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METHOD:PUBLISH
BEGIN:VEVENT
DTSTAMP:20260608T213635Z
DTSTART:20260615T130000Z
DTEND:20260615T140000Z
SUMMARY:Ke Yuan -- Mapping the landscape of histomorphological cancer phe
 notypes with self-supervised learning [IN PERSON]
UID:{http://www.columbasystems.com/customers/uom/gpp/eventid/}d1q8-mm3dqt
 wb-yobra1
DESCRIPTION:Join us for this seminar by Ke Yuan (Glasgow) as part of the 
 Maths in the Life Sciences seminar series (and the online North West Sem
 inar Series in Mathematical Biology and Data Sciences in collaboration w
 ith Liverpool Universities). \n\nTitle: Mapping the landscape of histomo
 rphological cancer phenotypes with self-supervised learning\n\nAbstract:
 \nSelf-supervised representation learning is transforming computational 
 pathology\, enabling powerful predictive models for cancer diagnosis\, p
 rognosis\, and treatment response. We leverage this technology to system
 atically map recurrent and rare histomorphological patterns directly fro
 m unannotated pathology slides. Across multiple cancer types\, we found 
 previously underappreciated histological features strongly correlated wi
 th patient outcomes and molecular data. The patterns define a quantitati
 ve landscape of cancer phenotypes\, facilitating novel hypothesis genera
 tion and deeper biological understanding. This work demonstrates the pow
 er of self-supervised AI to unlock clinically relevant insights and disc
 overies from routinely collected pathology data.\n\nBio:\nKe Yuan is a R
 eader in Machine Learning and Computational Biology at the School of Can
 cer Sciences\, University of Glasgow and a Group Leader at the Cancer Re
 search UK Scotland Institute. Previously\, he served as a Lecturer and t
 hen Senior Lecturer at the School of Computing Science\, also at the Uni
 versity of Glasgow. He received his PhD from the University of Southampt
 on in 2013 under the supervision of Mahesan Niranjan. Until April 2016\,
  he worked as a postdoctoral research fellow at the Cancer Research UK C
 ambridge Institute at the University of Cambridge\, working with Florian
  Markowetz. His research focuses on developing novel machine learning an
 d AI methods for genomic and image data to advance our understanding of 
 cancer and virus evolution.\n\nThe talk will be also be streamed via Tea
 ms\, please contact carl.whitfield@manchester.ac.uk or igor.chernyavsky@
 manchester.ac.uk for the link\, or sign up to the mailing list.\n\nTo su
 bscribe to the mailing list for this event series\, please send an e-mai
 l with the phrase “subscribe math-lifesci-seminar” in the message body t
 o listserv@listserv.manchester.ac.uk
STATUS:TENTATIVE
TRANSP:TRANSPARENT
CLASS:PUBLIC
LOCATION:4.04\, Simon Building\, Manchester
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