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

ABSTRACT:

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.

Design

This was a retrospective cohort study. The study cohort included treatment-naïve CD patients that have performed CE (SB3, Medtronic) within 6 months of diagnosis. Complete small bowel videos were extracted using the RAPID Reader software.

Methods

CE videos were scored using the Lewis score (LS). Clinical, endoscopic, and laboratory data were

SUBMITTER: Kellerman R 

PROVIDER: S-EPMC10333642 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature