Artificial intelligence in orthopaedic surgery

康复 医疗保健 医学 人工智能 叙述性评论 骨科手术 医学物理学 重症监护医学 计算机科学 外科 物理疗法 经济 经济增长
作者
Anthony Lisacek-Kiosoglous,Amber S. Powling,Andreas Fontalis,Ayman Gabr,Evangelos B. Mazomenos,Fares S. Haddad
出处
期刊:Bone and Joint Research [Journal of Bone and Joint Surgery]
卷期号:12 (7): 447-454 被引量:129
标识
DOI:10.1302/2046-3758.127.bjr-2023-0111.r1
摘要

The use of artificial intelligence (AI) is rapidly growing across many domains, of which the medical field is no exception. AI is an umbrella term defining the practical application of algorithms to generate useful output, without the need of human cognition. Owing to the expanding volume of patient information collected, known as ‘big data’, AI is showing promise as a useful tool in healthcare research and across all aspects of patient care pathways. Practical applications in orthopaedic surgery include: diagnostics, such as fracture recognition and tumour detection; predictive models of clinical and patient-reported outcome measures, such as calculating mortality rates and length of hospital stay; and real-time rehabilitation monitoring and surgical training. However, clinicians should remain cognizant of AI’s limitations, as the development of robust reporting and validation frameworks is of paramount importance to prevent avoidable errors and biases. The aim of this review article is to provide a comprehensive understanding of AI and its subfields, as well as to delineate its existing clinical applications in trauma and orthopaedic surgery. Furthermore, this narrative review expands upon the limitations of AI and future direction. Cite this article: Bone Joint Res 2023;12(7):447–454.
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