Application of Artificial Intelligence-Powered Research in Gastrointestinal Pathophysiology: Unveiling Intestinal Pathobionts and Microbiota Dysbiosis

Export Emerging evidence indicates a critical role of an imbalanced microbiota ecosystem in the development of human diseases. The presence of decreased beneficial microbes and increased harmful bacteria is widely accepted as one of the etiologies of intestinal and extraintestinal disorders. Pathobionts (commensal-derived opportunistic pathogens) with colitogenic and tumorigenic capabilities are now recognized as contributors to the pathogenesis of inflammatory bowel diseases (IBDs) and colitis-associated colorectal cancers (CRC). Aside from classical wet-lab techniques and traditional scientific paper-mining approaches, the innovation of artificial intelligence (AI)-powered biotechnology devices and tools, such as machine learning, deep learning, and natural language processing, is a valuable asset for modern researchers to enhance data interpretation and develop precision medical strategies. This review discusses potential AI-assisted approaches in gastrointestinal (GI) pathophysiological research, with a focus on investigating gut dysbiosis. The advantages and shortcomings of AI-generated data and research strategies will be assessed in the context of dysbiosis-driven IBD and CRC. Studies that apply methods leveraging advanced computational techniques and AI-assisted research methodologies would help better understand the complex interactions within the microbiome and their interactions with hosts. A multidisciplinary approach to GI pathophysiological research that integrates AI tools can pave the way for innovative interventions targeting bacteria, with a focus on colitis and cancer.