Deep Learning Methods in the Imaging of Hepatic and Pancreaticobiliary Diseases.
Publication Title
Journal of clinical gastroenterology
Document Type
Article
Publication Date
5-1-2025
Keywords
washington; swedish; swedish digestive health institute; artificial intelligence
Abstract
Reports indicate a growing role for artificial intelligence (AI) in the evaluation of pancreaticobiliary and hepatic conditions. A key focus is differentiating between benign and malignant lesions, which is crucial for treatment decisions. AI improves diagnostic accuracy through high sensitivity and specificity, while CNN algorithms enhance image analysis and reduce variability. These advancements aim to match the accuracy of pathologists in cancer detection. In addition, AI aids in identifying diagnostic markers, as early detection is essential. This article reviews the applications of machine learning and deep learning in the diagnosis of hepatic and pancreaticobiliary diseases. Although the use of AI in these specialized areas of gastroenterology is primarily confined to experimental trials, current models demonstrate significant potential for enhancing the detection, evaluation, and treatment planning of hepatic and pancreaticobiliary conditions.
Area of Special Interest
Digestive Health
Specialty/Research Institute
Gastroenterology
Specialty/Research Institute
Hepatology
Specialty/Research Institute
Swedish Digestive Health Institute
DOI
10.1097/MCG.0000000000002125
