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Wicking Tests for Unidirectional Fabrics: Measurements of Capillary Parameters to Evaluate Capillary Pressure in Liquid Composite Molding Processes
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Text Processing.

Francisco M Couto1

  • 1LASIGE, Department of Informatics, Faculdade de Ciências, Universidade de Lisboa, Lisbon, Portugal.

Advances in Experimental Medicine and Biology
|June 12, 2019
PubMed
Summary
This summary is machine-generated.

This chapter details using shell scripts to extract disease information related to caffeine from biomedical text. Learn essential text processing skills for meaningful data extraction.

Keywords:
Evaluation metricsNER: Named-Entity RecognitionNLP: Natural Language ProcessingPattern matchingRegular expressionsRelation extractionString matchingText miningTokenizationWord matching

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Area of Science:

  • Biomedical Informatics
  • Computational Biology
  • Text Mining

Background:

  • Previous chapter covered automated retrieval of chemical compound data.
  • Biomedical text mining requires efficient data processing techniques.

Purpose of the Study:

  • Introduce shell scripting for biomedical text analysis.
  • Demonstrate extracting disease-related information for specific compounds like caffeine.

Main Methods:

  • Utilizing shell script commands for text processing.
  • Step-by-step guide for information extraction from unstructured text.

Main Results:

  • Successfully extracting disease associations for caffeine.
  • Developing foundational text processing skills.

Conclusions:

  • Shell scripting provides a powerful method for biomedical text analysis.
  • Readers will gain practical skills for extracting meaningful information from diverse texts.