Artificial intelligence in shoulder arthroplasty: how smart is it?
  • Kim, Hyun Gon
  • Kim, Su Cheol
  • Park, Jong Hun
  • Kim, Jae Soo
  • Kim, Dae Yeung
  • 외 1명
Citations

WEB OF SCIENCE

0
Citations

SCOPUS

0

초록

Background: 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. Methods: 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. Results: 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. Conclusion: 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.

키워드

Shoulder arthroplastyArtificial intelligenceMachine learningDeep learningPredictionClinical decision
제목
Artificial intelligence in shoulder arthroplasty: how smart is it?
저자
Kim, Hyun GonKim, Su CheolPark, Jong HunKim, Jae SooKim, Dae YeungYoo, Jae Chul
DOI
10.1016/j.jseint.2024.07.002
발행일
2025-05
유형
Article in press
저널명
JSES International
9
3
페이지
988 ~ 993

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