Clinical Text Analysis Using Interactive Natural Language Processing

Gaurav Trivedi
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引用次数: 2

Abstract

Natural Language Processing (NLP) systems are typically developed by informaticists skilled in machine learning techniques that are unfamiliar to end-users. Although NLP has been widely used in extracting information from clinical text, current systems generally do not provide any provisions for incorporating feedback and revising models based on input from domain experts. The goal of this research is to close this gap by building highly-usable tools suitable for the analysis of free text reports.
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使用交互式自然语言处理的临床文本分析
自然语言处理(NLP)系统通常由精通最终用户不熟悉的机器学习技术的信息学家开发。虽然NLP已广泛用于从临床文本中提取信息,但目前的系统通常没有提供任何规定,以结合反馈和修改基于领域专家输入的模型。本研究的目标是通过构建适合于分析自由文本报告的高可用性工具来缩小这一差距。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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