Predictive Methodology for Diabetic Data Analysis in Big Data

被引:63
|
作者
Kumar, Saravana N. M. [1 ]
Eswari, T. [3 ]
Sampath, P. [2 ]
Lavanya, S. [3 ]
机构
[1] Bannari Amman Insitute Technol, Dept CSE, Sathyamangalam 638401, India
[2] Bannari Amman Inst Technol, Dept CSE, Sathymangalam 628401, India
[3] Sri Krishna Coll Engn & Techechnol, Dept IT, Coimbatore 641008, Tamil Nadu, India
关键词
Healthcare industry; Hadoop/Map Reduce; Big Data; Predictive analysis;
D O I
10.1016/j.procs.2015.04.069
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Modernizing healthcare industry's move towards processing massive health records, and to access those for analysis and put into action will greatly increases the complexities. Due to the growing unstructured nature of Big Data form health industry, it is necessary to structure and emphasis its size into nominal value with possible solution. Healthcare industry faces many challenges that make us to know the importance to develop the data analytics. Diabetic Mellitus (DM) is one of the Non Communicable Diseases (NCD), is a major health hazard in developing countries such as India. The acute nature of DM is associated with long term complications and numerous of health disorders. In this paper, we use the predictive analysis algorithm in Hadoop/Map Reduce environment to predict the diabetes types prevalent, complications associated with it and the type of treatment to be provided. Based on the analysis, this system provides an efficient way to cure and care the patients with better outcomes like affordability and availability. (C) 2015 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
引用
收藏
页码:203 / 208
页数:6
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