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Big Data Analysis for Cardiovascular Diseases: Detection, Prevention, and Management
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Author(s): Miguel A. Sánchez-Acevedo (Universidad de la Cañada, Mexico & Universidad Popular Autónoma del Estado de Puebla, Mexico), Zaydi A. Acosta-Chí (Universidad de la Cañada, Mexico), Beatriz A. Sabino-Moxo (Universidad de la Cañada, Mexico), José A. Márquez-Domínguez (Universidad de la Cañada, Mexico)and Rosa M. Canton-Croda (Universidad Popular Autónoma del Estado de Puebla, Mexico)
Copyright: 2018
Pages: 18
Source title:
Big Data Management and the Internet of Things for Improved Health Systems
Source Author(s)/Editor(s): Brojo Kishore Mishra (C. V. Raman College of Engineering, India)and Raghvendra Kumar (LNCT Group of Colleges, India)
DOI: 10.4018/978-1-5225-5222-2.ch007
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Abstract
In the healthcare field, plenty of clinical data is generated every day from patient records, surveys, research papers, medical devices, among others sources. These data can be exploited to discover new insights about health issues. For helping decision makers and healthcare data managers, a survey of research works and tools covering the process of handling big data in the healthcare field is included. A methodology for CVD prevention, detection and management through the use of tools for big data analysis is proposed. Also, it is important to maintain privacy of patients when handling healthcare data; therefore, a list of recommendations for maintaining privacy when handling healthcare data is presented. Specific clinical analysis are recommended on those regions where the incidence rate of CVD is high, but a weak relation with the common risk factors is observed according to historical data. Finally, challenges which need to be addressed are presented.
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