Medical Information Extraction Using Natural Language Interpretation

Gunjan Dhole, Nilesh J. Uke
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Abstract

NLP Based Retrieval of Medical Information is the extraction of medical data from narrative clinical documents. In this paper, we review Natural Language Processing (NLP) applications designed to extract medical problems from narrative text clinical documents. This paper also covers the methods used in this field and it also describes the architecture of the proposed system. However extraction of medical information is the difficult task due to complex symptom names and complex disease names. Proposed system is an expert system which will try to understand the input that can be the question about disease or list of symptoms and the system will try to give out the proper answer. Proposed system will consist of modules such as data processing, query processing, data extraction, answer matching, user interface etc. Lots of data are available in the medical field in free text form which is not used by normal rule based systems, so with the help of NLP we can use this free text data such as it will try to give out the answers that we search on our own.
基于自然语言解释的医学信息提取
基于自然语言处理的医学信息检索是从叙述性临床文献中提取医学数据。在本文中,我们回顾了自然语言处理(NLP)用于从叙事文本临床文件中提取医学问题的应用。本文还介绍了该领域所使用的方法,并描述了所提出的系统的体系结构。然而,由于症状名称和疾病名称复杂,医学信息的提取是一项艰巨的任务。拟议的系统是一个专家系统,它将尝试理解输入,可以是关于疾病或症状列表的问题,系统将尝试给出正确的答案。系统将由数据处理、查询处理、数据提取、答案匹配、用户界面等模块组成。在医学领域有很多自由文本形式的数据,这些数据通常是基于规则的系统所不使用的,所以在NLP的帮助下,我们可以使用这些自由文本数据,比如它会尝试给出我们自己搜索的答案。
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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