Geoff Rubin
- Chair, Department of Medical Imaging
- Professor, Medical Imaging
- Member of the Graduate Faculty
- (520) 626-9440
- AHSC, Rm. 20A
- Tucson, AZ 85724
- grubin@arizona.edu
Biography
Geoffrey D. Rubin, MD, MBA, FACR, FAHA, FSABI, FNASCI is Professor and Chair of the Department of Medical Imaging at the University of Arizona and Service Chief of Medical Imaging at Banner University Medicine in Tucson, Arizona. He was previously the George B. Geller Distinguished Professor and Chair of Radiology at Duke University. He is a past President of the Fleischner Society, the Society for Body Imaging, the North American Society for Cardiovascular Imagers, and currently President and Board Chair of the International Society for Computed Tomography, founding Board Member of the Radiology Leadership Institute of the American College of Radiology, Board Member of RAD-AID International, and host of the acclaimed RLI podcast, “Taking the Lead.” Prior to joining Duke University in 2010, he was professor of radiology at Stanford University, where he also served as Associate Dean for Clinical Affairs in the Stanford School of Medicine and Chief of Cardiovascular Imaging. In 2014 he earned an MBA from the Fuqua School of Business at Duke University where he was recognized as a Fuqua Scholar and represented his class as their commencement speaker. He is the author of over 300 published works and principal investigator for over $10M in research grants from the National Institutes of Health.
Degrees
- M.B.A.
- Fuqua School of Management, Duke University, Durham, North Carolina, United States
- M.D.
- University of California, San Diego, La Jolla, California, United States
- B.S. Chemistry and Biology
- California Institute of Technology, Pasadena, California, United States
Work Experience
- Duke University, Durham, North Carolina (2010 - 2020)
- Stnford University (1993 - 2010)
Awards
- Gold Medal
- Association of Academic Radiologists, Spring 2024
- Honorary Member
- Japan Radiological Society, Spring 2024
- Honored Educator Award
- Radiological Society of North America, Fall 2021
Interests
No activities entered.
Courses
No activities entered.
Scholarly Contributions
Journals/Publications
- More infoMultiple applications for machine learning and artificial intelligence (AI) in cardiovascular imaging are being proposed and developed. However, the processes involved in implementing AI in cardiovascular imaging are highly diverse, varying by imaging modality, patient subtype, features to be extracted and analyzed, and clinical application. This article establishes a framework that defines value from an organizational perspective, followed by value chain analysis to identify the activities in which AI might produce the greatest incremental value creation. The various perspectives that should be considered are highlighted, including clinicians, imagers, hospitals, patients, and payers. Integrating the perspectives of all health care stakeholders is critical for creating value and ensuring the successful deployment of AI tools in a real-world setting. Different AI tools are summarized, along with the unique aspects of AI applications to various cardiac imaging modalities, including cardiac computed tomography, magnetic resonance imaging, and positron emission tomography. AI is applicable and has the potential to add value to cardiovascular imaging at every step along the patient journey, from selecting the more appropriate test to optimizing image acquisition and analysis, interpreting the results for classification and diagnosis, and predicting the risk for major adverse cardiac events.
