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Cloud enabled data analytics and visualization framework for health-shocks prediction

Mahmud, Shahid and Iqbal, Rahat and Doctor, Faiyaz (2016) 'Cloud enabled data analytics and visualization framework for health-shocks prediction.' Future Generation Computer Systems, 65. 169 - 181. ISSN 0167-739X

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Abstract

In this paper, we present a data analytics and visualization framework for health-shocks prediction based on large-scale health informatics dataset. The framework is developed using cloud computing services based on Amazon web services (AWS) integrated with geographical information systems (GIS) to facilitate big data capture, storage, index and visualization of data through smart devices for different stakeholders. In order to develop a predictive model for health-shocks, we have collected a unique data from 1000 households, in rural and remotely accessible regions of Pakistan, focusing on factors like health, social, economic, environment and accessibility to healthcare facilities. We have used the collected data to generate a predictive model of health-shock using a fuzzy rule summarization technique, which can provide stakeholders with interpretable linguistic rules to explain the causal factors affecting health-shocks. The evaluation of the proposed system in terms of the interpret-ability and accuracy of the generated data models for classifying health-shock shows promising results. The prediction accuracy of the fuzzy model based on a k-fold cross-validation of the data samples shows above 89% performance in predicting health-shocks based on the given factors.

Item Type: Article
Uncontrolled Keywords: Technology integration, Data analytics and Visualization, Cloud computing, Scientific overflow of big data, Development process of big data application, Healthcare demonstration
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Science and Health > Computer Science and Electronic Engineering, School of
Depositing User: Elements
Date Deposited: 19 Feb 2018 14:41
Last Modified: 19 Feb 2018 14:41
URI: http://repository.essex.ac.uk/id/eprint/21445

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