Deep Neural Networks for the Assessment of Surgical Skills: A Systematic Review

@article{Yanik2021DeepNN,
  title={Deep Neural Networks for the Assessment of Surgical Skills: A Systematic Review},
  author={Erim Yanik and Xavier Intes and Uwe Kruger and Pingkun Yan and David Miller and Brian Van Voorst and Basiel Makled and Jack Norfleet and Suvranu De},
  journal={ArXiv},
  year={2021},
  volume={abs/2103.05113}
}
Surgical training in medical school residency programs has followed the apprenticeship model. The learning and assessment process is inherently subjective and time-consuming. Thus, there is a need for objective methods to assess surgical skills. Here, we use the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines to systematically survey the literature on the use of Deep Neural Networks for automated and objective surgical skill assessment, with a focus on… Expand
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