Successful Development of a Natural Language Processing Algorithm for Pancreatic Neoplasms and Associated Histologic Features.

Journal: Pancreas
Published Date: Sep 14, 2023

Abstract

OBJECTIVES: Natural language processing (NLP) algorithms can interpret unstructured text for commonly used terms and phrases. Pancreatic pathologies are diverse and include benign and malignant entities with associated histologic features. Creating a pancreas NLP algorithm can aid in electronic health record coding as well as large database creation and curation.

Authors

  • Jon Michael Harrison
    From the Department of GI and General Surgery, Massachusetts General Hospital, Boston.
  • Adam Yala
    Department of Electrical Engineering and Computer Science, CSAIL, MIT, Cambridge, USA.
  • Peter Mikhael
    Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, Mass.
  • Jorge Roldan
    From the Department of GI and General Surgery, Massachusetts General Hospital, Boston.
  • Debora Ciprani
    From the Department of GI and General Surgery, Massachusetts General Hospital, Boston.
  • Theodoros Michelakos
    From the Department of GI and General Surgery, Massachusetts General Hospital, Boston.
  • Louisa Bolm
    From the Department of GI and General Surgery, Massachusetts General Hospital, Boston.
  • Motaz Qadan
    From the Department of GI and General Surgery, Massachusetts General Hospital, Boston.
  • Cristina Ferrone
    From the Department of GI and General Surgery, Massachusetts General Hospital, Boston.
  • Carlos Fernandez-Del Castillo
    From the Department of GI and General Surgery, Massachusetts General Hospital, Boston.
  • Keith Douglas Lillemoe
    From the Department of GI and General Surgery, Massachusetts General Hospital, Boston.
  • Enrico Santus
    Department of Electrical Engineering and Computer Science, CSAIL, MIT, Cambridge, Massachusetts, United States of America.
  • Kevin Hughes
    Division of Surgical Oncology, MGH, Boston, USA.

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