Rapid Endoscopic Diagnosis of Benign Ulcerative Colorectal Diseases With an Artificial Intelligence Contextual Framework.
Journal:
Gastroenterology
PMID:
38583724
Abstract
BACKGROUND & AIMS: Benign ulcerative colorectal diseases (UCDs) such as ulcerative colitis, Crohn's disease, ischemic colitis, and intestinal tuberculosis share similar phenotypes with different etiologies and treatment strategies. To accurately diagnose closely related diseases like UCDs, we hypothesize that contextual learning is critical in enhancing the ability of the artificial intelligence models to differentiate the subtle differences in lesions amidst the vastly divergent spatial contexts.
Authors
Keywords
Adult
Aged
Artificial Intelligence
Case-Control Studies
Colitis, Ulcerative
Colon
Colonoscopy
Diagnosis, Differential
Female
Humans
Image Interpretation, Computer-Assisted
Machine Learning
Male
Middle Aged
Predictive Value of Tests
Reproducibility of Results
Retrospective Studies
ROC Curve
Video Recording