Artificial intelligence automates and augments baseline impedance measurements from pH-impedance studies in gastroesophageal reflux disease.

Journal: Journal of gastroenterology
Published Date: Jan 1, 2021

Abstract

BACKGROUND: Artificial intelligence (AI) has potential to streamline interpretation of pH-impedance studies. In this exploratory observational cohort study, we determined feasibility of automated AI extraction of baseline impedance (AIBI) and evaluated clinical value of novel AI metrics.

Authors

  • Benjamin Rogers
    Division of Gastroenterology, Washington University School of Medicine, 660 South Euclid Ave., Campus Box 8124, Saint Louis, MO, 63110, USA.
  • Sabyasachi Samanta
    Crosswave Solutions, LLC., Lexington, KY, USA.
  • Kevan Ghobadi
    Crosswave Solutions, LLC., Lexington, KY, USA.
  • Amit Patel
    Division of Gastroenterology, Duke University School of Medicine, The Durham Veterans Affairs Medical Center, Durham, NC, USA.
  • Edoardo Savarino
    Gastroenterolgy Unit, Department of Surgery, Oncology and Gastroenterology, University of Padua, Padua, Italy.
  • Sabine Roman
    Digestive Physiology, Hospices Civils de Lyon, Hopital E Herriot, Université de Lyon, 69437, Lyon, France.
  • Daniel Sifrim
    Barts and The London School of Medicine and Dentistry Queen Mary, University of London, London, UK.
  • C Prakash Gyawali
    Division of Gastroenterology, Washington University School of Medicine, 660 South Euclid Ave., Campus Box 8124, Saint Louis, MO, 63110, USA. cprakash@wustl.edu.

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