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.

人工智能（Artificial Intelligence）融入外科诊断，是当代医学领域最具变革性的进展之一。近十年来，机器学习（Machine Learning）、深度学习（Deep Learning）与计算机视觉（Computer Vision）技术已逐步渗透至外科临床实践的几乎所有范畴——从术前影像解读、风险分层，到术中决策支持与术后预后预测。本综述全面整合了人工智能在外科诊断领域的现有研究证据，系统剖析了其理论基础、多外科专科的临床应用场景、诊断准确性评估指标及固有局限性。