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Updated: Apr 18, 2026
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Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications
Published on: February 23, 2019
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Application of text mining in the biomedical domain
Wilco W M Fleuren1, Wynand Alkema2
1Computational Discovery & Design Group CMBI, Radboudumc, Nijmegen, The Netherlands; Netherlands eScience Center, The Netherlands.
Methods (San Diego, Calif.)
|February 3, 2015
Summary
Automated literature mining helps researchers keep up with the rapid growth of biomedical data and publications. Text mining tools offer solutions for drug discovery and interpreting experimental results.
Area of Science:
- Biomedical Research
- Bioinformatics
- Computational Biology
Background:
- Rapid expansion of experimental data and publications in biomedical research.
- Increasing need for researchers to stay updated and interpret findings.
- Growing reliance on automated literature mining for efficient information retrieval.
Purpose of the Study:
- To introduce key text mining techniques.
- To provide an overview of current text mining tools.
- To outline typical applications of text mining in research.
Main Methods:
- Review of established text mining methodologies.
- Survey of available text mining software and platforms.
- Categorization of tools based on research problems addressed.
Main Results:
- Identification of essential text mining techniques.
- Compilation of a diverse range of text mining tools.
- Demonstration of text mining's utility in drug target discovery and biological interpretation.
Conclusions:
- Text mining is crucial for navigating the vast biomedical literature.
- A variety of tools exist to support different research needs.
- Text mining enhances the interpretation of experimental outcomes and aids discovery.
Keywords:
Automatic information extractionBiomedical researchDrug discoveryNatural language processingOntologyText miningMore Related Videos
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