Using an artificial intelligence (AI) tool that emulates how humans visualize and is trained to recognize and classify images, investigators constructed a model that predicts the postoperative recurrence of Crohn disease with high accuracy by evaluating histological images. The AI tool also revealed previously unrecognized differences in adipose cells and significant differences in the extent of mast cell infiltration in the subserosa, or outer lining of the intestine, comparing patients with and without disease recurrence. The findings appear in The American Journal of Pathology. The 10-year rate of postoperative symptomatic recurrence of Crohn disease, a chronic inflammatory gastrointestinal disease, is estimated at 40%. Although there are scoring systems to evaluate Crohn disease activity and the existence of postoperative recurrence, no scoring system had been developed to predict whether Crohn disease might recur.

A new study finds that an artificial intelligence model can predict whether Crohn's disease will recur after surgery. A deep learning model trained to analyze histological images of surgical specimens accurately classified patients with and without Crohn's disease recurrence, investigators report in The American Journal of Pathology. According to researchers, more than 500,000 individuals in the United States have Crohn's disease. Crohn's disease is a chronic inflammatory bowel disease that damages the digestive system lining. It can cause digestive system inflammation, which may result in abdominal pain, severe diarrhea, exhaustion, weight loss, and malnutrition.