Kim Hyun Gon, Kim Su Cheol, Park Jong Hun, Kim Jae Soo, Kim Dae Yeung, Yoo Jae Chul
Department of Orthopedic Surgery, Korea University Ansan Hospital, Ansan, Republic of Korea.
Department of Orthopedic Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea.
JSES Int. 2024 Jul 20;9(3):988-993. doi: 10.1016/j.jseint.2024.07.002. eCollection 2025 May.
The application of artificial intelligence (AI) is growing rapidly in many fields, and the medical field is no exception. The amount of information we collect before, during, and after surgery is growing exponentially, making the opportunity for AI applications to be integrated into our daily practice more and more apparent.
A literature search was conducted in January 2024 using PubMed (MEDLINE), SCOPUS, and EMBASE databases. A critical analysis of the relevant literature on AI technology in shoulder arthroplasty was conducted.
In the field of shoulder arthroplasty, recent literature reports the predictive value of AI models in predicting length of hospital stay and health-care costs, predicting clinical outcomes and complications, and identifying implants. By leveraging machine learning before, during, and after surgery, surgeons can make clinical decisions, predict possible problems, estimate resources needed and clinical outcomes, and ultimately personalize care for each patient.
AI technology is becoming more and more advanced, especially in the medical field. By leveraging machine learning before, during, and after surgery, surgeons can make clinical decisions, predict possible problems, estimate resources needed and clinical outcomes, and ultimately personalize treatment for each patient. Because this technology is still in its infancy, there are several limitations to bringing it into the real-world clinical setting. However, it is advancing at a rapid pace, and therefore as a shoulder surgeon, you need to understand and be interested in AI technology.
人工智能（AI）在许多领域的应用正在迅速增长，医学领域也不例外。我们在手术前、手术中和手术后收集的信息量呈指数级增长，这使得人工智能应用融入我们日常实践的机会越来越明显。
2024年1月使用PubMed（MEDLINE）、SCOPUS和EMBASE数据库进行了文献检索。对肩关节置换术中人工智能技术的相关文献进行了批判性分析。
在肩关节置换领域，最近的文献报道了人工智能模型在预测住院时间和医疗费用、预测临床结果和并发症以及识别植入物方面的预测价值。通过在手术前、手术中和手术后利用机器学习，外科医生可以做出临床决策，预测可能出现的问题，估计所需资源和临床结果，并最终为每个患者提供个性化护理。
人工智能技术正变得越来越先进，尤其是在医学领域。通过在手术前、手术中和手术后利用机器学习，外科医生可以做出临床决策，预测可能出现的问题，估计所需资源和临床结果，并最终为每个患者提供个性化治疗。由于这项技术仍处于起步阶段，将其引入实际临床环境存在一些局限性。然而，它正在快速发展，因此作为一名肩关节外科医生，你需要了解并对人工智能技术感兴趣。
