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Classifying Measurements in Dictated, Free-Text Radiology Reports

  • Merlijn Sevenster
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7885)

Abstract

Radiological measurements (e.g., ‘3.2 x 1.4 cm’) are the predominant type of quantitative data in free-text radiology reports. We report on the development and evaluation of a classifier that labels measurement descriptors with the exam they refer to: current and/or prior exam. Our classifier aggregates regular expressions as binary features in a maximum entropy model. It has average F-measure 0.942 on 2,000 annotated instances; the rule-based baseline algorithm has F-measure 0.795. Potential applications and routes for future are discussed.

Keywords

Radiology report natural language processing measurements 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Merlijn Sevenster
    • 1
  1. 1.Philips Research North AmericaBriarcliff ManorUSA

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