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.