Artificial intelligence (AI) is redefining the management of inflammatory bowel diseases (IBD) by enhancing diagnostic accuracy, refining disease classification, and optimizing disease monitoring. This review highlights AI’s potential to transform IBD management by streamlining clinical workflows, improving diagnostic precision, and supporting personalized treatment strategies. By addressing the limitations of traditional clinical assessments including variability, subjectivity, and resource intensity, AI offers unbiased, consistent, and efficient solutions. Concluding with a forward-looking perspective, this paper emphasizes how integrating AI into clinical practice could lead to more precise, proactive, and patient-centric approaches to IBD care, ultimately enhancing clinical outcomes and quality of life for these patients.

Background: Fecal calprotectin (FC) is a promising biomarker for assessing ulcerative colitis (UC) endoscopic activity. However, the optimal FC cutoff to identify each Mayo endoscopic subscore (MES) remains inconclusive. Methods: The electronic medical records of 177 adult UC patients evaluated at Mayo Clinic Rochester from January 2017 to March 2023 were retrospectively reviewed, obtaining clinical data and US-based Werfen Diagnostics FC levels collected within 30 days before colonoscopy or flexible sigmoidoscopy. Three independent inflammatory bowel disease specialist endoscopists blindly reviewed the most severe endoscopic images for grading MES. Results: The median interval between FC collection and endoscopy was 2 days. Fecal calprotectin showed strong positive correlations with MES (Spearman’s r = 0.709; P < .01) and other clinical parameters. Fecal calprotectin cutoff of 60 mcg/g effectively distinguished MES 0 from MES 1-3 (sensitivity, 0.78; specificity, 0.97; area under the receiver operating characteristic curve [AUC], 0.901) and predicted clinical remission (Total Mayo Score ≤2 and no subscore >1; sensitivity, 0.83; specificity, 0.98; AUC, 0.921). Fecal calprotectin cutoff of 110 mcg/g effectively differentiated MES 0-1 from MES 2-3 (sensitivity, 0.86; specificity, 0.87; AUC, 0.915), while a cutoff of 310 mcg/g distinguished MES 0-2 from MES 3 (sensitivity, 0.80; specificity, 0.76; AUC, 0.820). Conclusions: This study supports the reliability and applicability of FC as a valuable marker of endoscopic inflammation, particularly in distinguishing MES 0 from MES 1-3 using the FC cutoff of 60 mcg/g. Sensitivity analysis demonstrated robust results.