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Proposal of a Big Data Platform for Intelligent Antibiotic Surveillance in a Hospital

机译:医院中智能抗生素监测大数据平台的建议

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From a technological point of view two kinds of requirements must be taken into account when implementing Clinical Decision Support Systems (CDSSs) for antibiotic surveillance in a hospital. First, Artificial Intelligence (AI) technologies are usually applied to represent and reason about existing clinical knowledge, but also to discover new one from raw data. Second, at a global decision level, representative applications of Business Intelligence (BI) must be also considered. The present work introduces the design and implementation of a CDSS platform that integrates both AI and BI technologies to assist clinicians in the rational use of antibiotics in a hospital. The choice of a Hadoop based Big Data architecture provides a suitable solution for the problem of integrating, processing and analysing large sets of clinical data. The platform facilitates the daily follow-up of antibiotic therapies and infections while offering various decision support modules at both patient and global level. The system is being tested and evaluated in a university hospital.
机译:从技术角度来看,在医院中实施用于抗生素监测的临床决策支持系统(CDSS)时,必须考虑两种要求。首先,人工智能(AI)技术通常用于表示和推理现有的临床知识,而且还可以从原始数据中发现新的知识。其次,在全球决策层面,还必须考虑商业智能(BI)的代表性应用。本工作介绍了CDSS平台的设计和实现,该平台集成了AI和BI技术,可帮助临床医生在医院中合理使用抗生素。基于Hadoop的大数据架构的选择为集成,处理和分析大量临床数据的问题提供了合适的解决方案。该平台促进了抗生素治疗和感染的日常随访,同时在患者和全球范围内提供了各种决策支持模块。该系统正在大学医院中进行测试和评估。

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