Imaging AI and Machine Learning – Beyond the Hype

Life Sciences, Healthcare, Laboratory Technology, Digital Health,
  • Wednesday, December 16, 2020

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.

Speakers

Paul McCracken, ICON Medical Imaging

Paul McCracken, Vice President, Head of Medical Imaging, ICON Medical Imaging

Dr. Paul McCracken is the Vice President, Global Head of ICON Medical Imaging, and North Wales Site Head at ICON Plc. McCracken has over 20 years’ experience in imaging and pharmaceuticals, with a strong track record of applying imaging and biomarkers to drug discovery and development across a range of therapeutic areas. He joined ICON in 2016 having previously founded and led the Imaging Centre of Excellence at Eisai Co. Prior to Eisai, he worked at Merck Research Laboratories, where he developed preclinical and translational imaging biomarkers and strategies to assess new molecular and biologic entities. McCracken holds a Bachelor of Science in Physics from The College of New Jersey, a Master of Science in Physics/Medical Physics from Wright State University and received his Ph.D. in Biomedical Engineering – Imaging from the Mayo Clinic College of Medicine.

Message Presenter
Dan Braga, Medidata, a Dassault Systèmes company

Dan Braga, VP, Product Management, Acorn AI Product & Ecosystem, Medidata, a Dassault Systèmes company

Dan Braga is the VP of Product Management for medical imaging solutions at Medidata Solutions. Dan works with sponsors, CROs, core labs, and sites to adopt medical image technologies to help automate image acquisition, distribution, assessment, and data collection. Prior to Medidata, Dan was one of the co-founders of Intelemage, a medical image management and workflow company later acquired by Medidata. Prior to Intelemage, Dan worked in various product management, operational and sales roles with healthcare technology companies such as GE Healthcare, PocketScript, and WebMD.

Message Presenter

Who Should Attend?

  • Clinical Operations
  • Procurement
  • Imaging
  • Executive Management
  • Therapeutic Area Heads
  • Professionals in the Radiology Field

What You Will Learn

In this webinar, participants will learn:

  • How AI needs to be focusing in specific areas, as past efforts to do everything have failed
  • How to narrow down imaging problem statements that will generate better results
  • How AI and ML can function as “guide rails” for radiologists
  • Areas that AI and ML can increase efficiency (thus saving money) and improve quality (thus saving lives)

Xtalks Partner

Medidata, a Dassault Systèmes company

Medidata, a Dassault Systèmes company, is leading the digital transformation of life sciences, creating hope for millions of patients by helping to generate the evidence and insights to help pharmaceutical, biotech, medical device and diagnostics companies, and academic researchers accelerate value, minimize risk, and optimize outcomes.

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