METHODS OF APPLYING ARTIFICIAL INTELLIGENCE IN SURGICAL DIAGNOSTICS

The integration of artificial intelligence  into surgical diagnostics represents one of the most transformative developments in contemporary medicine. Over the past decade, machine learning, deep learning, and computer vision technologies have progressively permeated virtually every domain of surgical practice - from preoperative imaging interpretation and risk stratification to intraoperative decision support and postoperative outcome prediction. This comprehensive review synthesizes current evidence on the role of AI in surgical diagnostics, examining its theoretical foundations, clinical applications across multiple surgical specialties, diagnostic accuracy metrics, and inherent limitations.