Toward the intelligent operating room: Artificial intelligence and computer vision applications in surgery

The operating room is evolving into an information-rich environment where surgical care is increasingly shaped by integrated digital architectures. The proliferation of minimally invasive and robotic platforms has generated a massive influx of high-resolution video, shifting the field toward real-time computational analysis. Artificial intelligence, particularly computer vision, is moving beyond retrospective analysis to extract structured intelligence from the operative field, redefining how procedures are analyzed and supported. This review focuses on the clinical applications of computer vision with the greatest translational relevance: Computer-aided detection, instrument tracking, procedural phase recognition, and video-based skill assessment. However, clinical translation remains constrained by practice variability, a lack of standardized open datasets, ethical and regulatory considerations, and the difficulty of ensuring model generalizability across diverse institutions. This review examines the current evidence for computer-aided detection, instrument tracking, phase recognition, and video-based skill assessment in surgery, and discusses their clinical readiness and key limitations.