Uploaded September 2022 | Updated September 2026, 1 week ago
Artificial intelligence (AI) and machine learning are increasingly being applied to medicine in novel and diverse ways. Rima Arnaout, MD, joins us to demonstrate how machine learning research can be used in cardiovascular imaging. She will also explain how to evaluate new research on machine learning/AI and break down the complexities of convolutional neural networks and how they relate to the larger fields of cardiology and imaging.
Speaker:
Rima Arnaout, MD is an associate professor of cardiology, a Chan Zuckerberg Biohub investigator, and a faculty member in the Bakar Computational Health Sciences Institute, the Biological and Medical Informatics program, and the Center for Intelligent Imaging at UCSF. She is investigating whether machine learning can be used to detect standard and novel patterns in biomedical imaging in a scalable fashion, with the goals of decreasing diagnostic error in medical imaging and uncovering new phenotypes for precision medicine research.
Note: Closed captions will be available within 48-72 hours after posting.
Program
Bob Wachter: Introduction
00:2:45-00:43:42 – Rima Arnaout, MD, (associate professor of cardiology, Chan Zuckerberg Biohub investigator, faculty at the Bakar Computational Health Sciences Institute, the Biological and Medical Informatics program, and the Center for Intelligent Imaging at UCSF)
00:43:42-01:01 - Q&A with Rima Arnaout and Bob Wachter
See previous Medical Grand Rounds:
• September 15: A Fireside Chat with Renowned Pandemic Expert Michael Osterholm
youtu.be/z16SBJNKKds
• June 30: America’s Epidemic of Gun Violence: The State of the Science
youtube.com/watch?v=XihYtM8KGF8&t=106s
• June 23: Clinical Problem Solving with Sarah Goglin
youtube.com/watch?v=N02tUI5mQX8
• June 16: The Science Behind Real-World Data: Answering Today’s Questions Today
youtube.com/watch?v=wOWtTp11_YQ
See all UCSF Covid-19 grand rounds, which have been viewed over 3M times:
youtube.com/playlist?list=PLp2l8GCZXFqSgUfwaResQ7rGwKbGIUi_m
Artificial intelligence (AI) and machine learning are increasingly being applied to medicine in novel and diverse ways. Rima Arnaout, MD, joins us to demonstrate how machine learning research can be used in cardiovascular imaging. She will also explain how to evaluate new research on machine learning/AI and break down the complexities of convolutional neural networks and how they relate to the larger fields of cardiology and imaging.
Speaker:
Rima Arnaout, MD is an associate professor of cardiology, a Chan Zuckerberg Biohub investigator, and a faculty member in the Bakar Computational Health Sciences Institute, the Biological and Medical Informatics program, and the Center for Intelligent Imaging at UCSF. She is investigating whether machine learning can be used to detect standard and novel patterns in biomedical imaging in a scalable fashion, with the goals of decreasing diagnostic error in medical imaging and uncovering new phenotypes for precision medicine research.
Note: Closed captions will be available within 48-72 hours after posting.
Program
Bob Wachter: Introduction
00:2:45-00:43:42 – Rima Arnaout, MD, (associate professor of cardiology, Chan Zuckerberg Biohub investigator, faculty at the Bakar Computational Health Sciences Institute, the Biological and Medical Informatics program, and the Center for Intelligent Imaging at UCSF)
00:43:42-01:01 - Q&A with Rima Arnaout and Bob Wachter
See previous Medical Grand Rounds:
• September 15: A Fireside Chat with Renowned Pandemic Expert Michael Osterholm
youtu.be/z16SBJNKKds
• June 30: America’s Epidemic of Gun Violence: The State of the Science
youtube.com/watch?v=XihYtM8KGF8&t=106s
• June 23: Clinical Problem Solving with Sarah Goglin
youtube.com/watch?v=N02tUI5mQX8
• June 16: The Science Behind Real-World Data: Answering Today’s Questions Today
youtube.com/watch?v=wOWtTp11_YQ
See all UCSF Covid-19 grand rounds, which have been viewed over 3M times:
youtube.com/playlist?list=PLp2l8GCZXFqSgUfwaResQ7rGwKbGIUi_m
