Artificial Intelligence-Based Classification and Prognostic Prediction in Small Bowel Crohn's Disease

This retrospective observational study aims to develop an artificial intelligence-based system for the precise classification and prognostic prediction of small bowel Crohn's disease. The study includes 437 patients with Crohn's disease who were hospitalized at Shanghai Tenth People's Hospital between January 1, 2020, and January 31, 2025. Clinical information, laboratory results, endoscopic findings, computed tomography enterography or magnetic resonance enterography images, and available pathological and molecular data will be collected from existing medical records. Artificial intelligence-based image segmentation and multimodal analysis will be used to identify and quantify intestinal lesions, strictures, mesenteric changes, fistulas, abscesses, and other disease characteristics. The study will examine whether these features can classify patients more accurately and predict clinical outcomes, including response to medical treatment, treatment failure or switching, and the need for surgery. The resulting system may support individualized assessment and clinical decision-making for patients with small bowel Crohn's disease.