SEMANTIC PARSER FOR MEDICAL FREE TEXT

医学自由文本的语义解析器

• 批准号: 2771704
• 负责人: PETER John HAUG
• 金额: $ 19.08万
• 依托单位: LDS HOSPITAL
• 依托单位国家: 美国
• 财政年份: 1997
• 资助国家: 美国
• 起止时间: 1997-09-30 至 2000-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/2771704
• 关键词: automated medical record system; behavioral /social science research tag; data management; health care facility information system; human data; indexing; radiology; semantics; syntax; vocabulary development for information system

DESCRIPTION (Taken from application abstract): Integrated clinical data bases are the cornerstones of computerized clinical information systems. As these systems evolve to support more and more of the health care delivered in this country, the completeness and accuracy of these data bases will increase in importance. So too will the need to capture the clinical data that they store in a form that computers can analyze and manipulate, a coded form. Much of the information currently captured fails this criterion; it is collected as a variety of free-text medical documents. This natural language data can be interpreted only by human readers. This proposal describes research intended to develop a natural language understanding system specifically aimed at extracting relevant clinical facts from medical free-text. It builds on previous work in two domains. In the domain of radiology an application has been developed that encodes relevant clinical data using a model of the semantics of sentences. This project seeks to extend that work by developing additional contextual models whose focus is the semantics of the entire x-ray report. In the domain of diagnostic coding, previous work has demonstrated a promising approach to encoding free-text admitting diagnoses using a semantic model derived from the work in radiology. This project seeks to extend that work by developing techniques to 1) manage the need for regular training to update knowledge structures in this system and 2) extend the semantic model to assist in recognizing misspellings and variations on accepted abbreviations. As a part of this project, two systems will be developed to explore these two complimentary parts of the natural language understanding problem. These systems will undergo a sequence of testing procedures as a part of formative evaluations. Ultimately, the goal of this project is to further techniques that allow the encoding of medical information captured as free-text into a form appropriate for research, quality assurance, the management of medical enterprises, and direct clinical decision support.

描述（摘自申请摘要）：综合临床数据 基础是计算机化临床信息系统的基石。 作为 这些系统不断发展，以支持越来越多的医疗保健服务， 在这个国家，这些数据库的完整性和准确性将 重要性增加。 因此，也需要捕捉临床数据， 它们以计算机可以分析和操作的形式存储， form. 目前收集的许多信息都不符合这一标准， 是以各种自由文本医学文档的形式收集的。 这种自然 语言数据只能由人类读者解释。 该提案描述了旨在开发自然语言的研究 理解系统，专门针对提取相关临床 来自医学自由文本的事实。 它建立在以前的工作在两个领域。 在放射学领域中，已经开发了一种应用，其编码 使用句子语义模型的相关临床数据。 这 一个项目试图通过开发额外的上下文模型来扩展这项工作 其焦点是整个X射线报告的语义。 在诊断编码领域，以前的工作已经证明了 有前途的方法来编码自由文本承认诊断使用 语义模型源自放射学工作。 本项目谋求 通过开发技术来扩展这项工作，以1）管理定期 培训，以更新该系统中的知识结构，2）扩大 语义模型，以帮助识别拼写错误和变化， 接受的缩写。 作为该项目的一部分，将开发两个系统来探索这些问题。 自然语言理解问题的两个互补部分。 这些系统将进行一系列测试程序， 形成性评价。 最终，该项目的目标是进一步 允许对捕获的医疗信息进行编码的技术， 自由文本转换成适合研究、质量保证、 医疗企业的管理和直接的临床决策支持。