Activity Pattern Mining from Social Media for Healthcare Monitoring on Big data

被引:0
|
作者
Sadagopan, S. [1 ]
Michael, G. [1 ]
机构
[1] BIHER, BIST, Dept Comp Sci & Engn, Chennai, Tamil Nadu, India
关键词
Healthcare; Big data; Activity Patterns Likelihood;
D O I
10.26782/jmcms.spl.2019.08.00023
中图分类号
O3 [力学];
学科分类号
08 ; 0801 ;
摘要
Big data applications introduce novel openings for establishinginnovative information and produce differentadvanced methods to improve the worth of healthcare.In this paper, a novel activity pattern mining from social media for healthcare to examine big data applications in different biomedical multi-disciplines such as bioinformatics, medical imaging and community healthcare applications.Big data analytical tools perform the key part in their task for extracting hidden behavioural and expressive patterns frompersonal messages and their tweets. The behavioural patterns of the users can realizetheir additional informations about their concealed feelings and sentiments. Further, the neural network is modelled to predict the psychological informations, such as nervousness, depression, behavioural disorder and mental stress.This is also shows that integrating variety of sources of data enables medical practitioner to show a novel investigation of patient care processes, improvements in new mobile healthcare technological developments aid real-time data collection, archiving and analysis of data in distributed environments.
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页码:184 / 189
页数:6
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