Application of Artificial Intelligence in Celiac Disease: from diagnosis to patient follow-up

Celiac disease (CD) is an autoimmune digestive condition that is distinguished by inflammation of the small intestine as a result of gluten ingestion. Its worldwide prevalence is approximately 1%. Despite progress in understanding CD, challenges in pathogenesis, diagnosis, treatment, and management persist. Genetic and environmental factors, such as HLA and non-HLA genes, gluten, gut microbiota imbalance, and immune responses involving CD4+ T cells, influence CD. Diagnostic challenges arise due to diverse clinical presentations and overlap with other gastrointestinal disorders. Following a gluten-free diet (GFD) strictly is the primary treatment for CD, but this diet presents social, psychological, and financial hurdles. Artificial intelligence (AI) has emerged as a potent instrument in CD management. Techniques like machine learning (ML), deep learning (DL), natural language processing (NLP), and computer-aided algorithms have shown promise in CD diagnosis by improving microbiome analysis, disease prediction, interpretation of medical records and endoscopy images. AI-based decision-support systems can aid in diagnosis. AI-driven personalized nutrition and gluten contamination monitoring techniques offer potential improvements for treatment. Overall, AI has potential in addressing CD challenges and enhancing patient outcomes.