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SUMMARY:Harnessing Multimodal AI for Knowledge-Enhanced Computational Path
 ology - Prof Lequan Yu\, HKU\, Hong Kong SAR
DTSTART:20250430T120000Z
DTEND:20250430T133000Z
UID:TALK231400@talks.cam.ac.uk
CONTACT:125959
DESCRIPTION:Computational pathology has emerged as a transformative field\
 , leveraging artificial intelligence to analyze Whole Slide Images (WSIs) 
 and enhance diagnostic accuracy and efficiency. However\, traditional appr
 oaches often focus solely on learnable features from WSIs\, neglecting the
  critical role of clinical expertise and domain knowledge in interpreting 
 histopathologic entities. In this talk\, I will share our recent works in 
 addressing these limitations through the integration of multimodal AI and 
 knowledge-guided frameworks. I will highlight strategies for aligning huma
 n-like reasoning with computational methods to enhance diagnostic precisio
 n and interpretability. Additionally\, I will explore how expert knowledge
  can be utilized to dynamically adapt pathology foundation models to speci
 fic tasks\, improving feature representation and performance. These advanc
 ements illustrate the transformative potential of multimodal AI to develop
  precise\, interpretable\, and clinically impactful diagnostic tools\, set
 ting the stage for the next era of computational pathology.
LOCATION:Teams Meeting ID: 316 477 688 057 9 Passcode: cT3Gf6Sh
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