Gastroenterology and Artificial Intelligence: 4th Annual Global Artificial Intelligence Summit | August 2022-Learning from Other Disciplines

Pdf Summary

In this document, Dr. Charles E. Kahn Jr. discusses the importance of learning from other specialties in the field of radiology. He emphasizes the need for thorough validation of artificial intelligence (AI) algorithms used in healthcare, referencing a study that found diminished algorithm performance when tested on external datasets. The document also highlights the importance of considering key questions when integrating AI applications into clinical workflows, such as the intended problem the application is meant to solve, potential benefits and risks, validation, interoperability, IT infrastructure requirements, and compliance with medical device and data protection regulations. Additionally, the document suggests conducting return on investment analyses, ensuring maintenance of the product, providing user training and follow-up, and establishing protocols for handling potential malfunctions or erroneous results. Dr. Kahn provides his contact information for further inquiries and references relevant resources on the Radiological Society of North America (RSNA) website.

Asset Subtitle

Charles Kahn, Jr., MD, MS

Keywords

radiology

AI algorithms

healthcare

algorithm performance

clinical workflows

interoperability

medical device regulations

data protection regulations

user training

RSNA