Application of artificial intelligence in eosinophilic esophagitis - Xu, Xiaoming; Chen, Hualei; Chen, Yun; Fan, Lijuan (Frontiers in Immunology, 2025)
Artificial intelligence (AI) shows great promise in eosinophilic esophagitis (EoE) management. It enhances diagnostic accuracy and consistency in endoscopic and histopathological analyses, with performance comparable to or exceeding non-experts. AI aids in standardizing assessments like EREFS and EoEHSS, identifies molecular phenotypes and novel biomarkers, and predicts treatment responses, facilitating precision medicine. However, challenges exist: “black box” issues demand explainable AI (XAI) for trust; validation in large, diverse cohorts, ensuring model generalization, and regulatory approval are crucial; data governance, privacy, and algorithmic integrity require attention. Future priorities include researching pediatric populations, improving treatment response prediction, and developing non-invasive monitoring tools. An integrated multimodal AI platform may transform EoE care from reactive to proactive, personalized approaches.