Sports Medicine Institute, Hospital for Special Surgery.
Arthroscopy. 2023 Mar;39(3):787-789. doi: 10.1016/j.arthro.2022.07.012.
Orthopaedic and sports medicine research surrounding artificial intelligence (AI) has dramatically risen over the last 4 years. Meaningful application and methodologic rigor in the scientific literature are critical to ensure appropriate use of AI. Common but critical errors for those engaging in AI-related research include failure to 1) ensure the question is important and previously unknown or unanswered; 2) establish that AI is necessary to answer the question; and 3) recognize model performance is more commonly a reflection of the data than the AI itself. We must take care to ensure we are not repackaging and internally validating registry data. Instead, we should be critically appraising our data-not the AI-based statistical technique. Without appropriate guardrails surrounding the use of artificial intelligence in Orthopaedic research, there is a risk of repackaging registry data and low-quality research in a recursive peer-reviewed loop.
在过去的 4 年中，围绕人工智能（AI）的骨科和运动医学研究急剧增加。在科学文献中实现有意义的应用和方法严谨对于确保 AI 的合理使用至关重要。从事 AI 相关研究的人常见但关键的错误包括未能：1）确保问题很重要且以前未知或未得到解答；2）确定 AI 是回答问题所必需的；3）认识到模型性能通常反映的是数据而不是 AI 本身。我们必须小心确保我们不是在重新包装和内部验证登记数据。相反，我们应该批判性地评估我们的数据，而不是基于 AI 的统计技术。如果在骨科研究中使用人工智能没有适当的防护措施，就有可能将登记数据和低质量的研究重新包装在递归同行评审循环中。
