Gastroenterology & Artificial Intelligence: 3rd Annual Global Artificial Intelligence Summit | September 2021-Utilizing AI and ML in IBD Diagnosis and Prognostication

Video Transcription

Video Summary

In this video, Dr. Rubin discusses the application of artificial intelligence (AI) and machine learning (ML) in the field of inflammatory bowel disease (IBD). He highlights the challenges in IBD management, such as delays in diagnosis and lack of predictive therapeutic biomarkers. Dr. Rubin explains that AI and ML have the potential to improve diagnosis, prognosis, therapy choices, and disease monitoring in IBD. He provides several examples of how AI and ML have been used in the field, including the development of a model to predict individualized risk of complications in Crohn's disease, the use of serum markers to assess mucosal healing in ulcerative colitis, the incorporation of laboratory values for predicting treatment response, and the analysis of capsule endoscopy videos to predict the presence of strictures in Crohn's disease. Dr. Rubin also mentions ongoing research on the use of AI and ML in assessing endoscopic and histologic inflammation in ulcerative colitis, and the use of biosensors to predict disease relapse in IBD. He concludes by emphasizing the potential of AI and ML in achieving objective disease control in IBD.

Asset Subtitle

David Rubin, MD, FASGE

Keywords

artificial intelligence

machine learning

inflammatory bowel disease

diagnosis

therapeutic biomarkers