Abstract

Artificial intelligence (AI) refers to computer-based methodologies which use data to teach a computer to solve pre-defined tasks; these methods can be applied to identify patterns in large multi-modal data sources. AI applications in inflammatory bowel disease (IBD) includes predicting response to therapy, disease activity scoring of endoscopy, drug discovery, and identifying bowel damage in images. As a complex disease with entangled relationships between genomics, metabolomics, microbiome, and the environment, IBD stands to benefit greatly from methodologies that can handle this complexity. We describe current applications, critical challenges, and propose future directions of AI in IBD.

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