Gastroenterology in the age of artificial intelligence: Bridging technology and clinical practice

Table 1 Artificial intelligence applications in gastroenterology

Application domain	AI technologies used	Clinical utility	Examples
Diagnostic endoscopy	CNN, CADe, CADx	Real-time polyp detection, dysplasia localization	GI Genius, EndoAngel
Disease prediction	GBM, XGBoost, SVM	Severity scoring, relapse prediction, treatment response	IBD, acute pancreatitis models
Drug discovery	Deep learning, AlphaFold2	Target identification, ADMET profiling, formulation optimization	AI-driven computational chemistry
Tumor boards	Multimodal AI integration	Personalized therapy recommendations in GI cancers	AI-assisted tumor boards
Remote monitoring	RNN, wearable integration	Decompensation alerts in cirrhosis, post-transplant monitoring	Telemonitoring platforms
Education and NLP	Transformers, NLP	Automated reporting, AI tutors for endoscopy training	GastroAGI, report auto-generation
Regulatory-approved tools	CNN-based commercial systems	Clinical deployment for screening and diagnosis	GI Genius (FDA), EndoAngel (CE)

NLP: Natural language processing; CNN: Convolutional neural network; CADx: Computer-aided diagnosis; CADe: Computer-aided detection; GBM: Gradient boosting machine; XGBoost: Extreme gradient boosting; SVM: Support vector machine; RNN: Recurrent neural network; ADMET: Absorption, distribution, metabolism, excretion and toxicity; AI: Artificial intelligence; GI: Gastrointestinal; IBD: Inflammatory bowel disease; GastroAGI: Artificial intelligence-powered learning in gastroenterology; FDA: Food and Drug Administration; CE: Conformite Europeenne.