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Deep Learning in Biomedical Text Mining: Contributions and Challenges
Multiple Perspectives on Artificial Intelligence in Healthcare, 2021T. Alam, S. Schmeier
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Introduction to Biomedical Literature Text Mining: Context and Objectives
2014If you are reading this, you know how important it is and almost certainly look to the biomedical literature for a large part of the information you need. We work hard to find more and more biomedical literature, seeking new content from multiple sources. But, can there be too much of a good thing? Most science is reductionist by nature.
Jeffrey D, Saffer, Vicki L, Burnett
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Text Mining for Automatic Lexical Analysis of Layman Text of Biomedical Argument
2009Despite various efforts to improve reliability of health care material on the world wide web in recent years, progress on this issue has been limited. Thus far, a variety of terms intended to describe this issue, including quality, trustworthiness, and credibility have been used.
D. Defilippi +2 more
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Frequent item-set mining and clustering based ranked biomedical text summarization
Journal of Supercomputing, 2022Supriya Gupta +2 more
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Mining molecular binding terminology from biomedical text.
Proceedings. AMIA Symposium, 2000Automatic access to information regarding macromolecular binding relationships would provide a valuable resource to the biomedical community. We report on a pilot project to mine such information from the molecular biology literature. The program being developed takes advantage of natural language processing techniques and is supported by two ...
T C, Rindflesch, L, Hunter, A R, Aronson
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2018
Most word embedding methods are proposed with general purpose which take a word as a basic unit and learn embeddings by words’ external contexts. However, in the field of biomedical text mining, there are many biomedical entities and syntactic chunks which can enrich the semantic meaning of word embeddings. Furthermore, large scale background texts for
Lishuang Li, Jia Wan, Degen Huang
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Most word embedding methods are proposed with general purpose which take a word as a basic unit and learn embeddings by words’ external contexts. However, in the field of biomedical text mining, there are many biomedical entities and syntactic chunks which can enrich the semantic meaning of word embeddings. Furthermore, large scale background texts for
Lishuang Li, Jia Wan, Degen Huang
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Utilizing BERT for biomedical and clinical text mining
, 2021Runjie Zhu, Xinhui Tu, J. Huang
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