Development and Validation of a Machine Learning System to Identify Reflux Events in Esophageal 24-hour pH/Impedance Studies.
Margaret J ZhouThomas ZikosKaran GoelKabir GoelAlbert GuChristopher ReDavid RodriguezJohn O ClarkePatricia GarciaNielsen Fernandez-BeckerIrene SonuAfrin KamalSidhartha R SinhaPublished in: Clinical and translational gastroenterology (2023)
We trained and validated a novel machine learning system to successfully identify reflux events in 24-hour pH/impedance studies. Our model performance was superior to that of existing software and comparable to that of a human reader. Machine learning tools could significantly improve automated interpretation of pH/impedance studies.