Using machine learning to parse breast pathology reports.

Journal: Breast cancer research and treatment
Published Date: Nov 8, 2016

Abstract

PURPOSE: Extracting information from electronic medical record is a time-consuming and expensive process when done manually. Rule-based and machine learning techniques are two approaches to solving this problem. In this study, we trained a machine learning model on pathology reports to extract pertinent tumor characteristics, which enabled us to create a large database of attribute searchable pathology reports. This database can be used to identify cohorts of patients with characteristics of interest.

Authors

  • Adam Yala
    Department of Electrical Engineering and Computer Science, CSAIL, MIT, Cambridge, USA.
  • Regina Barzilay
    Computer Science and Artificial Intelligence Laboratory , Massachusetts Institute of Technology , 77 Massachusetts Avenue , Cambridge , MA 02139 , USA . Email: regina@csail.mit.edu.
  • Laura Salama
    Department of Radiation Oncology, MGH, Boston, USA.
  • Molly Griffin
    Division of Surgical Oncology, MGH, Boston, USA. megriff@post.harvard.edu.
  • Grace Sollender
    Geisel School of Medicine at Dartmouth, Hanover, USA.
  • Aditya Bardia
    Department of Medical Oncology, MGH, Boston, USA.
  • Constance Lehman
    Department of Radiology, MGH, Boston, USA.
  • Julliette M Buckley
    Division of Surgical Oncology, MGH, Boston, USA.
  • Suzanne B Coopey
    Division of Surgical Oncology, MGH, Boston, USA.
  • Fernanda Polubriaginof
    Department of Biomedical Informatics, Columbia University, New York, USA.
  • Judy E Garber
    Department of Medical Oncology, DFCI, Boston, USA.
  • Barbara L Smith
    Division of Surgical Oncology, MGH, Boston, USA.
  • Michele A Gadd
    Division of Surgical Oncology, MGH, Boston, USA.
  • Michelle C Specht
    Division of Surgical Oncology, MGH, Boston, USA.
  • Thomas M Gudewicz
    Department of Pathology, MGH, Boston, USA.
  • Anthony J Guidi
    Department of Pathology, NWH, Newton, USA.
  • Alphonse Taghian
    Department of Radiation Oncology, MGH, Boston, USA.
  • Kevin S Hughes
    Division of Surgical Oncology, MGH, Boston, USA.

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