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Text mining patents for biomedical knowledge
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AI
DOI：10.1016/j.drudis.2016.05.002.png)
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摘要
En 中文
Biomedical text mining of scientific knowledge bases, such as Medline, has received much attention in recent years. Given that text mining is able to automatically extract biomedical facts that revolve around entities such as genes, proteins, and drugs, from unstructured text sources, it is seen as a major enabler to foster biomedical research and drug discovery. In contrast to the biomedical literature, research into the mining of biomedical patents has not reached the same level of maturity. Here, we review existing work and highlight the associated technical challenges that emerge from automatically extracting facts from patents. We conclude by outlining potential future directions in this domain that could help drive biomedical research and drug discovery.
Keyword:
INFORMATION
EXTRACTION
ABSTRACTS
IDENTIFICATION
DATABASES
TOOL
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
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7.5
论文数:
6.4K
被引数:
2.3W
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