Advancements in biliopancreatic endoscopy: a comprehensive review of artificial intelligence in EUS and ERCP.
Belén Agudo CastilloMiguel Mascarenhas SaraivaMiguel MartinsFrancisco MendesDaniel Iglesia-GarcíaAntonio Miguel Martins Pinto da CostaCarlos Esteban Fernández-ZarzaMariano González-Haba RuizPublished in: Revista espanola de enfermedades digestivas (2024)
The development and implementation of artificial intelligence (AI), particularly deep learning (DL) models, has generated significant interest across various fields of gastroenterology. While research in luminal endoscopy has seen rapid translation to clinical practice with approved AI devices, its potential extends far beyond, offering promising benefits for biliopancreatic endoscopy like optical characterization of strictures during cholangioscopy or detection and classification of pancreatic lesions during diagnostic endoscopic ultrasound (EUS). This narrative review provides an up-to-date of the latest literature and available studies in this field. Serving as a comprehensive guide to the current landscape of AI in biliopancreatic endoscopy, emphasizing technological advancements, main applications, ethical considerations, and future directions for research and clinical implementation.
Keyphrases
- artificial intelligence
- deep learning
- machine learning
- small bowel
- big data
- roux en y gastric bypass
- gastric bypass
- convolutional neural network
- clinical practice
- primary care
- healthcare
- ultrasound guided
- loop mediated isothermal amplification
- fine needle aspiration
- systematic review
- magnetic resonance imaging
- quality improvement
- high speed
- current status
- drug administration
- sensitive detection