Imaging AI and Machine Learning -- Beyond the Hype, Upcoming Webinar Hosted by Xtalks
In this free webinar, experts from ICON Medical Imaging and Medidata will discuss how AI needs to have focus in specific areas, as past efforts to do everything have failed. The presenters will talk about narrowing down imaging problem statements to generate better results. How AI and ML can function as "guide rails" for radiologists will also be explored, in addition to areas in which AI and ML can increase (thus saving money) and improve quality (thus saving lives).
TORONTO, Nov. 30, 2020 /PRNewswire-PRWeb/ -- For the first 125 years of medical imaging, technological advances focused primarily on new modes of imaging as technology progressed from the discovery of the X-ray in 1895 to ultrasounds, MRIs, PET and CT scans in the late 20th century. Now, arguably, the most notable advances are being made in how images from those technologies are securely shared, managed, stored and assessed. These advancements are largely due to the application of artificial intelligence (AI) and machine learning (ML) to imaging systems and data platforms.
Automation is improving virtually every stage of the imaging workflow, but there is a lot of hype concerning AI and ML in the marketplace. Companies have underestimated the challenge that complexity presents, and predictions of the end of radiologists have proven false multiple times.
Join experts from ICON Medical Imaging and Medidata for this webinar on the practical applications for AI and ML in clinical trial imaging and what is possible today. Learn what is available today in the current landscape, its applications for building efficiency and what is coming in the near future to help life science companies transform their clinical trial imaging.
Join Paul McCracken, Vice President, Head of Medical Imaging, ICON Medical Imaging; and Dan Braga, VP, Product Management, Acorn AI Product & Ecosystem, Medidata, in a live webinar on Wednesday, December 16, 2020 at 11am EST (8am PST).
For more information, or to register for this event, visit Imaging AI and Machine Learning — Beyond the Hype.
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