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DESCRIPTION:This presentation outlines the rising global burden of cancer a
 nd the increasing strain on pathology services due to manual workflows and
  a worldwide shortage of expert pathologists. It introduces Digital Pathol
 ogy as a transformative solution that uses whole-slide imaging\, telepatho
 logy\, and integrated digital workflows to improve diagnostic efficiency\,
  accuracy\, and accessibility. The presentation highlights the capabilitie
 s of modern scanners\, the advantages of digitized slides\, and the result
 ing improvements in collaboration\, automation\, and data management.\n\nI
 t further describes how Artificial Intelligence (AI) enhances cancer diagn
 osis through automated tumor detection\, grading\, cell counting\, and pre
 dictive modeling for precision medicine. The presentation also reviews ind
 ustry investment trends and explores future opportunities created by combi
 ning digital slides with clinical\, genomic\, and treatment data for resea
 rch\, clinical trials\, and data-driven insights. Finally\, it identifies 
 significant opportunities to build AI-driven diagnostics\, drug discovery\
 , and advance cancer research\n\nSpeaker(s): Mr. Singhal\n\nVirtual: https
 ://events.vtools.ieee.org/m/543670
LOCATION:Virtual: https://events.vtools.ieee.org/m/543670
ORGANIZER:hsingh@eng.wayne.edu
SEQUENCE:21
SUMMARY:Invited talk on Digital Pathology & AI
URL;VALUE=URI:https://events.vtools.ieee.org/m/543670
X-ALT-DESC:Description: <br /><p>This presentation outlines the rising glob
 al burden of cancer and the increasing strain on pathology services due to
  manual workflows and a worldwide shortage of expert pathologists. It intr
 oduces Digital Pathology as a transformative solution that uses whole-slid
 e imaging\, telepathology\, and integrated digital workflows to improve di
 agnostic efficiency\, accuracy\, and accessibility. The presentation highl
 ights the capabilities of modern scanners\, the advantages of digitized sl
 ides\, and the resulting improvements in collaboration\, automation\, and 
 data management.</p>\n<p>It further describes how Artificial Intelligence 
 (AI) enhances cancer diagnosis through automated tumor detection\, grading
 \, cell counting\, and predictive modeling for precision medicine. The pre
 sentation also reviews industry investment trends and explores future oppo
 rtunities created by combining digital slides with clinical\, genomic\, an
 d treatment data for research\, clinical trials\, and data-driven insights
 . Finally\, it identifies significant opportunities to build AI-driven dia
 gnostics\, drug discovery\, and advance cancer research</p>
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