Natural language processing in radiology: Clinical applications and future directions.

Journal: Clinical imaging
Published Date:

Abstract

Natural language processing (NLP) is a wide range of techniques that allows computers to interact with human text. Applications of NLP in everyday life include language translation aids, chat bots, and text prediction. It has been increasingly utilized in the medical field with increased reliance on electronic health records. As findings in radiology are primarily communicated via text, the field is particularly suited to benefit from NLP based applications. Furthermore, rapidly increasing imaging volume will continue to increase burden on clinicians, emphasizing the need for improvements in workflow. In this article, we highlight the numerous non-clinical, provider focused, and patient focused applications of NLP in radiology. We also comment on challenges associated with development and incorporation of NLP based applications in radiology as well as potential future directions.

Authors

  • Pratheek S Bobba
    Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, United States.
  • Anne Sailer
    Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, United States.
  • James A Pruneski
    Department of Orthopedic Surgery, Boston Children's Hospital, Boston, MA, USA.
  • Spencer Beck
    Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, United States.
  • Ali Mozayan
    From the Department of Radiology and Biomedical Imaging, Yale School of Medicine, PO Box 208042, Tompkins East 2, New Haven, CT 06520 (A.M., M.M., I.T., S.C.); and Department of Computer Science, Yale University, New Haven, Conn (A.R.F.).
  • Sara Mozayan
    Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, United States.
  • Jennifer Arango
    Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, United States.
  • Arman Cohan
    Department of Computer Science, Yale University, New Haven, CT, United States.
  • Sophie Chheang
    From the Department of Radiology and Biomedical Imaging, Yale School of Medicine, PO Box 208042, Tompkins East 2, New Haven, CT 06520 (A.M., M.M., I.T., S.C.); and Department of Computer Science, Yale University, New Haven, Conn (A.R.F.).