Yale University School of Medicine, New Haven, Connecticut, USA.
J Am Med Inform Assoc. 2011 Sep-Oct;18(5):544-51. doi: 10.1136/amiajnl-2011-000464.
To provide an overview and tutorial of natural language processing (NLP) and modern NLP-system design.
This tutorial targets the medical informatics generalist who has limited acquaintance with the principles behind NLP and/or limited knowledge of the current state of the art.
We describe the historical evolution of NLP, and summarize common NLP sub-problems in this extensive field. We then provide a synopsis of selected highlights of medical NLP efforts. After providing a brief description of common machine-learning approaches that are being used for diverse NLP sub-problems, we discuss how modern NLP architectures are designed, with a summary of the Apache Foundation's Unstructured Information Management Architecture. We finally consider possible future directions for NLP, and reflect on the possible impact of IBM Watson on the medical field.
提供自然语言处理(NLP)和现代 NLP 系统设计概述和教程。
本教程面向对 NLP 原理知之甚少或对当前技术水平了解有限的医学信息学通才。
我们描述了 NLP 的历史演变,并总结了这个广泛领域中的常见 NLP 子问题。然后,我们简要介绍了医学 NLP 工作的一些亮点。在简要描述正在用于各种 NLP 子问题的常见机器学习方法之后,我们讨论了如何设计现代 NLP 架构,并总结了 Apache 基金会的非结构化信息管理架构。最后,我们考虑了 NLP 的可能未来方向,并思考了 IBM Watson 对医学领域的可能影响。