Enhancing Case Capture, Quality, and Completeness of Primary Melanoma Pathology Records via Natural Language Processing.

Journal: JCO clinical cancer informatics
Published Date:

Abstract

PURPOSE: Medical records contain a wealth of useful, informative data points valuable for clinical research. Most data points are stored in semistructured or unstructured legacy documents and require manual data abstraction into a structured format to render the information more readily accessible, searchable, and generally analysis ready. The substantial labor needed for this can be cost prohibitive, particularly when dealing with large patient cohorts.

Authors

  • Jared C Malke
    The University of Texas MD Anderson Cancer Center, Houston, TX.
  • Shida Jin
    The University of Texas MD Anderson Cancer Center, Houston, TX.
  • Samuel P Camp
    The University of Texas MD Anderson Cancer Center, Houston, TX.
  • Bryan Lari
    The University of Texas MD Anderson Cancer Center, Houston, TX.
  • Trey Kell
    The University of Texas MD Anderson Cancer Center, Houston, TX.
  • Julie M Simon
    The University of Texas MD Anderson Cancer Center, Houston, TX.
  • Victor G Prieto
    The University of Texas MD Anderson Cancer Center, Houston, TX.
  • Jeffrey E Gershenwald
    The University of Texas MD Anderson Cancer Center, Houston, TX.
  • Lauren E Haydu
    The University of Texas MD Anderson Cancer Center, Houston, TX.