AI in Surgery

Performance Analytics & Feedback

Measure What Matters. Improve What’s Measured.

Traditional apprenticeship models are having a hard time keeping pace with modern surgical complexity. AI-powered performance platforms will be able to convert every hand movement, pupillary response, and thought process into actionable intelligence:

Objective Metrics, Unlocked - Embedded sensors will track instrument trajectory, force, speed, precision, visual focus, and even EEG-based cognitive load will transform subjective evaluation into a 360-degree skills profile.
Instant, Adaptive Feedback - Machine-learning models will compare trainee performance against thousands of expert benchmarks, highlighting inefficiencies in real time and prescribing micro-drills that speed skill acquisition.
Longitudinal Benchmarking - Progress dashboards will chart improvement across a continuum of training and spotlight areas of rapid growth and plateau points so mentors can intervene appropriately.
Scenario-Based Mastery - High-fidelity VR/AR cases will recreate rare complications and crisis scenarios, conditioning surgeons to perform decisively under pressure.

Dive deeper

Consensus on Metrics: Read the outcomes of ISE’s two AI & Surgical Metrics Consensus Conferences—the field’s first road map for objective skill measurement.
Research in Action: The Collaborative for Advanced Assessment of Robotic Surgical Skills (CAARSS) is validating these metrics across specialties. Join the research cohort or explore preliminary findings.