ASGE Weekend Endoscopy: AI in IBD | August 2025-2025Aug AI in IBD for GI LEAP

Video Transcription

Video Summary

In this comprehensive ASGE Weekend Endoscopy Live session, experts discuss the evolving role of artificial intelligence (AI) in managing inflammatory bowel disease (IBD). Current IBD diagnosis relies heavily on colonoscopy and histology, but variability in disease severity assessment among clinicians remains a challenge. AI, particularly modern computer vision technologies, offers promise in standardizing and automating disease severity scoring, enhancing reliability and reproducibility across modalities like white light and virtual chromoendoscopy.<br /><br />Panelists highlight AI’s ability to analyze endoscopic images and videos, producing heat maps and vascular assessments that correlate closely with histology and clinical outcomes. Advanced tools like endocytoscopes offer real-time histologic evaluation during endoscopy. Moreover, AI assists with difficult issues such as detecting dysplasia—a rare but aggressive lesion—through enhanced imaging and synthetic data sets, addressing low prevalence and regulatory hurdles.<br /><br />In personalized medicine, AI can synthesize diverse data, including clinical parameters, imaging, histology, and biomarkers, to inform therapeutic decisions and predict disease course. Challenges include integrating multi-modal data and ensuring clinical applicability. Remote monitoring through patient-generated data and digital health tools is emerging but not yet widely adopted.<br /><br />On drug discovery, AI expedites identifying viable therapeutic molecules by predicting molecular interactions and properties, drastically reducing development timelines.<br /><br />Looking ahead, AI’s transformative potential lies both in enhancing clinical workflows—enabling better management of growing patient populations—and in advancing basic science to deepen understanding of IBD biology. Effective deployment requires collaboration among clinicians, researchers, industry, and regulatory bodies to validate AI tools, integrate multimodal data, and address economic and practical implementation challenges.

Keywords

Artificial Intelligence

Inflammatory Bowel Disease

Endoscopy

Colonoscopy

Disease Severity Scoring

Computer Vision

Histology Correlation

Dysplasia Detection

Personalized Medicine

Drug Discovery