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Knowledge Author: facilitating user-driven, domain content development to support clinical information extraction.

William Scuba1, Melissa Tharp1, Danielle Mowery1

  • 1Department of Biomedical Informatics, University of Utah, Salt Lake City, UT, 84108, USA.

Journal of Biomedical Semantics
|June 25, 2016
PubMed
Summary
This summary is machine-generated.

Knowledge Author is a web-based tool that helps clinical experts create semantic schemas for Natural Language Processing (NLP) systems. This tool facilitates information extraction from clinical texts, improving NLP accuracy.

Keywords:
Information extractionKnowledge representationNatural Language ProcessingSemanticsUnified Medical Language System

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Area of Science:

  • Natural Language Processing (NLP)
  • Clinical Informatics
  • Knowledge Representation

Background:

  • Clinical NLP systems require semantic schemas for accurate information extraction from clinical texts.
  • Developing these schemas typically involves collaboration between clinical and NLP experts.
  • Bridging this gap is crucial for effective clinical text analysis.

Purpose of the Study:

  • To develop a web-based tool, Knowledge Author, to facilitate semantic schema creation for clinical NLP.
  • To enable clinical domain experts to develop computable representations of clinical concepts.
  • To bridge the gap between clinical expertise and NLP system development.

Main Methods:

  • Knowledge Author is a web-based recommendation system for developing domain content for clinical NLP.
  • It utilizes semantic types from established models and suggests concepts via the Unified Medical Language System Metathesaurus.
  • Collaborative development features are integrated.

Main Results:

  • Proof of concept studies demonstrated Knowledge Author's flexibility in creating a broad range of concepts (76% success rate).
  • Evaluation in an NLP system (pyConText) for carotid stenosis extraction showed high recall for concepts (86%) and varied recall for modifiers (e.g., certainty 91%, sidedness 80%).

Conclusions:

  • Knowledge Author effectively supports clinical domain content development for information extraction.
  • It empowers domain experts in creating semantic schemas essential for clinical NLP applications.