Natural Language Processing for Identification of Incidental Pulmonary Nodules in Radiology Reports.

Journal: Journal of the American College of Radiology : JACR
Published Date:

Abstract

PURPOSE: To develop natural language processing (NLP) to identify incidental lung nodules (ILNs) in radiology reports for assessment of management recommendations.

Authors

  • Stella K Kang
    Department of Radiology, NYU Langone Health, New York, New York; Department of Population Health, NYU Langone Health, New York, New York. Electronic address: stella.kang@nyumc.org.
  • Kira Garry
    Department of Population Health, NYU Langone Health, New York, New York.
  • Ryan Chung
    Department of Radiology, NYU Langone Health, New York, New York.
  • William H Moore
    Department of Radiology, NYU Langone Health, New York, New York.
  • Eduardo Iturrate
    New York University School of Medicine, Department of Internal Medicine, New York, NY, United States.
  • Jordan L Swartz
    Department of Emergency Medicine, NYU Langone Health, New York, New York.
  • Danny C Kim
    Department of Radiology, NYU Langone Health, New York, New York.
  • Leora I Horwitz
    Department of Radiology (M.K., W.M., K.F., J.S.B., G.M., J.P.K.), Department of Medicine, Division of Hematology and Medical Oncology, Laura and Isaac Perlmutter Cancer Center (D.K.), and Center for Healthcare Innovation and Delivery Science (L.I.H.), NYU Langone Health, 550 First Ave, New York, NY 10016; Division of Healthcare Delivery Science, Department of Population Health and Division of General Internal Medicine and Clinical Innovation, Department of Medicine, NYU Grossman School of Medicine, New York, NY (L.I.H.); and Garden State Urology, Wayne, NJ (A.K.).
  • Saul Blecker
    2 Department of Population Health, NYU Langone Medical Center, New York University , New York, New York.