Emerging use of artificial intelligence in inflammatory bowel disease

Abstract

Inflammatory bowel disease (IBD) is a complex, immune-mediated gastrointestinal disorder with ill-defined etiology, multifaceted diagnostic criteria, and unpredictable treatment response. Innovations in IBD diagnostics, including developments in genomic sequencing and molecular analytics, have generated tremendous interest in leveraging these large data platforms into clinically meaningful tools. Artificial intelligence, through machine learning facilitates the interpretation of large arrays of data, and may provide insight to improving IBD outcomes. While potential applications of machine learning models are vast, further research is needed to generate standardized models that can be adapted to target IBD populations. 

Keywords: Artificial intelligence; Machine learning; Automated diagnostics; Colorectal neoplasia screening; Multiomic data; Predictive models

Core Tip: Artificial intelligence (AI) is a novel technological advancement that is rapidly growing in the field of inflammatory bowel disease. The use of AI and machine learning has been shown to aid in diagnosing and understanding severity of disease, predicting treatment response along with likelihood of disease recurrence and assisting with colorectal neoplasia screening in this patient population. Further studies are needed to understand the full impact AI may have on improving Crohn’s disease and ulcerative colitis patient outcomes.