Can we please use a public calendar? After all the debates about the "right way" to do calendars mine does not show that we have a tea talk on Friday.

On Tue, May 14, 2019 at 11:47 AM Rim Assouel rim.assouel@gmail.com wrote:

This week we have Dan Sodickson from NYU giving a talk on Machine Learning and Medicine: How AI will change the way we see patients, and the way we see ourselves. at 10h30 in Auditorium H2.

Auditorium H2 is on the 2nd floor of the 6650 building. Indications will be put from the agora and the elevators as well !

Will this talk be streamed ? yes

See you there! The Tea Talk Team

TITLE Machine Learning and Medicine: How AI will change the way we see patients, and the way we see ourselves.

ABSTRACT Just as astronomy constitutes the exploration of outer space, advances in medicine may be seen as an ever-deeper exploration of inner space. This talk will explore how that inwardly-focused exploration may be transformed in the age of machine learning. I will begin by attempting to convey a view of artificial intelligence from the vantage point of medicine: what physicians tend to feel about AI, what they tend to know, and what they generally do not know. I will briefly cite examples of productive (and less productive) emerging uses of AI in medicine. I will then focus on medical imaging in particular, and will summarize some of the goals, early outcomes, challenges, and future directions of the fastMRI collaboration between NYU School of Medicine and Facebook AI Research, in which deep learning is being used to accelerate MRI beyond previous limits. In addition to being of great value to patients, physicians, and healthcare systems, acceleration serves as a potent enabler of several emerging trends that promise to reshape the future of biomedical imaging, including a move from carefully-staged snapshots to continuous streaming, and a move from imitating the eye to emulating the brain. In this context, I will explore how AI may change not only the analysis of images and other sensor data streams, but also the design and use of future imaging devices. I will conclude with a few speculations about potential changes in the way we interact with the medical system and even how we perceive the world around us. Throughout, I will attempt to highlight areas in which data scientists can add value to the day-to-day practice of medical imaging, to the improvement of human health, and to the ongoing exploration of inner space.

BIO Daniel K. Sodickson MD, PhD is Vice-Chair for Research in the Department of Radiology at NYU Langone Health, Professor of Radiology and Physiology & Neuroscience at NYU School of Medicine, and Professor of Biomedical Engineering at the NYU Tandon School of Engineering. He has led a transformation of imaging research at NYU Langone, bringing the Radiology Department’s national research ranking from #17 to #5, and earning the department’s Center for Advanced Imaging Innovation and Research (CAI2R) a designation as a national Biomedical Technology Resource Center. Dr. Sodickson’s research aims at seeing what has previously been invisible, in order to improve human health. He is credited with founding the field of parallel imaging, in which distributed arrays of detectors are used to gather magnetic resonance images at previously inaccessible speeds. Parallel imaging hardware and software is now an integral part of MRI machines, and is used routinely in MRI scans worldwide. In 2006, Dr. Sodickson was awarded the Gold Medal of the International Society for Magnetic Resonance in Medicine (ISMRM), and he recently completed a term as ISMRM president. Last year, he helped to initiate the fastMRI collaboration between NYU and FAIR, and he continues to work closely with colleagues at FAIR. He is currently in the process of launching a new institute – Tech4Health – designed to bring emerging technologies such as continuous sensing and artificial intelligence to biomedicine.

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