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VERSION:2.0
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CALSCALE:GREGORIAN
X-WR-CALNAME:Artificial intelligence for medical image analysis: our approa
 ches 
X-WR-TIMEZONE:Eastern Time (US & Canada)
BEGIN:VEVENT
DTSTAMP:20261015T020747Z
UID:tag:localist.com\,2008:EventInstance_35891003287230
DTSTART:20210212T200000Z
DTEND:20210212T210000Z
DESCRIPTION:Chemistry Seminar Series\nDr.  Weihua Zhou\,  Assistant Profess
 or\, College of Computing\nMichigan Technological University\n\nAbstract:\
 nMachine learning (ML) has shown great advantages to overcome the challeng
 es of high-dimensional complexity and inter-correlation among clinical pre
 dictors and help physicians make patient-specific clinical decisions relat
 ed to diagnosis and treatment. Deep learning as a type of more complicated
  ML methods has been extensively used to extract information from medical 
 records and images\, and predict outcomes with a very high accuracy. Convo
 lutional neural networks (CNN) are state-of-the-art deep learning techniqu
 es for computer vision\, such as medical image segmentation and classifica
 tion. This research talk will introduce our approaches of applying these a
 rtificial intelligence (AI) techniques to medical image analysis\, particu
 larly on image segmentation. We will also give an example about building a
  clinically accurate and practical AI-based software toolkit to improve pe
 rcutaneous coronary intervention (PCI) for the treatment of patients with 
 coronary artery disease. \n\nBio:\nDr. Weihua Zhou\, is an Assistant Profe
 ssor of Applied Computing at Michigan Tech. He has been doing research on 
 medical imaging and informatics since 2008. Prior to joining Michigan Tech
 \, he was a post-doctoral fellow at Emory University School of Medicine fr
 om 2012 to 2015 and was an Assistant Professor of Computer Science at The 
 University of Southern Mississippi from 2015 to 2019. Dr. Zhou’s researc
 h is driven by clinical significance. His research record includes more th
 an 70 publications\, 1 active patent\, and 7 invention disclosures. His so
 ftware applications are being used by 3 clinical trials and more than 30 h
 ospitals.
LOCATION:
SUMMARY:Artificial intelligence for medical image analysis: our approaches 
URL;VALUE=URI:https://events.mtu.edu/event/artificial_intelligence_for_medi
 cal_image_analysis_our_approaches
CATEGORIES:Academics
CATEGORIES:Lectures/Seminars
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