METHODS OF APPLYING ARTIFICIAL INTELLIGENCE IN SURGICAL DIAGNOSTICS
Keywords:
artificial intelligence, surgical diagnostics, machine learning, deep learning, convolutional neural networks, computer vision, preoperative assessment, intraoperative guidance, postoperative outcomes, clinical decision support.Abstract
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.
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