Use of natural language processing to improve predictive models for imaging utilization in children presenting to the emergency department.

Journal: BMC medical informatics and decision making
Published Date: Dec 30, 2019

Abstract

OBJECTIVE: To examine the association between the medical imaging utilization and information related to patients' socioeconomic, demographic and clinical factors during the patients' ED visits; and to develop predictive models using these associated factors including natural language elements to predict the medical imaging utilization at pediatric ED.

Authors

  • Xingyu Zhang
    Department of Communication Science and Disorders, School of Health and Rehabilitation Sciences, University of Pittsburgh, Pittsburgh, PA, USA.
  • M Fernanda Bellolio
    Department of Emergency Medicine, Mayo Clinic, Rochester, USA.
  • Pau Medrano-Gracia
    Department of Anatomy and Medical Imaging, University of Auckland, Auckland, New Zealand.
  • Konrad Werys
    Oxford Centre for Clinical Magnetic Resonance Research, University of Oxford, Oxford, UK.
  • Sheng Yang
    Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences, Beijing, China.
  • Prashant Mahajan
    Department of Emergency Medicine, University of Michigan School of Medicine, Ann Arbor, USA.

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