Multimodal artificial intelligence technology in the precision diagnosis and treatment of gastroenterology and hepatology: Innovative applications and challenges.

With the rapid development of artificial intelligence (AI) technology, multimodal data integration has become an important means to improve the accuracy of diagnosis and treatment in gastroenterology and hepatology. This article systematically reviews the latest progress of multimodal AI technology in the diagnosis, treatment, and decision-making for gastrointestinal tumors, functional gastrointestinal diseases, and liver diseases, focusing on the innovative applications of endoscopic image AI, pathological section AI, multi-omics data fusion models, and wearable devices combined with natural language processing. Multimodal AI can significantly improve the accuracy of early diagnosis and the efficiency of individualized treatment planning by integrating imaging, pathological data, molecular, and clinical phenotypic data. However, current AI technologies still face challenges such as insufficient data standardization, limited generalization of models, and ethical compliance. This paper proposes solutions, such as the establishment of cross-center data sharing platform, the development of federated learning framework, and the formulation of ethical norms, and looks forward to the application prospect of multimodal large-scale models in the disease management process. This review provides theoretical basis and practical guidance for promoting the clinical translation of AI technology in the field of gastroenterology and hepatology.