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

Ming-Wun WongBenjamin D RogersMin-Xiang LiuWei-Yi LeiTso-Tsai LiuChih-Hsun YiJui-Sheng HungShu-Wei LiangChiu-Wang TsengJen-Hung WangPing-An WuChien-Lin Chen
Published in: Diagnostics (Basel, Switzerland) (2023)
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.
Keyphrases
  • artificial intelligence
  • machine learning
  • big data
  • deep learning
  • gastroesophageal reflux disease
  • dual energy
  • systematic review