Artificial intelligence-driven precision management of Helicobacter pylori: an integrated framework from endoscopy and multi-omics to vaccine design and digital care

Helicobacter pylori ( H. pylori ) infection, affecting half of the world’s population, is the principal cause of peptic ulcer disease and gastric cancer, yet its clinical management is increasingly undermined by the rapidly escalating global burden of antibiotic resistance, the suboptimal accuracy of conventional diagnostic methods, and the declining efficacy of empirical therapeutic regimens. Artificial intelligence (AI) is rapidly reshaping this landscape, but existing research remains fragmented across single modalities. We propose a conceptual five-module framework that integrates AI approaches across the H. pylori care continuum: (1) global disease burden and the evolutionary dynamics of H. pylori drug resistance; (2) the application of multimodal AI, from convolutional neural networks to vision-language foundation models, for endoscopic early screening, pathological identification, and functional assessment; (3) the harnessing of machine learning (ML) on genomic and electronic health record data to decipher resistance mechanisms and generate personalized eradication regimens; (4) AI-driven vaccine target discovery and generative design, spanning reverse vaccinology to de novo immunogen creation; and (5) a digital closed-loop patient management platform that leverages new media and reinforcement learning to enhance adherence and eradication rates. We further delineate the core challenges of data bias, cross-scenario generalization, and the critical absence of prospective randomized evidence, and propose a future direction anchored in multimodal foundation models, federated learning, and continuous AI quality improvement. Rather than an established clinical pathway, this framework is proposed as a conceptual blueprint that, once prospectively validated, could upgrade AI-enabled H. pylori care from isolated image recognition toward an end-to-end “perception–reasoning–intervention” system, offering a blueprint for precision prevention and control.