Big Data Research in Fighting COVID-19: Contributions and Techniques

Riswantini, Dianadewi; Nugraheni, Ekasari; Arisal, Andria; Khotimah, Purnomo Husnul; Munandar, Devi; Suwarningsih, Wiwin

doi:10.3390/bdcc5030030

Cited by 15 publications

(11 citation statements)

References 111 publications

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“…Riswantini et al. [14] discussed the role and contribution of big data research in five primary domains, including healthcare, social life, government policy, business and management, and the environment from a COVID-19 viewpoint. The findings of this article showed that healthcare and social life are significant research areas.…”

Section: Introductionmentioning

confidence: 99%

A visual review of artificial intelligence and Industry 4.0 in healthcare

Sood¹,

Rawat²,

Kumar³

2022

Computers and Electrical Engineering

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Section: Introductionmentioning

confidence: 99%

A visual review of artificial intelligence and Industry 4.0 in healthcare

Sood¹,

Rawat²,

Kumar³

2022

Computers and Electrical Engineering

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“…In recent years, there has been a process of digitalization and technological innovation in the healthcare sector to enable the transformation of a huge volume of data into valuable health BD, optimize resources, and improve both the patient experience and organizational performance [ 66 ]. The main sources of health data are EHR [ 38 ], medical data [ 130 ], laboratory information systems [ 131 , 132 , 133 , 134 , 135 ], biometric sources, patient-reported data, and social media (wearable devices and sensors that provide information about a patient’s lifestyle) [ 22 , 130 ].…”

Section: Discussionmentioning

confidence: 99%

“…Despite the important strides made in healthcare digitalization, there are numerous challenges to making the healthcare sector more resilient in the face of health crises. In this regard, it is necessary not only to strengthen the system but also to change its architecture toward a connected care model in which the organization, care, and assistance processes are redefined from a digital perspective and allow for making informed decisions using cutting-edge technology and BDA [ 22 , 134 , 135 ].…”

Section: Discussionmentioning

confidence: 99%

Towards the Use of Big Data in Healthcare: A Literature Review

et al. 2022

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The interest in new and more advanced technological solutions is paving the way for the diffusion of innovative and revolutionary applications in healthcare organizations. The application of an artificial intelligence system to medical research has the potential to move toward highly advanced e-Health. This analysis aims to explore the main areas of application of big data in healthcare, as well as the restructuring of the technological infrastructure and the integration of traditional data analytical tools and techniques with an elaborate computational technology that is able to enhance and extract useful information for decision-making. We conducted a literature review using the Scopus database over the period 2010–2020. The article selection process involved five steps: the planning and identification of studies, the evaluation of articles, the extraction of results, the summary, and the dissemination of the audit results. We included 93 documents. Our results suggest that effective and patient-centered care cannot disregard the acquisition, management, and analysis of a huge volume and variety of health data. In this way, an immediate and more effective diagnosis could be possible while maximizing healthcare resources. Deriving the benefits associated with digitization and technological innovation, however, requires the restructuring of traditional operational and strategic processes, and the acquisition of new skills.

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“…The requirements of the results of data cleaning comprise the standardization of data format, ensuring no data are abnormal, removing erroneous data, and filling f blank data. Data integration is the unified processing of multiple data sources in massive data sets to improve the effectiveness of data storage [45]. If the form of the original data is not suitable for the information processing algorithm, data transformation is necessary.…”

Section: Mining Technology Under Big Datamentioning

confidence: 99%

Design of Intelligent Management Platform for Industry–Education Cooperation of Vocational Education by Data Mining

Hao

Yang

et al. 2022

Applied Sciences

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Data are playing an increasingly important role in the development of industry–education cooperation strategies in vocational education and training. The objective of this study was to promote the comprehensive progress of an industry–education cooperation system and improve the effect of the application of big data technology in this system. First, we designed of a big data technology application in an intelligent management platform system for industry–education cooperation. Second, we analyzed the synthetical design of the system. Finally, we optimized and designed a support vector machine (SVM) data mining (DM) algorithm model based on big data, and evaluated the model. The results revealed that the designed algorithm model provides outstanding advantages compared with similar algorithm models. In general, the highest average computation time of the designed SVM algorithm model is about 95 ms. The overall average calculation time linearly decreases around 200 iterations and tends to be stable, and the lowest overall average computation time is about 20 ms. In the DM process, the highest accuracy rate of the model is about 97%, and the lowest is about 92%. The DM accuracy rate is always stable as the number of iterations of the model continues to increase. The designed model slowly increases the occupancy rate of the system in the process of increasing computing time. At about 60 min, the system occupancy rate of the model tends to be stable, and the highest is maintained at about 23%. This study not only provides technical support for the optimization of DM algorithms with big data technology, but also contributes to the integrated development of industry–education cooperation systems.

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Big Data Research in Fighting COVID-19: Contributions and Techniques

Cited by 15 publications

References 111 publications

A visual review of artificial intelligence and Industry 4.0 in healthcare

A visual review of artificial intelligence and Industry 4.0 in healthcare

Towards the Use of Big Data in Healthcare: A Literature Review

Design of Intelligent Management Platform for Industry–Education Cooperation of Vocational Education by Data Mining

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