New York-Presbyterian/Queens, Department of Emergency Medicine, Flushing, New York.
Boston Children's Hospital, Harvard Medical Toxicology, Boston, Massachusetts.
West J Emerg Med. 2019 Jan;20(1):78-86. doi: 10.5811/westjem.2018.11.39725. Epub 2018 Dec 12.
Natural language processing (NLP) aims to program machines to interpret human language as humans do. It could quantify aspects of medical education that were previously amenable only to qualitative methods. The application of NLP to medical education has been accelerating over the past several years. This article has three aims. First, we introduce the reader to NLP. Second, we discuss the potential of NLP to help integrate FOAM (Free Open Access Medical Education) resources with more traditional curricular elements. Finally, we present the results of a systematic review. We identified 30 articles indexed by PubMed as relating to medical education and NLP, 14 of which were of sufficient quality to include in this review. We close by discussing potential future work using NLP to advance the field of medical education in emergency medicine.
自然语言处理（NLP）旨在编程机器像人类一样解释人类语言。它可以量化以前只能通过定性方法来处理的医学教育方面的问题。过去几年，NLP 在医学教育中的应用发展迅速。本文有三个目标。首先，我们向读者介绍 NLP。其次，我们讨论 NLP 帮助将 FOAM（免费开放获取医学教育）资源与更传统的课程元素整合的潜力。最后，我们呈现了一项系统评价的结果。我们在 PubMed 中确定了 30 篇与医学教育和 NLP 相关的文章，其中 14 篇的质量足以纳入本综述。最后，我们讨论了使用 NLP 来推进急诊医学领域医学教育的潜在未来工作。
