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Artificial intelligence in laparoscopic simulation: a promising future for large-scale automated evaluations.

Francisca Belmar1, María Inés Gaete1, Gabriel Escalona1

  • 1Experimental Surgery and Simulation Center, Department of Digestive Surgery, Catholic University of Chile, Santiago, Chile.

Surgical Endoscopy
|October 3, 2022
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Summary

Artificial intelligence (AI) shows strong agreement with expert evaluators for assessing basic laparoscopic simulation training. This AI algorithm offers a scalable solution for surgical skills assessment, overcoming limitations in expert availability.

Keywords:
Artificial intelligenceLaparoscopySurgical simulation

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Area of Science:

  • Surgical Education
  • Medical Simulation
  • Artificial Intelligence in Medicine

Background:

  • Laparoscopic simulation training programs face limitations due to a scarcity of expert evaluators.
  • A digital platform for remote laparoscopic training has been validated, collecting extensive video data.
  • Artificial intelligence (AI) is emerging as a tool for surgical simulation assessment.

Purpose of the Study:

  • To analyze the agreement between an AI algorithm and expert evaluators in assessing basic laparoscopic simulation training exercises.
  • To evaluate the potential of AI in overcoming expert evaluator limitations in surgical training.

Main Methods:

  • An AI algorithm was developed and trained on videos of bean drop (BD) and peg transfer (PT) exercises.
  • The AI's performance was tested against expert evaluations using Cohen's Kappa test.
  • Agreement was assessed using a pass/fail nomenclature based on exercise completion time.

Main Results:

  • The AI algorithm achieved 79.69% agreement for BD exercises and 93.02% for PT exercises.
  • Cohen's Kappa coefficients indicated moderate agreement (0.59) for BD and almost perfect agreement (0.86) for PT.
  • The AI demonstrated capability in detecting object movement, dropped objects, grasper location, and timing.

Conclusions:

  • The AI algorithm shows promising results for assessing basic laparoscopic simulation skills.
  • This study provides a framework for expanding AI applications in surgical skills training.
  • AI offers a scalable and objective method to supplement expert evaluation in surgical simulation.