基于自然语言的医疗保健领域知识提取

Edgars Rencis
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引用次数: 5

摘要

医院数据库中的数据量越来越大。这些数据可以用来减轻医院管理者、医生和研究人员的决策过程。然而,这些类型的最终用户通常缺乏从数据库中提取这些数据所需的专业知识。在如何允许非程序员以方便的方式编写查询的领域中存在几种方法,但是没有一种方法达到完全令人满意的结果。本文通过引入用包含关键字的自然语言编写查询的方法,从而简化了最终用户的查询编写过程,从而初步解决了这一问题。在组织的知识管理系统中引入这种方法将极大地有利于领域专家,使他们能够以更快速和更少错误的方式执行决策过程。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Natural Language-Based Knowledge Extraction in Healthcare Domain
There is a growing amount of data in the databases of hospitals. These data could be exploited to alleviate the decision-making process of hospital managers, physicians and researchers. However, these types of end-users often lack the expertise necessary for extracting those data from the database. Several approaches exist in the field of how to allow non-programmers writing queries in a convenient manner, but none of them has yet reached fully satisfactory results. This paper sketches a solution to this problem by introducing means for writing queries in a keywords-containing natural language thus alleviating the query writing process for the end-user. Introducing this approach in the knowledge management system of the organization would greatly benefit the domain experts by allowing them to carry out the decision-making process in a more rapid and less erroneous manner.
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