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An end-to-end pipeline that captures motion in the operating room and uses it to train a surgical robot policy, validated on live animals, and shows that demonstrations recorded from a surgeon's own instruments are sufficient to train, select and deploy a bimanual surgical policy in vivo.
Despite advances in AI-driven surgical skill assessment, reliably tracking hands and tools in open surgery videos remains a surprisingly difficult problem, hindering motion-based analysis.
