Webinar: Cloud-Scale COVID-19 AI Research and Collaboration in Radiology
Data management is a key component to developing AI software. Organizations need adaptable, scalable infrastructure that can provide access to curated data while maintaining strict privacy and compliance standards and supporting secure sharing across multiple institutions. Learn how a small, investigator-initiated project developed into a valuable COVID-19 chest CT dataset using Flywheel's research data management platform. You will also hear how Imbio is exploring the correlation between lung injury severity and patient prognosis, as well as developing AI to diagnose COVID-19.
Digital transformation professionals, radiologists, data scientists, and clinical and translational imaging leads should attend to learn about integrating radiology research and AI solutions to enable collaboration and improve R&D efficiency.
The webinar will cover:
Kathryn Olsen, M.D.
Cardiothoracic Radiologist and Clinical Associate Professor
Banner Health/University of Arizona College of Medicine Phoenix
Dr. Kathryn Olsen is the newest faculty member of the University of Arizona College of Medicine. However, during the initial onset of the COVID-19 pandemic, she worked for the largest radiology practice in the Denver metro and northern Colorado area. She established an unprecedented level of collaboration among four regional healthcare systems, resulting in a dataset of initial chest CTs obtained prior to hospitalization from 10 hospitals. She is currently leading a team of radiologists and clinicians to investigate both the diagnostic and prognostic utility of chest CT in the acute and subacute presentations of COVID-19.
Daniel J Rafter, M.D.
Dr. Daniel Rafter is a Product Manager at Flywheel and has been with the company since July of 2020. He is responsible for curating a wide array of product features and is most intimately involved in the design of clinical research workflow features. He brings a diverse entrepreneurial and clinical background that is best highlighted by his five years directing neurotrauma research at a Level-1 Trauma Center. He is passionate about empowering researchers, like himself, to optimize their study life cycles so that their efforts can remain appropriately focused on addressing critical pathophysiologies affecting the world, and not on administrative overhead.
Chuck Hatt, Ph.D.
Dr. Hatt is a Director of Research and Senior Scientist at Imbio, as well as a Research Adjunct Professor in the Department of Radiology at the University of Michigan. His primary research interests are in the development and application of quantitative imaging biomarkers. He is the PI on multiple NIH grants related to quantitative image based analysis of cardiac and pulmonary diseases, and is also the primary machine learning architect of multiple imaging biomarker software applications at Imbio.
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