Wednesday, November 10, 2021 4pm to 5pm
About this Event
Data Citizens: A Distinguished Lecture Series is an ongoing course of in-depth talks by experts in the field of data science on a wide variety of topics including data visualization, big data, artificial intelligence, and predictive analytics. Join us as we welcome Dr. Eliot Siegel, Professor and Vice Chair of Research Information Systems at the University of Maryland School of Medicine, Department of Diagnostic Radiology and Nuclear Medicine, and Chief of Radiology and Nuclear Medicine for the Veterans Affairs Maryland Health Care System, both in Baltimore, MD, for a talk on AI in Medical Imaging: Hype, Reality, and Future.
This lecture series is free and open to the public.
TITLE: "AI and the Presumed Demise of Radiologists"
Paraphrasing Mark Twain’s famous quote, “The reports of my death are greatly exaggerated,” predictions made during the past half a dozen years about the demise of “Radiologist” as a profession have been made with alarming frequency. Geoffrey Hinton, one of the “fathers” of Deep Learning stated that “They should stop training Radiologists now.” Andrew Ng, Professor of Computer Science at Stanford, declared that it would be easier to replace a Radiologist than his personal assistant. Ezekiel Emmanuel proclaimed in the New England Journal of Medicine that, Radiologists, as a profession, could cease to exist in the next few years and that AI was the greatest threat to the practice. A half a dozen years later, it has become obvious that those predictions made by some of the most acclaimed “experts” in Computer Science and Medicine got it completely wrong. This talk will explore the fascinating, daunting, and yet tantalizing challenges associated with the implementation of AI in clinical practice for Diagnostic Imaging and will discuss the hype, reality, and future of Deep Learning for Diagnostic Imaging.
AudienceAlumni General Public Faculty Students Students - Undergrad Students - Grad/Professional Students - International Students - Prospective Students - Admitted Staff
Tagsai radiology machinelearning TELEMEDICINE digitalimaging medicalimaging electronichealthrecords
DepartmentClinical & Translational Science Institute, Institute for Data Science and Computing, Research & Scholarship