DEVELOPMENT OF A SEMANTIC PARSER FOR MEDICAL TEXT

该项目旨在开发一个自然语言理解系统 专门针对从医学中提取相关临床事实， 报道 该系统主要基于语义解析技术， 强调使用以四种形式编码的医学知识。 这些形式 包括：嵌入在通用医疗数据中术语的层次结构 字典;语义网络，旨在捕获有关 不同解剖部位的相对位置;帧的集合 指定允许的术语组合。 这些框架还具有 层次结构，旨在帮助分析器找到适当的 用于识别和存储复杂医学事实的格式; 转换语法附加到框架的层次结构， 提出不同的方式一个医疗事实，如所表示的组合 术语在一个框架中，可以表达;因果网络发展 特别是允许消除许多不完全表达的歧义， 可以在医疗报告中找到的事实。 表达系统已知的不同单词的词典和 表达报告中预期的所有有意义短语的同义词词典 域也将建成。 使用该信息来解析医学文本的系统将是 构建和评估。 测试的领域将是胸部的报告 X光片、入院史和体格检查， 肺和/或心脏疾病。 评估将确定是否 报告中呈现的相关医疗事实被捕获并存储， 综合通用医学数据中的自然语言解析器 基地 这个项目的目标是进一步的技术，使 将作为自由文本捕获的医学信息编码成表格 适用于研究、质量、保证和直接临床决策 支持.

This project seeks to develop a natural language understanding system specifically aimed at extracting relevant clinical facts from medical reports. The system is based largely on a semantic parsing technique that stresses the use of medical knowledge encoded in four forms. These forms include: a hierarchy of terms embedded in a general purpose medical data dictionary; a semantic network designed to capture knowledge concerning the relative locations of different anatomic sites; a collection of frames specifying allowable combinations of terms. These frames also have a hierarchial organization designed to help the parser find an appropriate format for the recognition and storage of a complex medical fact; a transformational grammar attached to the hierarchy of frames which can propose the different ways a medical fact, as indicated by the combined terms in a frame, might be expressed; a causal network developed specifically to allow disambiguation of the many incompletely expressed facts that can be found in a medical report. Both a lexicon expressing the different words known to the system and a thesaurus expressing all meaningful phrases expected in the reporting domain will also be built. A system that uses this information to parse medical text will be constructed and evaluated. The domains tested will be the reports of chest x-rays and admitting history and physical examination for patients with pulmonary and/or cardiac diseases. The evaluation will determine whether relevant medical facts presented in the reports are captured and stored by the natural language parser in an integrated, general purpose medical data base. 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, and direct clinical decision support.