From Data to Decision: A Comprehensive Review of Real-Time Analytics and Smart Technologies in the Surgical Suite

从数据到决策:手术室实时分析和智能技术的全面综述

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Abstract

Advancements in intraoperative data acquisition and analytics are transforming surgical care by integrating diverse information streams into cohesive, real-time decision-support systems. This review explores the use of physiological monitoring, medical imaging, instrument motion data, surgical video, and environmental metrics within next-generation operating rooms. Traditional vital sign monitoring is now augmented by wearable and minimally invasive technologies capable of continuously capturing respiratory rate, heart rate, skin temperature, and hemodynamic parameters such as stroke volume, cardiac output, systemic vascular resistance, and mean arterial pressure. Real-time imaging modalities including intraoperative cone-beam computed tomography, 3-dimensional fluoroscopy with image fusion, ultrasound, and Doppler systems provide dynamic anatomical context to guide precision interventions. Concurrently, computer vision and artificial intelligence tools are being applied to surgical video and kinematic data to identify procedural phases, assess performance, and recognize critical events. Predictive analytics models, trained on large procedural datasets, can anticipate adverse outcomes like excessive blood loss or prolonged operative time, enhancing intraoperative awareness. Smart operating room platforms integrate these multimodal data sources into centralized interfaces, enabling synchronized documentation, workflow coordination, and team communication. Moreover, emerging concepts such as patient-specific surgical simulation and digital twin models offer personalized guidance and outcome forecasting. Despite these advances, challenges remain in managing data overload, achieving system interoperability, ensuring regulatory compliance, and safeguarding privacy.

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