人工智能在骨关节炎诊疗中的应用进展

doi:10.12114/j.issn.1007-9572.2023.0019

摘要/Abstract

摘要： 骨关节炎（OA）是临床常见的退行性疾病，晚期可导致关节功能丧失，具有致残率高的特点，目前尚无有效的根治方法。因此，早期诊断和精准治疗是改善治疗效果的关键。人工智能（AI）属于多学科交叉融合的研究热点，近年来已逐渐应用到OA诊疗过程中，能够提高OA的诊断准确性、改善临床治疗和预后效果。本文通过归纳相关文献，对AI在OA诊疗中的应用现状进行系统阐述，发现其在辅助OA影像诊断、手术治疗、疾病进展预测和术后康复等方面具有潜在的应用价值，但也存在数据采集不规范、算法系统不稳定等局限，今后应建立标准化的临床样本数据库，持续优化算法模型，使AI技术更好地参与OA诊疗。

关键词: 人工智能, 骨关节炎, 机器学习, 深度学习, 手术机器人, 智能康复, 综述

Abstract:

Osteoarthritis (OA) is a degenerative disease frequently encountered clinically, which can lead to loss of joint function in the late stage and is associated with a high disability rate. There is still no available cure for OA. Therefore, early diagnosis and precise treatment are the key to improving the therapeutic effect. Being an interdisciplinary research focus, artificial intelligence (AI) has been increasingly used in the diagnosis and treatment of OA recently, as it improves the diagnostic accuracy as well as clinical treatment and prognosis of OA. We summarized and systematically reviewed the literature on the application of AI in the diagnosis and treatment of OA, in which the application potential in assisting imaging diagnosis, surgical treatment, progression prediction and postoperative rehabilitation of OA was indicated, yet some limitations including non-standardized data collection and unstable algorithmic system were also identified. In the future, it is expected to establish a standardized clinical sample database and continuously optimize the algorithmic model, so as to better incorporate AI technologies in the diagnosis and treatment process of OA.

Key words: Artificial intelligence, Osteoarthritis, Machine learning, Deep learning, Surgical robot, Intelligent rehabilitation, Review

郭天赐,陈继鑫,余伟杰,等. 人工智能在骨关节炎诊疗中的应用进展[J]. 中国全科医学, 2023, 26(19): 2428-2433. DOI: 10.12114/j.issn.1007-9572.2023.0019.
GUO Tianci,CHEN Jixin,YU Weijie, et al. Recent Developments in the Application of Artificial Intelligence in the Diagnosis and Treatment of Osteoarthritis[J]. Chinese General Practice, 2023, 26(19): 2428-2433. DOI: 10.12114/j.issn.1007-9572.2023.0019.

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