Gastroenterology and Artificial Intelligence: 3rd Annual Artificial Intelligence Summit (On-Demand) | September 2021-AI and Radiology: Lessons for Clinical Implementation in GI

Video Transcription

Video Summary

In the video, Dr. Chuck Kahn, a professor and vice chair of radiology at UPenn, discusses the lessons learned from applying artificial intelligence (AI) in radiology and how it can impact gastroenterology and endoscopy. He emphasizes the importance of rigorous testing to understand the capabilities and limitations of AI systems. He presents examples where AI systems detected features unrelated to the actual medical condition, highlighting the need for thorough validation. Dr. Kahn also discusses the importance of defining accurate ground truth data and ensuring that it is well-defined and measured consistently. He mentions the value of AI competitions and challenges in advancing AI technology and improving performance. In addition, he stresses the importance of establishing standards and common data elements to facilitate information exchange and comparison across AI systems. Dr. Kahn concludes by encouraging practitioners to test AI systems rigorously, understand the ground truth data, and work towards developing standards and participating in AI competitions and challenges.

Asset Subtitle

Charles Kahn, MD

Keywords

artificial intelligence

radiology

gastroenterology

rigorous testing

ground truth data