Integration of AI in surgical decision support: improving clinical judgment

Though early in its development, artificial Intelligence (AI)-enabled clinical decision support (CDS) systems show promise in improving surgical decision-making. Applications for AI have been proposed in all surgical specialties and cover pre-operative risk assessment tools, intra-operative monitoring and decision-making, and post-operative patient management. These AI systems find patterns in data, with sources ranging from radiology, pathology, and intra-operative images to the human genome and real-time physiological parameters. They may improve hospital workflow through information extraction, documentation, and summarization. However, these new tools require validation in real-world clinical settings, adherence to standardized reporting guidelines, and a comprehensive evaluation of both performance and fairness metrics. In overcoming these limitations, AI is poised to offer data-driven insights to enhancing patient care.