大数据对医疗保健的影响:一项调查

D. Thara, B. Premasudha, V. Ram, R. Suma
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引用次数: 15

摘要

随着互联网世界中产生的数据量日益增加,“大数据”一词正在成为当今市场上非常流行的流行语。大数据应用于互联网世界的各个领域。在本文中,我们试图证明,即使是医疗保健行业也正在进入大数据池,从各种先进的工具和技术中获益。本文介绍了使用大数据概念和方法在医疗保健领域所做的各种研究工作的回顾。大数据的思想可以用于更好的健康规划。其方法可用于医疗保健数据分析,这有助于更好地制定决策,以增加业务价值和客户兴趣,并通过使用诸如Health Level?医学中的数字成像和通信(DICOM)、健康保险可移植性和责任(HIPAA)、消息代理等。大数据技术可用于开发疾病早期诊断系统,了解HATS(艾滋病毒/艾滋病结核病和矽肺病)之间的联系,以及开发集成数据分析平台。在介绍了大数据在医疗保健方面的许多积极进展之后,本文也介绍了医疗保健系统在使用大数据技术时面临的障碍。此外,本文还包括各种大数据工具的列表,一些案例研究,一些值得在医疗保健中使用大数据的应用程序,然后是结束语。
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Impact of big data in healthcare: A survey
As the volume of data generating is increasing day by day in this internet world, the term Big Data is becoming a very popular buzzword in today's market. Big Data is used in various sectors of the internet world. In this paper an effort is made to demonstrate that even the healthcare industries are stepping into Big Data pool to take all benefits from its various advanced tools and technologies. The paper presents the review of various research efforts made in healthcare domain using Big Data concepts and methodologies. The thought of Big Data can be used for better health planning. Its methodologies can be used for healthcare data analytics which helps in better decision making to increase the business value and customer interest and to provide eHealth services among various healthcare stakeholders by using messaging standards like Health Level?, Digital Imaging and Communications in Medicine (DICOM), Health Insurance Portability and Accountability (HIPAA), message broker etc. Big Data techniques can be applied to develop systems for the early diagnosis of disease, understand connection between HATS (HIV/AIDS Tuberculosis and Silicosis) and also to develop integrated data analytics platforms. After presenting these many positive progresses of Big Data on healthcare, the paper also presents the hurdles faced by healthcare systems in using Big Data technologies. Further the paper includes the list of various Big Data tools, few case studies, few applications which are worth implementing using Big Data in healthcare followed by the concluding remarks.
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