NATURAL LANGUAGE PROCESSING AND CODING OF NURSES' NOTES

护士笔记的自然语言处理和编码

• 批准号: 7366538
• 负责人: ROGER GREENWOOD MARK
• 金额: $ 0.81万
• 依托单位: BETH ISRAEL DEACONESS MEDICAL CENTER
• 依托单位国家: 美国
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-03-01 至 2007-02-28
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7366538
• 关键词: NATURAL; LANGUAGE; PROCESSING; CODING; NURSES

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. Free text progress notes, written up by nurses during a patient's hospital stay, contain a wealth of useful patient information, including diagnoses, symptoms medications, and test results. However, the notes are usually hastily written, containing all sorts of abbreviations and synonyms for medical terms as well as common words. Extracting all of the useful information by hand, and representing it in a standardized form suitable for analysis, would be an extremely tedious task. This project aims to develop a method to automatically extract the relevant pieces of information from nurses' notes, and assign to each of the terms a standardized code from the National Library of Medicine's Unified Medical Language System (UMLS).

该子项目是利用NIH/NCRR资助的中心赠款提供的资源的许多研究子项目之一。子项目和研究者（PI）可能从另一个NIH来源获得主要资金，因此可以在其他CRISP条目中表示。所列机构为中心，不一定是研究者所在机构。由护士在病人住院期间撰写的自由文本病程记录包含了大量有用的病人信息，包括诊断、症状、药物治疗和检查结果。然而，这些笔记通常是匆忙写的，包含了各种医学术语的缩写和同义词以及常用词。手工提取所有有用的信息，并将其表示为适合分析的标准化形式，将是一项极其繁琐的任务。本课题的目的是开发一种方法，从护士笔记中自动提取相关信息，并从国立医学图书馆的统一医学语言系统（UMLS）中为每个术语分配一个标准化代码。