Agreement between neuroimages and reports for natural language processing-based detection of silent brain infarcts and white matter disease.

Journal: BMC neurology
Published Date: May 11, 2021

Abstract

BACKGROUND: There are numerous barriers to identifying patients with silent brain infarcts (SBIs) and white matter disease (WMD) in routine clinical care. A natural language processing (NLP) algorithm may identify patients from neuroimaging reports, but it is unclear if these reports contain reliable information on these findings.

Authors

  • Lester Y Leung
    Division of Stroke and Cerebrovascular Diseases, Department of Neurology, Tufts Medical Center, Boston, USA.
  • Sunyang Fu
    Department of Artificial Intelligence and Informatics, Mayo Clinic, Rochester, USA.
  • Patrick H Luetmer
    Department of Radiology, Mayo Clinic, Rochester, MN, USA.
  • David F Kallmes
    Department of Radiology, Mayo Clinic, Rochester, MN, USA.
  • Neel Madan
    Department of Radiology, Tufts Medical Center, Boston, MA, USA.
  • Gene Weinstein
    Department of Radiology, Tufts Medical Center, Boston, MA, USA.
  • Vance T Lehman
    Department of Radiology, Mayo Clinic, Rochester, MN, USA.
  • Charlotte H Rydberg
    Department of Radiology, Mayo Clinic, Rochester, MN, USA.
  • Jason Nelson
    Institute for Clinical Research and Health Policy Studies, Tufts Medical Center, Boston, MA, USA.
  • Hongfang Liu
    Department of Artificial Intelligence & Informatics, Mayo Clinic, Rochester, MN, United States.
  • David M Kent
    Institute for Clinical Research and Health Policy Studies, Tufts Medical Center, Boston, MA, USA.

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