Big data technologies have proliferated since the dawn of the cloud-computing era. Traditional data storage, extraction, transformation, and analysis technologies have thus become unsuitable for the large volume, diversity, high processing speed, and low value density of big data in medical strategies, which require the development of novel big data application technologies. In this regard, we investigated the most recent big data platform breakthroughs in anesthesiology and designed an anesthesia decision model based on a cloud system for storing and analyzing massive amounts of data from anesthetic records. The presented Anesthesia Decision Analysis Platform performs distributed computing on medical records via several programming tools, and provides services such as keyword search, data filtering, and basic statistics to reduce inaccurate and subjective judgments by decision-makers. Importantly, it can potentially to improve anesthetic strategy and create individualized anesthesia decisions, lowering the likelihood of perioperative complications.

中文翻译：

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使用基于云的大数据平台进行麻醉决策分析

自云计算时代到来以来，大数据技术不断激增。传统的数据存储、提取、转换和分析技术已经不适合医疗策略中大数据的大数据量、多样性、高处理速度和低价值密度，这需要开发新颖的大数据应用技术。为此，我们研究了麻醉学大数据平台的最新突破，并设计了基于云系统的麻醉决策模型，用于存储和分析来自麻醉记录的大量数据。麻醉决策分析平台通过多种编程工具对病历进行分布式计算，并提供关键词搜索、数据过滤、基础统计等服务，减少决策者的不准确和主观判断。重要的是，它有可能改善麻醉策略并制定个体化麻醉决策，从而降低围手术期并发症的可能性。