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Knowledge acquisition semantic text mining and security risks in health and biomedical informatics

机译:知识获取语义文本挖掘以及健康和生物医学信息学中的安全风险

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摘要

Computational techniques have been adopted in medical and biological systems for a long time. There is no doubt that the development and application of computational methods will render great help in better understanding biomedical and biological functions. Large amounts of datasets have been produced by biomedical and biological experiments and simulations. In order for researchers to gain knowledge from original data, nontrivial transformation is necessary, which is regarded as a critical link in the chain of knowledge acquisition, sharing, and reuse. Challenges that have been encountered include: how to efficiently and effectively represent human knowledge in formal computing models, how to take advantage of semantic text mining techniques rather than traditional syntactic text mining, and how to handle security issues during the knowledge sharing and reuse. This paper summarizes the state-of-the-art in these research directions. We aim to provide readers with an introduction of major computing themes to be applied to the medical and biological research.
机译:计算技术已在医学和生物系统中长期采用。毫无疑问,计算方法的开发和应用将为更好地理解生物医学和生物学功能提供巨大帮助。通过生物医学和生物学实验以及模拟已经产生了大量的数据集。为了使研究人员从原始数据中获取知识,必须进行非平凡的转换,这被视为知识获取,共享和重用链中的关键环节。面临的挑战包括:如何在形式化的计算模型中有效地表示人类知识,如何利用语义文本挖掘技术而不是传统的句法文本挖掘,以及如何在知识共享和重用期间处理安全问题。本文总结了这些研究方向上的最新技术。我们旨在为读者介绍将应用于医学和生物学研究的主要计算主题。

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