Gastroenterology and Artificial Intelligence: 4th Annual Global Artificial Intelligence Summit (On-Demand | August 2022-Introducing AI in GI Fellowship Education

Pdf Summary

This document is a presentation about integrating artificial intelligence (AI) into gastrointestinal (GI) fellowship education. The speaker, Dr. Rajesh Keswani, discusses the need to improve endoscopy quality and trainee skills in gastroenterology. The variation in attending competency and quality is highlighted, indicating the need for methods to flatten trainee learning curves and remediate their skills.<br /><br />Dr. Keswani suggests several ways to improve endoscopic skill, including education, delivering quality metrics feedback, delivering skills feedback, simulation-based learning, and AI. The importance of education and obtaining it from industry, societies, and training programs is emphasized.<br /><br />The document also explores the advantages of using AI to measure colonoscopy skill, such as providing feedback and aiding trainee diagnostics and therapeutics. Machine learning is proposed as a method to measure quality, and the ideal future state is discussed.<br /><br />Additionally, a study is mentioned that evaluates the frequency of trainees missing lesions during colonoscopies. Trainee overall miss rates and the decrease in miss rates as training progresses are reported. The difficulty of identifying polyps and the potential role of AI in improving detection are addressed.<br /><br />The presentation concludes with the unanswered question of whether AI can improve trainee recognition of subtle neoplasia or if it leads to reduced development of independent skills. The document concludes with Dr. Keswani's contact information.<br /><br />Overall, the document emphasizes the need for AI integration in GI fellowship education to enhance trainee skills, improve endoscopy quality, and address the challenges in detecting polyps.

Asset Subtitle

Rajesh Keswani, MD

Keywords

artificial intelligence

gastrointestinal fellowship education

endoscopy quality

trainee skills

education

simulation-based learning

AI measurement

colonoscopy skill

polyp identification

subtle neoplasia recognition