R中的医疗保健数据建模

Diva Pant, Vishal Kumar, J. Kishore, Ritu Pal
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引用次数: 3

摘要

对大数据前所未有的兴趣为增强技术铺平了道路。大数据的主要用途之一是在医疗保健分析领域。医疗保健数据来自不同的来源。特别是电子病历数据提供了患者健康状况的全面视图。人们越来越关注自己的健康,希望获得最好的医疗保健,尤其是随着新技术的不断发展。我们可以分析这个天文病人的信息,并尝试研究某些模式,这可以让我们更好地理解目前的数据。在这项研究中,从一家医院收集了数千名患者的神经学数据集。从这些数据中,我们考虑了头部损伤的特殊病例,并研究和分析了脉搏率、血压、格拉斯哥昏迷量表、呼吸率、中枢神经系统等具体属性。分析基于两个因素:患者住院时间和损伤严重程度。在数据基础上建立了分类模型,并利用其统计软件包和图形功能在R编程中进行了实现。
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Healthcare data modeling in R
The unprecedented interest in big data has paved way for augmented technologies. One of the major usefulness of big data is found in the field of healthcare analytics. The healthcare data come from varied sources. Specifically EHR data provide a comprehensive view of patient's health. People are paying more attention to their health and want the best possible healthcare especially with new technologies evolving every now and then. We can analyze this astronomical patient's information and try to study certain patterns, which can give us the better understanding of the data present. In this study a neurological dataset of thousand patients has been collected from a hospital. Out of this data the particular cases of head injury are taken into account and specific attributes like pulse rate, blood pressure, Glasgow coma scale, respiratory rate, CNS are studied and analyzed. The analysis is performed on the basis of two factors: duration of patient's stay in the hospital and seriousness level of the injury. A classification model is prepared on the data and the implementation is carried out in R Programming, using its statistical packages and graphical abilities.
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