Accurate Identification of Fatty Liver Disease in Data Warehouse Utilizing Natural Language Processing.

Journal: Digestive diseases and sciences
PMID:

Abstract

INTRODUCTION: Natural language processing is a powerful technique of machine learning capable of maximizing data extraction from complex electronic medical records.

Authors

  • Joseph S Redman
    Baylor College of Medicine, Houston, TX, USA.
  • Yamini Natarajan
    Baylor College of Medicine, Houston, TX, USA. ynataraj@bcm.edu.
  • Jason K Hou
    Baylor College of Medicine, Houston, TX, USA.
  • Jingqi Wang
    School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX, USA.
  • Muzammil Hanif
    Clinical Epidemiology and Comparative Effectiveness Program, Center for Innovations in Quality, Effectiveness and Safety, Michael E. Debakey VA Medical Center, John P. McGovern Campus, 2450 Holcombe Blvd., Suite 01Y, Houston, TX, 77021, USA.
  • Hua Feng
    Clinical Epidemiology and Comparative Effectiveness Program, Center for Innovations in Quality, Effectiveness and Safety, Michael E. Debakey VA Medical Center, John P. McGovern Campus, 2450 Holcombe Blvd., Suite 01Y, Houston, TX, 77021, USA.
  • Jennifer R Kramer
    Clinical Epidemiology and Comparative Effectiveness Program, Center for Innovations in Quality, Effectiveness and Safety, Michael E. Debakey VA Medical Center, John P. McGovern Campus, 2450 Holcombe Blvd., Suite 01Y, Houston, TX, 77021, USA.
  • Roxanne Desiderio
    Clinical Epidemiology and Comparative Effectiveness Program, Center for Innovations in Quality, Effectiveness and Safety, Michael E. Debakey VA Medical Center, John P. McGovern Campus, 2450 Holcombe Blvd., Suite 01Y, Houston, TX, 77021, USA.
  • Hua Xu
    Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
  • Hashem B El-Serag
    Baylor College of Medicine, Houston, TX, USA.
  • Fasiha Kanwal
    Baylor College of Medicine, Houston, TX, USA.