# The utility of artificial intelligence in visualization of pediatric gastrointestinal mucosa

## TL;DR

This paper explores how artificial intelligence is being used to improve the visualization and diagnosis of pediatric gastrointestinal conditions.

## Contribution

The paper highlights emerging pediatric applications of AI in endoscopy, focusing on diagnosis and treatment optimization.

## Key findings

- AI is being used to improve visualization and diagnosis in pediatric gastrointestinal conditions.
- Applications include disease subtyping, lesion detection, and treatment optimization.
- Current research focuses on conditions like Crohn's disease and eosinophilic esophagitis.

## Abstract

The utilization of artificial intelligence (AI) is rapidly expanding in all areas of medicine. Pediatric gastroenterology is among the fields exploring the use of AI to better visualize the gastrointestinal tract and improve diagnosis, disease subtyping, lesion detection, risk prediction, and treatment optimization for better patient outcomes. AI shows promising developments and applications in complex diseases, such as Crohn's disease, polyposis syndromes, and eosinophilic esophagitis, where diagnosis and initial or subsequent management are impacted by mucosal visualization and analysis. This article summarizes how AI, machine learning, and these complex networks work in addition to addressing the limitations and ethical challenges faced with use of this budding technology. Although most available information on this topic comes from adult literature, this discussion focuses on current and emerging pediatric research and applications of AI in pediatric diagnostic and interventional endoscopy.