Using a Natural Language Processing and Machine Learning Algorithm Program to Analyze Inter-Radiologist Report Style Variation and Compare Variation Between Radiologists When Using Highly Structured Versus More Free Text Reporting.

Journal: Current problems in diagnostic radiology
Published Date: Oct 9, 2018

Abstract

PURPOSE: To use a natural language processing and machine learning algorithm to evaluate inter-radiologist report variation and compare variation between radiologists using highly structured versus more free text reporting.

Authors

  • Lane F Donnelly
    Department of Radiology, Texas Children's Hospital, Houston, Texas; Department of Radiology, Stanford University, Stanford, California. Electronic address: lane.donnelly@stanford.edu.
  • Robert Grzeszczuk
    InContext, Houston, Texas.
  • Carolina V Guimaraes
    Department of Radiology, Texas Children's Hospital, Houston, Texas; Department of Radiology, Stanford University, Stanford, California.
  • Wei Zhang
    The First Affiliated Hospital of Nanchang University, Nanchang, China.
  • George S Bisset Iii
    Department of Radiology, Texas Children's Hospital, Houston, TX.

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