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SUMMARY:AI applications in radiological image analysis for cancer research
   - Lorena Escudero
DTSTART:20221027T120000Z
DTEND:20221027T133000Z
UID:TALK183710@talks.cam.ac.uk
CONTACT:James Fergusson
DESCRIPTION:Imaging is one of the main pillars of clinical protocols for c
 ancer care that provides essential non-invasive biomarkers for detection\,
  diagnosis and response assessment. The development of Artificial Intellig
 ence (AI) tools have proven potential to transform the analysis of radiolo
 gical images\, by significantly reducing processing time\, by increasing t
 he reproducibility of measurements and by improving the sensitivity of tum
 our detection compared to the standard visual interpretation\, leading to 
 cancer early detection. \n\nDr Lorena Escudero Sanchez is a particle physi
 cist\, with a PhD in neutrino physics\, who has worked in large internatio
 nal collaborations for the neutrino oscillation experiments T2K\, MicroBoo
 NE and DUNE. She now works on AI applications to radiological image analys
 is for cancer research\, at the Department of Radiology of the University 
 of Cambridge and CRUK Cambridge Centre. She is also a Turing Fellow of The
  Alan Turing Instittue and a Borysiewicz Interdisciplinary Fellow. 
LOCATION:Kavli Large Meeting Room\, Kavli Building
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