为I2B2项目开发的一套自然语言处理工具。
A suite of natural language processing tools developed for the I2B2 project.
作者信息
Goryachev Sergey, Sordo Margarita, Zeng Qing T
机构信息
Decision Systems Group, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
出版信息
AMIA Annu Symp Proc. 2006;2006:931.
Textual medical records contain a wealth of information that needs to be extracted and / or indexed in order to be analyzed and interpreted by the automated tools. We have developed a collection of natural language processing (NLP) tools to extract various types of information from unstructured medical records. The generic NLP components, when assembled in pipelines and initialized with custom configuration parameters, become a powerful medical data mining instrument. We have successfully extracted such medical concepts as diagnoses, comorbidities, discharge medications, and smoking status from various types of medical records.
文本病历包含大量信息，为了能被自动化工具分析和解读，这些信息需要被提取和/或索引。我们开发了一系列自然语言处理（NLP）工具，用于从非结构化病历中提取各类信息。这些通用的NLP组件在组装成管道并使用自定义配置参数进行初始化后，就成为了强大的医学数据挖掘工具。我们已成功从各类病历中提取出诊断、合并症、出院用药和吸烟状况等医学概念。
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