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Using automatically extracted information from mammography reports for decision-support.利用从乳腺钼靶报告中自动提取的信息进行决策支持。
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@MInter: automated text-mining of microbial interactions.@MInter：微生物相互作用的自动化文本挖掘。
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A Natural Language Processing Tool for Large-Scale Data Extraction from Echocardiography Reports.一种用于从超声心动图报告中大规模提取数据的自然语言处理工具。
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OntoGene web services for biomedical text mining.OntoGene 生物医学文本挖掘网络服务。
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A knowledge-driven approach to extract disease-related biomarkers from the literature.一种从文献中提取疾病相关生物标志物的知识驱动方法。
Biomed Res Int. 2014;2014:253128. doi: 10.1155/2014/253128. Epub 2014 Apr 16.
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Biomedical text mining and its applications in cancer research.生物医学文本挖掘及其在癌症研究中的应用。
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PESCADOR, a web-based tool to assist text-mining of biointeractions extracted from PubMed queries.PESCADOR，一个基于网络的工具，用于辅助从 PubMed 查询中提取的生物相互作用的文本挖掘。
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Discovering drug-drug interactions: a text-mining and reasoning approach based on properties of drug metabolism.发现药物-药物相互作用：一种基于药物代谢特性的文本挖掘和推理方法。
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BioLMiner System: interaction normalization task and interaction pair task in the BioCreative II.5 challenge.BioLMiner 系统：BioCreative II.5 挑战赛中的交互归一化任务和交互对任务。
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生物医学领域中的文本挖掘，重点在于文档聚类

Text Mining in Biomedical Domain with Emphasis on Document Clustering.

作者信息

Renganathan Vinaitheerthan

机构信息

Head of Institutional Research, Skyline University College, Sharjah, UAE.

出版信息

Healthc Inform Res. 2017 Jul;23(3):141-146. doi: 10.4258/hir.2017.23.3.141. Epub 2017 Jul 31.

DOI:10.4258/hir.2017.23.3.141
PMID:28875048
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5572517/
Abstract

OBJECTIVES

With the exponential increase in the number of articles published every year in the biomedical domain, there is a need to build automated systems to extract unknown information from the articles published. Text mining techniques enable the extraction of unknown knowledge from unstructured documents.

METHODS

This paper reviews text mining processes in detail and the software tools available to carry out text mining. It also reviews the roles and applications of text mining in the biomedical domain.

RESULTS

Text mining processes, such as search and retrieval of documents, pre-processing of documents, natural language processing, methods for text clustering, and methods for text classification are described in detail.

CONCLUSIONS

Text mining techniques can facilitate the mining of vast amounts of knowledge on a given topic from published biomedical research articles and draw meaningful conclusions that are not possible otherwise.

摘要

目的

随着生物医学领域每年发表的文章数量呈指数级增长，有必要构建自动化系统来从已发表的文章中提取未知信息。文本挖掘技术能够从未结构化文档中提取未知知识。

方法

本文详细回顾了文本挖掘过程以及可用于进行文本挖掘的软件工具。它还回顾了文本挖掘在生物医学领域的作用和应用。

结果

详细描述了文本挖掘过程，如文档的搜索与检索、文档预处理、自然语言处理、文本聚类方法和文本分类方法。

结论

文本挖掘技术有助于从已发表的生物医学研究文章中挖掘关于特定主题的大量知识，并得出用其他方式无法得出的有意义的结论。