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CLAMP - a toolkit for efficiently building customized clinical natural language processing pipelines.

Ergin Soysal1, Jingqi Wang1, Min Jiang1

  • 1School of Biomedical Informatics, University of Texas Health Science Center at Houston, Houston, TX, USA.

Journal of the American Medical Informatics Association : JAMIA
|November 30, 2017
PubMed
Summary

This study introduces CLAMP, a clinical natural language processing (NLP) toolkit with a user-friendly interface for custom pipeline creation. CLAMP offers state-of-the-art NLP components and demonstrates efficient performance in clinical text analysis.

Keywords:
clinical text processingmachine learningnatural language processing

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Area of Science:

  • Clinical Natural Language Processing (NLP)
  • Biomedical Informatics

Background:

  • Existing clinical NLP systems require significant user customization and NLP expertise.
  • Information extraction from clinical text is crucial for research and healthcare.

Purpose of the Study:

  • To present CLAMP (Clinical Language Annotation, Modeling, and Processing), a novel clinical NLP toolkit.
  • To provide a user-friendly graphic interface for building customized NLP pipelines.
  • To evaluate the performance and efficiency of CLAMP.

Main Methods:

  • Developed CLAMP, a clinical NLP toolkit with state-of-the-art components.
  • Integrated a user-friendly graphic user interface (GUI) for pipeline customization.
  • Evaluated the default pipeline's performance on named entity recognition and concept encoding.
  • Demonstrated GUI efficiency using use cases for smoking status and lab test value extraction.

Main Results:

  • The CLAMP default pipeline achieved good performance in named entity recognition and concept encoding.
  • The CLAMP GUI efficiently enabled the creation of customized, high-performance NLP pipelines.
  • Successful extraction of smoking status and lab test values was demonstrated.

Conclusions:

  • CLAMP offers a valuable, user-friendly solution for clinical NLP tasks.
  • The toolkit simplifies the creation of customized NLP pipelines, enhancing accessibility for researchers.
  • CLAMP is a significant asset for the clinical NLP community and is available for research use.