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Performance Improvement (Pi) score: an algorithm to score Pi objectively during E-BLUS hands-on training sessions. A European Association of Urology, Section of Uro-Technology (ESUT) project.

Domenico VenezianoAntonio CanovaMichiel ArnoldsJohn D BeattyShekhar Chandra BiyaniFederico DehòCristian FioriGiles O HellawellJ F LangenhuijsenGiovannalberto PiniÓscar Rodríguez FabaGiampaolo SienaAndreas SkolarikosTheodoros TokasBen S E P Van CleynenbreugelChristian WagnerGiovanni TripepiBhaskar SomaniBhaskar Lima
Published in: BJU international (2018)
The present study shows that evaluation of Pi is highly variable, even when formulated by a cohort of experts. Our algorithm successfully provided an objective score that was equal to the average Pi assessment of a cohort of experts, in relation to a small amount of training attempts.
Keyphrases
  • machine learning
  • deep learning
  • physical activity
  • virtual reality
  • quality improvement
  • neural network
  • urinary tract