Application of Biomedical Text Mining

Lejun Gong
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引用次数: 10

Abstract

With the enormous volume of biological literature, increasing growth phenomenon due to the high rate of new publications is one of the most common motivations for the biomedical text mining. Aiming at this massive literature to process, it could extract more biological information for mining biomedical knowledge. Using the information will help understand the mechanism of disease generation, promote the development of disease diagnosis technology, and promote the development of new drugs in the field of biomedical research. Based on the background, this chapter introduces the rise of biomedical text mining. Then, it describes the biomedical text-mining technology, namely natural language processing, including the several components. This chapter emphasizes the two aspects in biomedical text mining involving static biomedical information recognization and dynamic biomedical information extraction using instance analysis from our previous works. The aim is to provide a way to quickly understand biomedical text mining for some researchers.
生物医学文本挖掘的应用
随着生物文献的巨大数量,由于新出版物的高增长率而导致的增长现象是生物医学文本挖掘的最常见动机之一。针对海量的文献进行处理,可以提取更多的生物信息进行生物医学知识的挖掘。利用这些信息有助于了解疾病发生的机制,促进疾病诊断技术的发展,促进生物医学研究领域新药的开发。基于这一背景,本章介绍了生物医学文本挖掘的兴起。然后,介绍了生物医学文本挖掘技术,即自然语言处理,包括几个组成部分。本章重点介绍了生物医学文本挖掘的两个方面,即静态生物医学信息识别和动态生物医学信息提取。目的是为一些研究人员提供一种快速理解生物医学文本挖掘的方法。
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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