[Feasibility Study of the Prediction of Radiologist's Instructions with the Bi-LSTM Model Trained with Descriptions of MR Imaging Order-statement].

Journal: Nihon Hoshasen Gijutsu Gakkai zasshi
Published Date:

Abstract

PURPOSE: Magnetic resonance (MR) images provide essential diagnostic information; however, it is also a very burdensome examination for patients. At our hospital, radiologists make imaging instructions for all MR examination orders, but this is a time-consuming task. If a natural language processing model can predict the imaging instructions, it will be possible to reduce the burden on radiologists and the instruction quality can be assured. The purpose of this study was to investigate the feasibility of using natural language processing to predict MR imaging instructions with the aim of assisting radiologists.

Authors

  • Kozo Shimizu
    Central Division of Radiology, Nara Medical University Hospital.
  • Tetsuya Tachiiri
    Department of Diagnostic and Interventional Radiology, Nara Medical University.
  • Yuya Yamatani
    Central Division of Radiology, Nara Medical University Hospital.
  • Yoshimasa Mai
    Central Division of Radiology, Nara Medical University Hospital.
  • Nagaaki Marugami
    Department of Diagnostic and Interventional Radiology, Nara Medical University.