Investigation of Disease from Multiple Health Care Data by Using HL7 Message on HDFS

M. Ramamoorthy
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Abstract

To furnish a detailed analysis on the healthcare data in HL7(Health Level 7) by utilizing Big data analytics and to create disease prediction system as the healthcare sector is considered as one of the important industries in information technology. In the past few years, healthcare data has become more complex with huge amount of data related to ever growing and changing technologies, mobile applications and discovery of new diseases. The belief of healthcare sectors is that healthcare data analytics tools are important to manage a large amount of complex data, to improve healthcare industries, efficiency and accuracy in medical practice. Information technology is a boon for the healthcare sectors to upgrade their efficiency in healthcare performance availing the provided data and information. The concept of big data though not new is constantly changing with attempts of defining big data and inventing newer hardware and software mechanisms to store, analyze and visualize the data in keeping with the requirements of collection of data elements as per the requisite size, speed and type. Velocity, variety and volume are the three innate aspects of the data produced. Furthermore, each of these data repositories is isolated and inherently incapable of providing a platform for global data transparency.
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利用HDFS上的HL7 Message对多个医疗数据进行疾病调查
利用大数据分析对HL7(Health Level 7)中的医疗数据进行详细分析,并创建疾病预测系统,因为医疗保健行业被认为是信息技术的重要行业之一。在过去的几年里,医疗数据变得越来越复杂,大量的数据与不断增长和变化的技术、移动应用程序和新疾病的发现有关。医疗保健行业的信念是,医疗保健数据分析工具对于管理大量复杂数据,提高医疗保健行业的效率和准确性非常重要。信息技术是医疗保健部门利用所提供的数据和信息提高其医疗保健绩效效率的福音。大数据的概念虽然并不新鲜,但也在不断变化,人们试图定义大数据,并发明更新的硬件和软件机制来存储、分析和可视化数据,以满足数据元素收集的要求,按照所需的大小、速度和类型。速度、种类和数量是所产生的数据的三个固有方面。此外,这些数据存储库中的每一个都是孤立的,本质上无法为全局数据透明提供平台。
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