Current validation practice undermines surgical AI development
This research identifies common mistakes in validating AI used for analyzing surgical videos. Drawing from 92 experts, it created a structured list of pitfalls across data, metrics, and reporting. The findings show that ignoring the temporal and hierarchical structure of surgical video leads to misleading results. The paper provides best practices to ensure rigorous, clinically relevant validation for surgical AI systems.