将软件开发流程引入NLP项目，提升临床文本分析成功率
Do It Right! A Methodology for Successful NLP System Development
- 采用系统开发周期（SDLC）分阶段推进NLP项目
- 强调流程规范性对临床数据提取效果的关键作用
- 适合医疗AI团队和临床研究者参考落地
自然语言处理（NLP）常用于从电子病历中提取信息，支持临床研究与决策。尽管已有大量教材和教程介绍具体算法与应用，但仅掌握算法知识不足以确保项目成功。本文基于现有文献，提出一种分步实施的方法，将系统开发生命周期（SDLC）应用于依赖语言处理的数据提取项目，以系统化流程提升NLP项目的实施质量与可靠性。
原文摘要 · Abstract (English)
Natural language processing (NLP) is a common method for supplying data to clinical research and decision making by extracting information from electronic medical records. Numerous textbooks and tutorials describe specific algorithms and applications for text processing, yet algorithmic knowledge is only one ingredient of a successful NLP project. Drawing on the available literature, this paper presents a stepwise approach that applies the Systems Development Life Cycle (SDLC) to projects that rely on data extraction through language processing.
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