AI in real-world biomechanics data collection, radiomics for imaging-based biomarkers, and large language models (LLMs) for clinical and research applications. Emphasis was placed on the need for interdisciplinary collaboration and ethical oversight.

Results

In biomechanics, AI-driven markerless motion capture and wearable sensors enable scalable, ecologically valid data collection, though issues such as class imbalance, data privacy, and model interpretability remain. In imaging, radiomics and deep learning models show promise for early OA detection and progression prediction but face challenges in domain adaptation and external validation. In clinical research, LLMs can streamline documentation and thematic analysis but must address concerns around bias, data security, and transparency. Across domains, transparency, reproducibility, and ethical use of AI were emphasized as critical for maintaining scientific rigor.

Conclusions

Cross-disciplinary collaboration and AI literacy are essential to responsibly advance AI integration in OA research. The workshop's collective insights call for ethical, patient-centered approaches that leverage AI's strengths while preserving research integrity and trust.
人工智能在骨关节炎研究中的应用:2025年OARSI会前研讨会综述
人工智能(AI)正在改变肌肉骨骼研究,为骨关节炎(OA)的诊断、预后和患者管理提供新的方法。然而,实施和道德方面的挑战依然存在。本文总结了OARSI 2025年骨关节炎研究中的人工智能大会前研讨会的见解,强调了在生物力学、成像和临床研究领域应用人工智能的机遇和挑战。该研讨会由OARSI早期职业研究者委员会组织,由dr。Matthew Harkey和Brooke Patterson召集专家讨论了人工智能在现实世界生物力学数据收集、基于成像的生物标志物放射组学以及临床和研究应用的大型语言模型(llm)中的应用。会议强调了跨学科合作和道德监督的必要性。在生物力学方面,人工智能驱动的无标记运动捕捉和可穿戴传感器能够实现可扩展的、生态有效的数据收集,但仍然存在诸如类别不平衡、数据隐私和模型可解释性等问题。在成像方面,放射组学和深度学习模型显示出早期OA检测和进展预测的前景,但在领域适应和外部验证方面面临挑战。在临床研究中,法学硕士可以简化文档和专题分析,但必须解决偏见、数据安全和透明度方面的问题。在各个领域,人工智能的透明度、可重复性和道德使用被强调为保持科学严谨性的关键。结论跨学科协作和人工智能素养对于负责任地推进OA研究中的人工智能集成至关重要。研讨会的集体见解要求采用道德的、以患者为中心的方法,在保持研究完整性和信任的同时利用人工智能的优势。
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来源期刊
Osteoarthritis and cartilage open
Osteoarthritis and cartilage open Orthopedics, Sports Medicine and Rehabilitation
CiteScore
3.30
自引率
0.00%
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