Role of Artificial Intelligence for Endoscopic Ultrasound

Abstract

Endoscopic ultrasound (EUS) is widely used for the diagnosis of biliopancreatic and gastrointestinal tract diseases, but it is one of the most operator-dependent endoscopic techniques, requiring a long and complex learning curve. The role of artificial intelligence (AI) in EUS is growing as AI algorithms can assist in lesion detection and characterization by analyzing EUS images. Deep learning (DL) techniques, such as convolutional neural networks, have shown great potential for tumor identification; the application of AI models can increase the EUS diagnostic accuracy, provide faster diagnoses, and provide more information that can be helpful also for a training program.

Keywords: Artificial intelligence; Cancer; Endoscopic ultrasound; Training.