Artificial Intelligence in Knee Arthroscopy

Artificial intelligence (AI) implementation has begun to revolutionize healthcare and has the potential to improve many aspects of orthopedic care. Specifically, minimally invasive knee arthroscopic procedures utilize small incisions and an arthroscope to visualize and repair internal structures of the knee joint. Although relatively streamlined and typically an outpatient procedure, obstacles through preoperative planning, intraoperative anatomic identification and limited visualization, and postoperative adverse outcomes are still apparent. AI implementation may improve treatment through efficient diagnostics, predictive accuracy, operative advantage, and optimized rehabilitation. The aim of a symbiotic relationship between AI and practitioners would allow AI to augment the capabilities of the healthcare professionals who navigate an already formidable schedule. These positives are not rendered without plausible consequence, the dispersion of information into machine learning systems increases the risk of dependency on AI, large financial expenses, and rigorous testing and time taken to verify the reliability of the technology. Artificial intelligence in knee arthroscopic surgery needs to be approached slowly and with care to ensure it is being used safely and effectively, however, if used properly, it has the potential to improve all aspects of patient care.