Big Data Challenges and Opportunities in Healthcare Informatics and Smart Hospitals

Hassan, Mohammed K.; Desouky, Ali I. El; Elghamrawy, Sally M.; Sarhan, Amany

doi:10.1007/978-3-030-01560-2_1

Cited by 29 publications

(22 citation statements)

References 43 publications

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“…Supply Chain Management (SCM) is one of the major contributors to improving the healthcare sector's performance. Still, its implementation is at the nascent stage worldwide [7]. Therefore, further study the supply chain's performance in providing excellent quality and service towards ending users requiring globalization.…”

Section: Conceptualizing the Evolution Of The Pharmaceutical Supply Cmentioning

confidence: 99%

International Integration of Pharmaceutical Supply Chains in Vietnam: An Overview of Challenges and Opportunities at Hospitals in Ho Chi Minh City

Quan

2020

International Journal of Medical and Health Sciences Research

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Section: Conceptualizing the Evolution Of The Pharmaceutical Supply Cmentioning

confidence: 99%

International Integration of Pharmaceutical Supply Chains in Vietnam: An Overview of Challenges and Opportunities at Hospitals in Ho Chi Minh City

Quan

2020

International Journal of Medical and Health Sciences Research

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“…This does not imply that any NoSQL model is a suitable choice, because we need a justifiable comparison between the NoSQL databases to choose the most suitable that can handle all the Vs that affect the IoT development layers. Some recent works [16,18,21] have reported their experiences in using Cloud platform, and edge/fog technologies for specialized applications. As pointed out in [21] there are some advantages and several advantages to using Cloud.…”

Section: Database Support For Smart City Developmentmentioning

confidence: 99%

“…Some recent works [16,18,21] have reported their experiences in using Cloud platform, and edge/fog technologies for specialized applications. As pointed out in [21] there are some advantages and several advantages to using Cloud. In smart city development the supervisory system in the city layer must have administrative role on the infrastructure, security, privacy, definition of contexts, and context constraints.…”

Section: Database Support For Smart City Developmentmentioning

confidence: 99%

“…In this section, we first review a literature survey to point out that database structures were not adequately investigated for smart city development. Some used Cloud platforms, and Edge and Fog Computing technologies [16,18,21], and many others [35,36,37,38] assumed database to exist as “black box” and focused only on context-awareness issues. Compared to these works, we next establish the significance of our work through a brief description of our current work on smart city development architecture [11].…”

Section: Database Support For Smart City Realizationmentioning

confidence: 99%

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Characterization and Efficient Management of Big Data in IoT-Driven Smart City Development

Alsaig

Alagar

Chammaa

et al. 2019

Sensors

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Smart city is an emerging initiative for integrating Information and Communication Technologies (ICT) in effective ways to support development of smart cities with enhanced quality of life for its citizens through safe and secure context-aware services. Major technical challenges to realize smart cities include resource use optimization, service delivery without interruption at all times in all aspects, minimization of costs, and reduction of resource consumption. To address these challenges, new techniques and technologies are required for modeling and processing the big data generated and used through the underlying Internet of Things (IoT). To this end, we propose a data-centric approach to IoT in conceptualizing the “things” from a service-oriented perspective and investigate efficient ways to identify, integrate, and manage big data. The data-centric approach is expected to better support efficient management of data with complexities inherent in IoT-generated big data. Furthermore, it supports efficient and scalable query processing and reasoning techniques required in development of smart city applications. This article redresses the literature and contributes to the foundations of smart cities applications.

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“…The term Big Data has a variety of definitions [2,[43][44][45][46], one proposed by the National Institute of Standards and Technology stating where data volume, acquisition rate or representation demand nontraditional approaches to data analysis or requires horizontal scaling for data processing [45]. Another definition is proposed by Hashem et al [2] as a set of technologies and techniques to discover hidden information from diverse, complex and massive scale datasets.…”

Section: Initial Conceptsmentioning

confidence: 99%

Parallelism Strategies for Big Data Delayed Transfer Entropy Evaluation

2019

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Generated and collected data have been rising with the popularization of technologies such as Internet of Things, social media, and smartphone, leading big data term creation. One class of big data hidden information is causality. Among the tools to infer causal relationships, there is Delay Transfer Entropy (DTE); however, it has a high demanding processing power. Many approaches were proposed to overcome DTE performance issues such as GPU and FPGA implementations. Our study compared different parallel strategies to calculate DTE from big data series using a heterogeneous Beowulf cluster. Task Parallelism was significantly faster in comparison to Data Parallelism. With big data trend in sight, these results may enable bigger datasets analysis or better statistical evidence.

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Big Data Challenges and Opportunities in Healthcare Informatics and Smart Hospitals

Cited by 29 publications

References 43 publications

International Integration of Pharmaceutical Supply Chains in Vietnam: An Overview of Challenges and Opportunities at Hospitals in Ho Chi Minh City

International Integration of Pharmaceutical Supply Chains in Vietnam: An Overview of Challenges and Opportunities at Hospitals in Ho Chi Minh City

Characterization and Efficient Management of Big Data in IoT-Driven Smart City Development

Parallelism Strategies for Big Data Delayed Transfer Entropy Evaluation

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