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Jigsaws soup: Improved laparoscopic surgical gesture classification, and skill level evaluation using model souping.

Kade MacWilliams1, Ahmed Nasr2, Georges Azzie3

  • 1Department of Systems and Computer Engineering, Carleton University, Ottawa, ON, Canada.

Computers in Biology and Medicine
|March 17, 2026
PubMed
Summary

An AI coach using model soup improves laparoscopic surgery training by accurately recognizing surgical gestures and assessing performance. This AI aims to make quality surgical education more accessible, especially where expert coaches are scarce.

Keywords:
Deep learningGesture recognitionModel soupSkill assessmentSurgical training

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Area of Science:

  • Medical Simulation
  • Artificial Intelligence in Surgery
  • Machine Learning for Skill Assessment

Background:

  • Laparoscopic surgery offers patient benefits but requires extensive, simulation-based training.
  • A global shortage of expert surgical coaches limits training accessibility.
  • Artificial Intelligence (AI) can provide automated feedback to enhance surgical training.

Purpose of the Study:

  • To improve AI-driven surgical training by enhancing gesture recognition and performance assessment.
  • To apply the 'model soup' machine learning approach to kinematic and video data from surgical simulations.
  • To develop a more accessible and effective AI coach for laparoscopic surgery.

Main Methods:

  • Utilized 'model soup,' an ensemble machine learning technique, to combine multiple models.
  • Applied model soup to kinematic simulator data for gesture recognition and performance scoring.
  • Applied model soup to video data for improved surgical gesture recognition.

Main Results:

  • Achieved performance improvements of 2.84-7.25 percentage points across three surgical tasks.
  • Outperformed state-of-the-art methods in gesture recognition and surgical score regression.
  • Demonstrated enhanced accuracy in classifying surgical movements from both kinematic and video data.

Conclusions:

  • The model soup approach significantly improves AI performance in surgical skill assessment.
  • This advancement moves closer to a fully autonomous AI laparoscopic surgery coach.
  • Enhanced AI coaching can increase the availability of quality surgical training globally.