Conventional small-bowel capsule endoscopy reading vs proprietary artificial intelligence auxiliary systems: Systematic review and meta-analysis.

ABSTRACT:

Background and study aims

Small-bowel capsule endoscopy (SBCE) is the gold standard for diagnosing small bowel (SB) pathologies, but its time-consuming nature and potential for human error make it challenging. Several proprietary artificial intelligence (AI) auxiliary systems based on convolutional neural networks (CNNs) that are integrated into SBCE reading platforms are available on the market and offer the opportunity to improve lesion detection and reduce reading times. This meta-analysis aimed to evaluate performance of proprietary AI auxiliary platforms in SBCE compared with conventional, human-only reading.

Methods

A systematic literature search was conducted to identify studies comparing AI-assisted SBCE readings with conventional readings by gastroenterologists. Per

SUBMITTER: Cortegoso Valdivia P 

PROVIDER: S-EPMC11922306 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature