ARTICLE HIGHLIGHTS Advances in artificial intelligence (AI) show promise for improving treatment response prediction, decision-making, and precision medicine in inflammatory bowel disease (IBD). In particular, AI could improve precision medicine for IBD by enabling identification of disease subtypes, prediction of disease progression and treatment response, selection of personalized treatments, and remote monitoring. Predictive models can benefit clinicians and patients alike by optimizing shared decision-making processes; patients can also use AI to cope with daily and long-term challenges of the disease. Beyond patients and practitioners, predictive models may positively impact healthcare structures and payers by enabling effective healthcare-resource utilization. To increase the accuracy and efficiency of AI models, biomarkers, patient-reported outcomes, and disease scores should be combined within predictive models, and the outputs should be compared with clinical trial data and real-world data for validation.
【저자키워드】 artificial intelligence, precision medicine, Inflammatory bowel disease, Computational model, Crohn’s disease, Shared decision-making, fecal calprotectin, Mucosal healing,