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Hadoop-based Implementation of Processing Medical Diagnostic Records for Visual Patient System

机译：基于Hadoop的视觉病人系统医疗诊断记录处理实现

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We have innovatively introduced Visual Patient (VP) concept and method visually to represent and index patient imaging diagnostic records (IDR) in last year SPIE Medical Imaging (SPIE MI 2017), which can enable a doctor to review a large amount of IDR of a patient in a limited appointed time slot. In this presentation, we presented a new approach to design data processing architecture of VP system (VPS) to acquire, process and store various kinds of IDR to build VP instance for each patient in hospital environment based on Hadoop distributed processing structure. We designed this system architecture called Medical Information Processing System (MIPS) with a combination of Hadoop batch processing architecture and Storm stream processing architecture. The MIPS implemented parallel processing of various kinds of clinical data with high efficiency, which come from disparate hospital information system such as PACS, RIS LIS and HIS.
机译：我们在去年SPIE Medical Imaging（SPIE MI 2017）上创新性地引入了可视患者（VP）概念和方法，以可视化方式表示和索引患者成像诊断记录（IDR），这可以使医生检查大量的IDR。病人在有限的指定时间段内。在本演示中，我们提出了一种新的方法来设计VP系统（VPS）的数据处理体系结构，以获取，处理和存储各种IDR，以基于Hadoop分布式处理结构为医院环境中的每个患者构建VP实例。我们将Hadoop批处理架构和Storm流处理架构相结合，设计了一种称为医疗信息处理系统（MIPS）的系统架构。 MIPS高效地并行处理各种临床数据，这些数据来自不同的医院信息系统，例如PACS，RIS LIS和HIS。

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