Natural Language Processing Technologies in Radiology Research and Clinical Applications
Natural Language Processing Technologies in Radiology Research and Clinical Applications
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DOI：
10.1148/rg.2016150080
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发表时间：
2016-01-01
期刊：
影响因子：
5.5
通讯作者：
Mitsouras, Dimitrios
中科院分区：
文献类型：
--
作者：
Cai, Tianrun;Giannopoulos, Andreas A.;Mitsouras, Dimitrios
通过利用不断更新、集成和共享的大量数据，影像报告向电子病历系统的迁移在推进放射学研究和实践方面具有巨大的潜力。然而，也存在着重大的挑战，主要是由于这些数据格式的异构性。事实上，尽管放射学有向结构化报告的趋势（即，使用标准化术语分层逐项报告），但大多数放射学报告仍然是非结构化的，使用自由形式的语言。为了有效地“挖掘”这些大型数据集进行假设检验，需要一个强大的策略来提取必要的信息。手动提取信息是一项耗时且往往难以管理的任务。“智能”搜索引擎，而不是依赖于自然语言处理（NLP），一种基于计算机的方法来分析自由格式的文本或语音，可以用来自动化这个数据挖掘任务。NLP的总体目标是将自然的人类语言翻译成一种结构化格式（即固定的元素集合），每个元素都有一组标准化的值选择，这很容易被计算机程序操纵，（除其他外）排序到子类别或查询是否有发现。作者回顾了NLP的基本原理，并描述了在放射学中构成NLP的各种技术，以及一些关键应用。(c) rsna, 2016。
The migration of imaging reports to electronic medical record systems holds great potential in terms of advancing radiology research and practice by leveraging the large volume of data continuously being updated, integrated, and shared. However, there are significant challenges as well, largely due to the heterogeneity of how these data are formatted. Indeed, although there is movement toward structured reporting in radiology (ie, hierarchically itemized reporting with use of standardized terminology), the majority of radiology reports remain unstructured and use free-form language. To effectively "mine" these large datasets for hypothesis testing, a robust strategy for extracting the necessary information is needed. Manual extraction of information is a time-consuming and often unmanageable task. "Intelligent" search engines that instead rely on natural language processing (NLP), a computer-based approach to analyzing free-form text or speech, can be used to automate this data mining task. The overall goal of NLP is to translate natural human language into a structured format (ie, a fixed collection of elements), each with a standardized set of choices for its value, that is easily manipulated by computer programs to (among other things) order into subcategories or query for the presence or absence of a finding. The authors review the fundamentals of NLP and describe various techniques that constitute NLP in radiology, along with some key applications. (C) RSNA, 2016.