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NoSQL Technologies for Real Time (Patient) Monitoring

NoSQL Technologies for Real Time (Patient) Monitoring

Ciprian Dobre, Fatos Xhafa
Copyright: © 2015 |Pages: 28
ISBN13: 9781466674813|ISBN10: 1466674814|EISBN13: 9781466674820
DOI: 10.4018/978-1-4666-7481-3.ch008
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MLA

Dobre, Ciprian, and Fatos Xhafa. "NoSQL Technologies for Real Time (Patient) Monitoring." Advanced Technological Solutions for E-Health and Dementia Patient Monitoring, edited by Fatos Xhafa, et al., IGI Global, 2015, pp. 183-210. https://doi.org/10.4018/978-1-4666-7481-3.ch008

APA

Dobre, C. & Xhafa, F. (2015). NoSQL Technologies for Real Time (Patient) Monitoring. In F. Xhafa, P. Moore, & G. Tadros (Eds.), Advanced Technological Solutions for E-Health and Dementia Patient Monitoring (pp. 183-210). IGI Global. https://doi.org/10.4018/978-1-4666-7481-3.ch008

Chicago

Dobre, Ciprian, and Fatos Xhafa. "NoSQL Technologies for Real Time (Patient) Monitoring." In Advanced Technological Solutions for E-Health and Dementia Patient Monitoring, edited by Fatos Xhafa, Philip Moore, and George Tadros, 183-210. Hershey, PA: IGI Global, 2015. https://doi.org/10.4018/978-1-4666-7481-3.ch008

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Abstract

Today we witness a growing change in how public health administration thinks about medical data. We have slowly moved from paper-based patient records to digitally storing medical data, in support for advanced evidence-based mining and decision support processes. With this change comes great responsibility, among which efficient storing and accessing the health status of the patient is particularly important. In this chapter, the authors analyze current storage technologies for storing medical data. We are witnessing a shift from traditional relational database support to NoSQL technologies capable of offering great availability and scalability options, and back to the mixture between the SQL and NoSQL worlds, and scalable SQL databases. All these alternatives come with their own pros and cons, which the authors carefully analyze. They believe that their survey will help medical practitioners and developers of health applications make a more informed decision when designing medical data storage support.

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