5th Global Gastroenterology and Artificial Intelligence Summit (Live)

Pdf Summary

This document discusses the use of artificial intelligence (AI) in training for gastroenterology. It explores the various applications of AI in endoscopy training, including withdrawal time, withdrawal stability, bowel preparation quality, and real-time polyp detection. The document also highlights the potential impacts of AI on skills acquisition, cognitive load, and desirable difficulties in learning. <br /><br />Several challenges are identified, such as the need for AI literacy among endoscopists and the inclusion of less experienced endoscopists in AI research. The integration of AI into training is outlined, including the assessment of educational needs, selection of appropriate AI technology, evidence-informed curricular integration, user training for both trainees and trainers, implementation, and continuous evaluation and improvement. <br /><br />Ethical considerations, data privacy, and equity, diversity, and inclusion are also mentioned in relation to AI in gastroenterology. The document emphasizes the importance of trainer education to support the implementation of AI curriculum. <br /><br />Future research areas are identified, such as assessing the impact of AI on skills acquisition, determining the effectiveness of AI in training, and reaching a consensus on core curricular topics for gastroenterology. The author also invites questions and comments regarding the curriculum for AI in gastroenterology.

Meta Tag

Concept Artificial Intelligence

Concept Gastroenterology Training Program

Concept Endoscopy

Concept Computer-Aided Detection

Concept Computer-aided Diagnosis

Keywords

artificial intelligence

gastroenterology

endoscopy training

withdrawal time

withdrawal stability

bowel preparation quality

real-time polyp detection

skills acquisition

cognitive load

AI literacy

Artificial Intelligence

Gastroenterology Training Program

Endoscopy

Computer-Aided Detection

Computer-aided Diagnosis