Computer vision in laparoscopic gastrointestinal surgery: A review of anatomical recognition and clinical navigation

Table 2 Major challenges to clinical translation of computer vision in gastrointestinal surgery and potential solutions

Challenge	Clinical impact	Potential solution	Validation priority
Single-center datasets	Poor generalizability	Multicenter standardized datasets	External validation
Domain shift	Performance degradation	Domain adaptation/federated learning	Cross-center testing
Soft-tissue deformation	Registration failure	Deformable registration and uncertainty estimation	Real-time validation
Latency	Delayed guidance	Edge computing	OR deployment
Privacy	Limits data sharing	Federated/privacy-preserving AI	Governance validation
Automation bias	Unsafe reliance	Human-in-the-loop design	Human-factors studies
Regulatory/liability uncertainty	Deployment barriers	Defined approval/accountability frameworks	Prospective implementation
Lack of clinical evidence	Uncertain patient benefit	Multicenter prospective trials/RCTs	Clinical effectiveness

AI: Artificial intelligence; OR: Operating room; RCTs: Randomized controlled trials.