Spatiotemporal analysis of small bowel capsule endoscopy videos for outcomes prediction in Crohn's disease.

Background: Deep learning techniques can accurately detect and grade inflammatory findings on images from capsule endoscopy (CE) in Crohn's disease (CD). However, the predictive utility of deep learning of CE in CD for disease outcomes has not been examined.

Objectives: We aimed to develop a deep learning model that can predict the need for biological therapy based on complete CE videos of newly-diagnosed CD patients.