Achalasia subtypes can be identified with functional luminal imaging probe (FLIP) panometry using a supervised machine learning process.
Journal:
Neurogastroenterology and motility
PMID:
32608147
Abstract
BACKGROUND: Achalasia subtypes on high-resolution manometry (HRM) prognosticate treatment response and help direct management plan. We aimed to utilize parameters of distension-induced contractility and pressurization on functional luminal imaging probe (FLIP) panometry and machine learning to predict HRM achalasia subtypes.