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DESCRIPTION:In this talk\, Beverly Freeman\, Google user experience researc
 her\, explores the challenges of collecting high-quality training data fro
 m medical experts for the development of artificial intelligence solutions
  for disease detection. Drawing from interviews with AI practitioners and 
 domain experts in ophthalmology\, radiology\, pathology\, and dermatology\
 , this talk describes the collaborative and iterative strategies that help
  teams identify and address issues before they proliferate. The key lesson
  learned in this research is "An ounce of prevention is worth a pound of c
 ure."\n\nSpeaker(s): Beverly Freeman\, \n\nVirtual: https://events.vtools.
 ieee.org/m/310017
LOCATION:Virtual: https://events.vtools.ieee.org/m/310017
ORGANIZER:genef@ieee.org
SEQUENCE:9
SUMMARY: AI- Iterative Quality Control Strategies for Expert Medical Image 
 Labeling (Google Health)
URL;VALUE=URI:https://events.vtools.ieee.org/m/310017
X-ALT-DESC:Description: <br /><p>In this talk\,&nbsp\; Beverly Freeman\, Go
 ogle user experience researcher\,&nbsp\; explores the challenges of collec
 ting high-quality training data from medical experts for the development o
 f artificial intelligence solutions for disease detection. Drawing from in
 terviews with AI practitioners and domain experts in ophthalmology\, radio
 logy\, pathology\, and dermatology\, this talk describes the collaborative
  and iterative strategies that help teams identify and address issues befo
 re they proliferate. The key lesson learned in this research is "An ounce 
 of prevention is worth a pound of cure."&nbsp\;</p>
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