Machine Learning Applications in Endoscopic Assessments

This research article highlights five key abstracts presented at ACG 2024, showcasing the potential of machine learning (ML) to enhance endoscopic assessments in inflammatory bowel disease (IBD). It discusses the challenges in endoscopy, opportunities for innovation, and the impact of real-world evidence on clinical decision-making. The findings emphasize the accuracy of ML models in predicting endoscopic scores and their implications for drug development and patient outcomes.