Application of Artificial Intelligence in Measuring Novel pH-Impedance Metrics for Optimal Diagnosis of GERD.

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Abstract

Novel metrics extracted from pH-impedance monitoring can augment the diagnosis of gastroesophageal reflux disease (GERD). Artificial intelligence (AI) is being widely used to improve the diagnostic capabilities of various diseases. In this review, we update the current literature regarding applications of artificial intelligence in measuring novel pH-impedance metrics. AI demonstrates high performance in the measurement of impedance metrics, including numbers of reflux episodes and post-reflux swallow-induced peristaltic wave index and, furthermore, extracts baseline impedance from the entire pH-impedance study. AI is expected to play a reliable role in facilitating measuring novel impedance metrics in patients with GERD in the near future.

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Author and article information

Journal

Journal ID (iso-abbrev): Diagnostics (Basel)

Title: Diagnostics (Basel, Switzerland)

Publisher: MDPI AG

ISSN: 2075-4418

ISSN (Print): 2075-4418

Publication date (Electronic): Mar 03 2023

Volume: 13

Issue: 5

Affiliations

[1 ] Department of Medicine, Hualien Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation, Tzu Chi University, 707, Section 3, Chung-Yang Road, Hualien 97004, Taiwan.

[2 ] School of Post-Baccalaureate Chinese Medicine, Tzu Chi University, Hualien 97004, Taiwan.

[3 ] Division of Gastroenterology, Hepatology and Nutrition, University of Louisville, Louisville, KY 40292, USA.

[4 ] Division of Gastroenterology, Washington University School of Medicine, St. Louis, MO 63110, USA.

[5 ] AI Innovation Research Center, Hualien Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation, Hualien 97004, Taiwan.

[6 ] NVIDIA AI Technology Center, NVIDIA Corporation, Taipei 11492, Taiwan.

[7 ] Department of Medical Research, Hualien Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation, Hualien 97004, Taiwan.

[8 ] Institute of Medical Sciences, Tzu Chi University, Hualien 97004, Taiwan.

Article

Publisher Item ID: diagnostics13050960

DOI: 10.3390/diagnostics13050960

PMC ID: 10000892

PubMed ID: 36900104

SO-VID: 5139cf6f-37f9-44a8-9c78-7591cc3bdc16

History

Keywords: post-reflux swallow-induced peristaltic wave index,reflux episodes,impedance-pH monitoring,gastroesophageal reflux disease,artificial intelligence

Data availability:

Keywords: post-reflux swallow-induced peristaltic wave index, reflux episodes, impedance-pH monitoring, gastroesophageal reflux disease, artificial intelligence

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