Application of artificial intelligence in eosinophilic esophagitis

Area of Science:

• Gastroenterology
• Medical Informatics

Background:

• Eosinophilic esophagitis (EoE) is a chronic immune-mediated esophageal disease.
• Current EoE management relies on endoscopic and histopathological assessments, which can have inter-observer variability.

Purpose of the Study:

• To review the potential applications and challenges of artificial intelligence (AI) in eosinophilic esophagitis (EoE) management.
• To highlight AI's role in enhancing diagnostic accuracy, treatment prediction, and personalized medicine approaches for EoE.

Main Methods:

• Literature review of AI applications in EoE.
• Analysis of AI's performance in endoscopic and histopathological analysis.
• Discussion of AI's potential in identifying biomarkers and predicting treatment response.

Main Results:

• AI demonstrates comparable or superior performance to non-experts in diagnostic tasks.
• AI aids in standardizing EoE assessments (e.g., EREFS, EoEHSS).
• AI facilitates precision medicine by identifying molecular phenotypes and predicting treatment outcomes.

Conclusions:

• AI offers significant potential to improve EoE diagnosis, management, and treatment personalization.
• Addressing challenges like explainability (XAI), validation in diverse cohorts, and regulatory approval is crucial for AI integration.
• Future research should focus on pediatric populations, non-invasive monitoring, and integrated AI platforms for proactive EoE care.