Abstract：
Artificial Intelligence (AI)/Machine Learning (ML) applications have been proven efficient to improve diagnosis, to stratify risk, and to predict outcomes in many respective medical specialties, including in orthopaedics.
Regarding hip and knee reconstruction surgery, AI/ML have not made it yet to clinical practice. In this review, we present sound AI/ML applications in the field of hip and knee degenerative disease and reconstruction. From osteoarthritis (OA) diagnosis and prediction of its advancement, clinical decision-making, identification of hip and knee implants to prediction of clinical outcome and complications following a reconstruction procedure of these joints, we report how AI/ML systems could facilitate data-driven personalized care for our patients.
Regarding hip and knee reconstruction surgery, AI/ML have not made it yet to clinical practice. In this review, we present sound AI/ML applications in the field of hip and knee degenerative disease and reconstruction. From osteoarthritis (OA) diagnosis and prediction of its advancement, clinical decision-making, identification of hip and knee implants to prediction of clinical outcome and complications following a reconstruction procedure of these joints, we report how AI/ML systems could facilitate data-driven personalized care for our patients.
摘要：
人工智能（AI）/机器学习（ML）应用程序已被证明可以有效地改善诊断，为了分层风险，并预测许多医学专业的结果，包括骨科。
关于髋关节和膝关节重建手术，AI/ML尚未进入临床实践。在这次审查中,我们介绍了AI/ML在髋关节和膝关节退行性疾病和重建领域的应用。从骨关节炎（OA）的诊断和预测其进展，临床决策,髋关节和膝关节植入物的识别，以预测这些关节的重建程序后的临床结果和并发症，我们报告了AI/ML系统如何为患者提供数据驱动的个性化护理。
关于髋关节和膝关节重建手术，AI/ML尚未进入临床实践。在这次审查中,我们介绍了AI/ML在髋关节和膝关节退行性疾病和重建领域的应用。从骨关节炎（OA）的诊断和预测其进展，临床决策,髋关节和膝关节植入物的识别，以预测这些关节的重建程序后的临床结果和并发症，我们报告了AI/ML系统如何为患者提供数据驱动的个性化护理。
