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SUMMARY:Artificial intelligence for prediction of genetic alterations dire
 ctly from histology images - Prof Jakob Kather is a physician/scientist an
 d assistant professor at RWTH Aachen University (Germany) with additional 
 affiliations at the NCT Heidelberg (Germany) and the University of Leeds (
 UK). 
DTSTART:20211004T083000Z
DTEND:20211004T093000Z
UID:TALK161974@talks.cam.ac.uk
CONTACT:Tania Smith
DESCRIPTION:Precision oncology requires molecular and genetic testing of t
 umor tissue. For many tests\, universal implementation in clinical practic
 e is limited because these biomarkers are costly\, require significant exp
 ertise and are limited by tissue availability. However\, virtually every c
 ancer patient gets a biopsy as part of the diagnostic workup and this tiss
 ue is routinely stained with hematoxylin and eosin (H&E). Recently\, we an
 d others have demonstrated that deep learning can infer tumor genotype\, p
 rognosis and treatment response directly from routine H&E histology images
 . This talk will summarize the state of the art of deep learning in oncolo
 gy\, demonstrate emerging use cases and discuss the clinical implications 
 of these novel biomarkers. 
LOCATION:ZOOM (live)
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