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Knowledge Author: facilitating user-driven domain content development to support clinical information extraction

机译:知识作者:促进用户驱动的领域内容开发以支持临床信息提取

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摘要

BackgroundClinical Natural Language Processing (NLP) systems require a semantic schema comprised of domain-specific concepts, their lexical variants, and associated modifiers to accurately extract information from clinical texts. An NLP system leverages this schema to structure concepts and extract meaning from the free texts. In the clinical domain, creating a semantic schema typically requires input from both a domain expert, such as a clinician, and an NLP expert who will represent clinical concepts created from the clinician’s domain expertise into a computable format usable by an NLP system. The goal of this work is to develop a web-based tool, Knowledge Author, that bridges the gap between the clinical domain expert and the NLP system development by facilitating the development of domain content represented in a semantic schema for extracting information from clinical free-text.
机译:背景临床自然语言处理(NLP)系统需要一个语义模式,该语义模式包括特定领域的概念,它们的词法变体以及相关的修饰符,以从临床文本中准确地提取信息。 NLP系统利用此架构来构造概念并从自由文本中提取含义。在临床领域,创建语义模式通常需要来自领域专家(例如临床医生)和NLP专家的输入,后者将代表从临床医生的领域专业知识创建的临床概念转化为NLP系统可用的可计算格式。这项工作的目标是开发一个基于网络的工具“知识作者”,它通过促进语义模式中表示的领域内容的开发来弥合临床领域专家与NL​​P系统开发之间的鸿沟,从而从临床免费软件中提取信息。文本。

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