A real-time spatiotemporal AI model analyzes skill in open surgical videos

TL;DR

This paper introduces a large-scale, real-time AI model trained on YouTube videos to analyze and assess skill in open surgical procedures across diverse environments.

Contribution

It creates the largest open surgical video dataset and develops a generalizable AI model for real-time surgical behavior and skill analysis.

Findings

Model generalizes across surgery types and environments

Identifies kinematic descriptors related to surgical skill

Demonstrates real-time analysis capability

Abstract

Open procedures represent the dominant form of surgery worldwide. Artificial intelligence (AI) has the potential to optimize surgical practice and improve patient outcomes, but efforts have focused primarily on minimally invasive techniques. Our work overcomes existing data limitations for training AI models by curating, from YouTube, the largest dataset of open surgical videos to date: 1997 videos from 23 surgical procedures uploaded from 50 countries. Using this dataset, we developed a multi-task AI model capable of real-time understanding of surgical behaviors, hands, and tools - the building blocks of procedural flow and surgeon skill. We show that our model generalizes across diverse surgery types and environments. Illustrating this generalizability, we directly applied our YouTube-trained model to analyze open surgeries prospectively collected at an academic medical center and identified kinematic descriptors of surgical skill related to efficiency of hand motion. Our Annotated Videos of Open Surgery (AVOS) dataset and trained model will be made available for further development of surgical AI.