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将人工智能整合到骨科领域:机遇、挑战与未来方向。

Integrating artificial intelligence into orthopedics: Opportunities, challenges, and future directions.

作者信息

Vaishya Raju, Sibal Anupam, Kar Sujoy, Reddy Sangita

机构信息

Indraprastha Apollo Hospitals, New Delhi, India.

Group Medical Director, Apollo Hospitals Group, Indraprastha Apollo Hospitals, New Delhi, India.

出版信息

J Hand Microsurg. 2025 Apr 22;17(4):100257. doi: 10.1016/j.jham.2025.100257. eCollection 2025 Jul.

Abstract

PURPOSE

Artificial intelligence (AI) is transforming orthopedics by improving diagnostic accuracy, optimizing surgical planning, and personalizing treatment approaches. This review evaluates the applications of AI in orthopedics, focusing on its impact on patient care, the efficacy of AI methodologies, and challenges in integrating these technologies into clinical practice.

METHODS

A comprehensive literature search was conducted across PubMed, Scopus, and Google Scholar for articles published up to 28 February 2025. Inclusion criteria included studies addressing AI applications in orthopedics, while non-peer-reviewed and non-English publications were excluded. Data extraction focused on AI technologies, applications, outcomes, and the advantages or limitations of AI integration.

RESULTS

Findings demonstrate AI's effectiveness in areas such as fracture detection and treatment planning, mainly through machine learning and deep learning. AI has improved outcomes in joint reconstruction, spine surgery, and rehabilitation. However, challenges such as data standardization and clinical validation remain.

CONCLUSION

The review highlights AI's potential to revolutionize orthopedic practice, emphasizing the need for ongoing research to overcome barriers to adoption. Future directions should prioritize multi-center clinical trials, enhanced data protocols, and stakeholder collaboration to ensure ethical and effective AI implementation, ultimately improving patient outcomes and care delivery.

摘要

目的

人工智能(AI)正在通过提高诊断准确性、优化手术规划和个性化治疗方法来改变骨科领域。本综述评估了人工智能在骨科中的应用,重点关注其对患者护理的影响、人工智能方法的有效性以及将这些技术整合到临床实践中的挑战。

方法

在PubMed、Scopus和谷歌学术上对截至2025年2月28日发表的文章进行了全面的文献检索。纳入标准包括涉及人工智能在骨科应用的研究,同时排除未经同行评审和非英文的出版物。数据提取重点关注人工智能技术、应用、结果以及人工智能整合的优势或局限性。

结果

研究结果表明,人工智能在骨折检测和治疗规划等领域有效,主要通过机器学习和深度学习实现。人工智能在关节重建、脊柱手术和康复方面改善了治疗效果。然而,数据标准化和临床验证等挑战仍然存在。

结论

该综述强调了人工智能在彻底改变骨科实践方面的潜力,强调需要持续研究以克服应用障碍。未来的方向应优先进行多中心临床试验、加强数据协议以及利益相关者合作,以确保符合伦理且有效的人工智能实施,最终改善患者治疗效果和护理服务。

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