Plenary Event
Tuesday Morning Keynotes
20 February 2024 • 8:30 AM - 10:00 AM PST | Town & Country A 

8:30 AM - 8:35 AM:
Welcome and introduction

8:35 AM - 8:40 AM:
Robert F. Wagner Award finalists announcement for conferences 12930 and 12933


8:40 AM - 9:20 AM:
Unlocking the value of 3D printed medical devices in hospitals and universities

Frank J. Rybicki, Banner Medical Group, The Univ. of Arizona (United States)

Medical imaging data is often used inefficiently, and this happens most often for patients with abnormal imaging who require a complex procedure. This talk describes those patients, how their medical images undergo Computer Aided Design (CAD), and how that data reaches a Final Anatomic Realization, one of which is 3D printing. This talk highlights “keys” to “unlock” value when this clinical service line is performed in a hospital, and the critical role for medical engineers who work in that infrastructure. The talk includes medical oversight, data generation, and a specific, durable definition of value for medical devices that are 3D printed in hospitals. The talk also includes clinical appropriateness, and how it folds into accreditation for 3D printing in hospitals and universities. Up to the minute information on reimbursement for medical devices that are 3D printed in hospitals and universities will be presented.

Frank Rybicki received his PhD in Medical Engineering from MIT in 1995. He chairs the Department of Radiology, Banner University Medical Group and The University of Arizona, Phoenix. Dr. Rybicki founded the RSNA 3D Printing Special Interest Group. He launched and is Editor-in-Chief of 3D Printing in Medicine (3D Print Med), 2022 IF = 3.7. Dr. Rybicki edited the most widely sold book on medical 3D printing. The second edition of this book 3D Printing at Hospitals and Medical Centers: A Practical Guide for Medical Professionals will be released in January 2024.

This keynote is part of the Clinical and Biomedical Imaging conference.


9:20 AM - 10:00 AM:
Clinical AI model translation and deployment: creating a scalable, standardized, and responsible AI lifecycle framework in healthcare

David McClintock, Mayo Clinic (United States)

The use of artificial intelligence in healthcare is a current hot topic, generating tons of excitement and pushing multiple academic medical centers, startups, and large established IT companies to dive into clinical AI model development. However, amongst that excitement, one topic that has lacked direction is how healthcare institutions, from small clinical practices to large health systems, should approach AI model deployment. Unlike typical healthcare IT implementations, AI models have special considerations that must be addressed prior to moving them into clinical practice. This talk will review the major issues surrounding clinical AI implementations and present a scalable, standardized, and responsible framework for AI deployment that can be adopted by many different healthcare organizations, departments, and functional areas.

David McClintock is the Chair of the Division of Computational Pathology and Artificial Intelligence within the Department of Laboratory Medicine and Pathology at Mayo Clinic (Rochester, MN). His primary clinical interests include clinical informatics, clinical AI lifecycle and AI model deployment, digital pathology, and clinical laboratory workflow optimization/analytics. His research interests include the use of artificial intelligence and machine learning tools for improved diagnostics, more efficient workflows, and improved patient outcomes, in addition to the application of robotic process automation and computer vision within healthcare. Dr. McClintock has previously served as the President of the Association for Pathology Informatics (API, 2018) and currently serves as the Program Committee Chair for API.

This keynote is part of the Digital and Computational Pathology conference.


Event Details

FORMAT: General session with live audience Q&A to follow each presentation.
MENU: Coffee, decaf, and tea will be available outside presentation room.
SETUP: Assortment of classroom and theater style seating.