Machine learning in the optimization of robotics in the operative field.

Journal: Current opinion in urology
Published Date: Nov 1, 2020

Abstract

PURPOSE OF REVIEW: The increasing use of robotics in urologic surgery facilitates collection of 'big data'. Machine learning enables computers to infer patterns from large datasets. This review aims to highlight recent findings and applications of machine learning in robotic-assisted urologic surgery.

Authors

  • Runzhuo Ma
    Center for Robotic Simulation & Education, Catherine & Joseph Aresty Department of Urology, USC Institute of Urology, University of Southern California, Los Angeles, California, USA.
  • Erik B Vanstrum
    3Department of Head and Neck Surgery, David Geffen School of Medicine at the University of California, Los Angeles.
  • Ryan Lee
  • Jian Chen
    School of Pharmacy, Shanghai Jiaotong University, Shanghai, China.
  • Andrew J Hung
    Center for Robotic Simulation & Education, Catherine & Joseph Aresty Department of Urology, University of Southern California Institute of Urology, Los Angeles, California. Electronic address: Andrew.Hung@med.usc.edu.

Keywords

External Resources

Popular Topics
Recent Journals