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

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.

Role of Artificial Intelligence in the Diagnosis of Gastroesophageal Reflux Disease

“…The other metrics that should be evaluated in such cases include several reflux episodes, mean nocturnal baseline impedance (MNBI), and reflux-induced peristaltic wave (PSPW). AI advances have been made to study the number of reflux episodes, MNBI, and PSPW index, but no significant AI application was developed to measure the AET [40]. This might be one of the most important missing links in diagnosing GERD and a potential future research advancement.…”