Integration of spatiotemporal features into machine learning assessment of open surgical skills

Key Points

• Machine learning methods significantly enhance the assessment of open surgical skills through detailed analysis of spatiotemporal features.
• The assessment resulted in improved metrics for skill evaluation, with notable performance increases observed in classification accuracy and precision.
• Observational analysis implemented advanced algorithms to correlate skill assessments with identified spatiotemporal features.
• These findings may enable enhanced training programs and more precise evaluations in surgical education and practice.