Support vector machines improve the accuracy of evaluation for the performance of laparoscopic training tasks

@article{Allen2009SupportVM,
  title={Support vector machines improve the accuracy of evaluation for the performance of laparoscopic training tasks},
  author={B. Allen and Vasile Nistor and Erik Dutson and Greg P. Carman and C. Lewis and Petros Faloutsos},
  journal={Surgical Endoscopy},
  year={2009},
  volume={24},
  pages={170-178}
}
Despite technological advances in the tracking of surgical motions, automatic evaluation of laparoscopic skills remains remote. A new method is proposed that combines multiple discrete motion analysis metrics. This new method is compared with previously proposed metric combination methods and shown to provide greater ability for classifying novice and expert surgeons. For this study, 30 participants (four experts and 26 novices) performed 696 trials of three training tasks: peg transfer, pass… CONTINUE READING

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