灵丹妙药
严厉
医学
人工智能
质量(理念)
数据科学
心理学
计算机科学
替代医学
认识论
哲学
病理
作者
Prem N. Ramkumar,Riley J. Williams
出处
期刊:Arthroscopy
[Elsevier]
日期:2023-02-03
卷期号:39 (3): 787-789
被引量:6
标识
DOI:10.1016/j.arthro.2022.07.012
摘要
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.
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