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本文引用的文献

1
Deep learning approach for guiding three-dimensional computed tomography reconstruction of lower limbs for robotically-assisted total knee arthroplasty.深度学习方法引导机器人辅助全膝关节置换术下肢三维 CT 重建。
Int J Med Robot. 2021 Oct;17(5):e2300. doi: 10.1002/rcs.2300. Epub 2021 Jun 14.
2
Artificial intelligence in oncology: From bench to clinic.人工智能在肿瘤学中的应用:从实验室到临床。
Semin Cancer Biol. 2022 Sep;84:113-128. doi: 10.1016/j.semcancer.2021.04.013. Epub 2021 Apr 26.
3
To Predict the Length of Hospital Stay After Total Knee Arthroplasty in an Orthopedic Center in China: The Use of Machine Learning Algorithms.预测中国某骨科中心全膝关节置换术后的住院时间:机器学习算法的应用
Front Surg. 2021 Mar 11;8:606038. doi: 10.3389/fsurg.2021.606038. eCollection 2021.
4
A Deep Learning Tool for Automated Radiographic Measurement of Acetabular Component Inclination and Version After Total Hip Arthroplasty.深度学习工具在全髋关节置换术后髋臼假体倾斜和版本的自动放射学测量中的应用。
J Arthroplasty. 2021 Jul;36(7):2510-2517.e6. doi: 10.1016/j.arth.2021.02.026. Epub 2021 Feb 16.
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Artificial Intelligence/Machine Learning in Respiratory Medicine and Potential Role in Asthma and COPD Diagnosis.人工智能/机器学习在呼吸医学中的应用及其在哮喘和 COPD 诊断中的潜在作用。
J Allergy Clin Immunol Pract. 2021 Jun;9(6):2255-2261. doi: 10.1016/j.jaip.2021.02.014. Epub 2021 Feb 19.
6
Comparison of an Artificial Intelligence-Enabled Patient Decision Aid vs Educational Material on Decision Quality, Shared Decision-Making, Patient Experience, and Functional Outcomes in Adults With Knee Osteoarthritis: A Randomized Clinical Trial.人工智能辅助患者决策辅助工具与教育材料对膝骨关节炎成人患者决策质量、共同决策、患者体验及功能结局影响的比较:一项随机临床试验
JAMA Netw Open. 2021 Feb 1;4(2):e2037107. doi: 10.1001/jamanetworkopen.2020.37107.
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Artificial Intelligence for the Future Radiology Diagnostic Service.面向未来放射诊断服务的人工智能
Front Mol Biosci. 2021 Jan 28;7:614258. doi: 10.3389/fmolb.2020.614258. eCollection 2020.
8
Artificial intelligence and digital pathology: Opportunities and implications for immuno-oncology.人工智能与数字病理学:免疫肿瘤学的机遇与挑战。
Biochim Biophys Acta Rev Cancer. 2021 Apr;1875(2):188520. doi: 10.1016/j.bbcan.2021.188520. Epub 2021 Feb 6.
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Approval of artificial intelligence and machine learning-based medical devices in the USA and Europe (2015-20): a comparative analysis.美国和欧洲对人工智能和基于机器学习的医疗器械的审批(2015-20):比较分析。
Lancet Digit Health. 2021 Mar;3(3):e195-e203. doi: 10.1016/S2589-7500(20)30292-2. Epub 2021 Jan 18.
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Development of a Novel, Potentially Universal Machine Learning Algorithm for Prediction of Complications After Total Hip Arthroplasty.开发一种用于预测全髋关节置换术后并发症的新型、可能通用的机器学习算法。
J Arthroplasty. 2021 May;36(5):1655-1662.e1. doi: 10.1016/j.arth.2020.12.040. Epub 2020 Dec 30.

人工关节置换术中的人工智能

Artificial intelligence in arthroplasty.

作者信息

Purnomo Glen, Yeo Seng-Jin, Liow Ming Han Lincoln

机构信息

St. Vincentius a Paulo Catholic Hospital, Surabaya, Indonesia.

Adult Reconstruction Service, Department of Orthopaedic Surgery, Singapore General Hospital, Singapore, Singapore.

出版信息

Arthroplasty. 2021 Nov 2;3(1):37. doi: 10.1186/s42836-021-00095-3.

DOI:10.1186/s42836-021-00095-3
PMID:35236494
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8796516/
Abstract

Artificial intelligence (AI) is altering the world of medicine. Given the rapid advances in technology, computers are now able to learn and improve, imitating humanoid cognitive function. AI applications currently exist in various medical specialties, some of which are already in clinical use. This review presents the potential uses and limitations of AI in arthroplasty to provide a better understanding of the existing technology and future direction of this field.Recent literature demonstrates that the utilization of AI in the field of arthroplasty has the potential to improve patient care through better diagnosis, screening, planning, monitoring, and prediction. The implementation of AI technology will enable arthroplasty surgeons to provide patient-specific management in clinical decision making, preoperative health optimization, resource allocation, decision support, and early intervention. While this technology presents a variety of exciting opportunities, it also has several limitations and challenges that need to be overcome to ensure its safety and effectiveness.

摘要

人工智能(AI)正在改变医学领域。鉴于技术的飞速发展,计算机现在能够学习和改进,模仿类人认知功能。目前人工智能应用存在于各个医学专科领域,其中一些已经在临床中使用。本综述介绍了人工智能在关节置换术中的潜在用途和局限性,以便更好地理解该领域的现有技术和未来发展方向。近期文献表明,在关节置换领域利用人工智能有潜力通过更好的诊断、筛查、规划、监测和预测来改善患者护理。人工智能技术的应用将使关节置换外科医生在临床决策、术前健康优化、资源分配、决策支持和早期干预方面能够提供针对患者的管理。虽然这项技术带来了各种令人兴奋的机会,但它也有一些局限性和挑战,需要克服这些问题以确保其安全性和有效性。