AI and data science

The study maps cell types and signals linked to submucosal scarring in Crohn's disease, a complication without drug treatments that often requires surgery. Understanding these mechanisms could point to future therapeutic...

Genetic ancestry can influence IBD risk and disease course, and most prior studies focused on European populations.

Distinguishing Crohn’s from ulcerative colitis can be hard and often requires invasive tests. A reliable blood test would speed diagnosis and help patients start the right treatments sooner. This study is an early step...

AI-assisted capsule endoscopy may improve detection of Crohn’s disease lesions and reduce missed findings, which could affect diagnosis and monitoring. People with IBD may see faster or more consistent reads of capsule...

This study suggests machine learning of stool microbiome data could eventually help distinguish IBD (especially Crohn’s) from healthy people and some other bowel or systemic conditions.

A predictive model for temporary stoma could influence surgical planning for people with Crohn’s disease, helping tailor decisions and expectations around intestinal resection.

A validated AI biomarker that predicts which IBD treatments are likely to work could reduce trial-and-error in treatment choices, potentially shortening time to effective therapy for people with Crohn's disease or...

This paper highlights potential ubiquitination-related genes and immune-cell patterns that could help researchers understand Crohn’s disease biology and point to new targets for lab validation. For patients, it signals...

This notes a new oral investigational drug (Amelenodor/NX-13) in Phase I for Crohn’s and ulcerative colitis and highlights industry predictions about its chances of advancing. People with IBD may want to know about...