Applying NoSQL Databases for Operationalizing Clinical Data Mining Models

Mazurek, Marcin

doi:10.1007/978-3-319-06932-6_51

Cited by 18 publications

(10 citation statements)

References 2 publications

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“…, Jin et al. , Mazurek ). Some research work has also studied and proposed several interactive methods of sharing medical data from multiple platforms (Chen et al.…”

Section: Healthcare Systemsmentioning

confidence: 99%

Emergence of Big Data Research in Operations Management, Information Systems, and Healthcare: Past Contributions and Future Roadmap

Guha

Kumar

2018

Production and Operations Management

192

114

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I n this day, in the age of big data, consumers leave an easily traceable digital footprint whenever they visit a website online. Firms are interested in capturing the digital footprints of their consumers to understand and predict consumer behavior. This study deals with how big data analytics has been used in the domains of information systems, operations management, and healthcare . We also discuss the future potential of big data applications in these domains (especially in the areas of cloud computing, Internet of Things and smart city, predictive manufacturing and 3-D printing, and smart healthcare) and the associated challenges. In this study, we present a framework for applications of big data in these domains with the goal of providing some interesting directions for future research.

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“…, Jin et al. , Mazurek ). Some research work has also studied and proposed several interactive methods of sharing medical data from multiple platforms (Chen et al.…”

Section: Healthcare Systemsmentioning

confidence: 99%

Emergence of Big Data Research in Operations Management, Information Systems, and Healthcare: Past Contributions and Future Roadmap

Guha

Kumar

2018

Production and Operations Management

192

114

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“…Compared with a traditional relational database that handles structured data well, the novel NoSQL is a great prospect for storing unstructured data. Mazurek 60 proposed a system that combines both relational and multidimensional technologies with NoSQL repositories to enable data mining techniques and provide flexibility and speed in data processing. Nguyen et al 61 presented a prototype system for storing clinical signal data, where the time series data of clinical sensors are stored within HBase in a way that the row key serves as the time stamp of a single value, and the column stores patient physiological values that correspond with the row key time stamp.…”

Section: Big Data Applicationsmentioning

confidence: 99%

Big Data Application in Biomedical Research and Health Care: A Literature Review

Luo

Gopukumar

et al. 2016

Biomed Inform Insights

417

214

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Big data technologies are increasingly used for biomedical and health-care informatics research. Large amounts of biological and clinical data have been generated and collected at an unprecedented speed and scale. For example, the new generation of sequencing technologies enables the processing of billions of DNA sequence data per day, and the application of electronic health records (EHRs) is documenting large amounts of patient data. The cost of acquiring and analyzing biomedical data is expected to decrease dramatically with the help of technology upgrades, such as the emergence of new sequencing machines, the development of novel hardware and software for parallel computing, and the extensive expansion of EHRs. Big data applications present new opportunities to discover new knowledge and create novel methods to improve the quality of health care. The application of big data in health care is a fast-growing field, with many new discoveries and methodologies published in the last five years. In this paper, we review and discuss big data application in four major biomedical subdisciplines: (1) bioinformatics, (2) clinical informatics, (3) imaging informatics, and (4) public health informatics. Specifically, in bioinformatics, high-throughput experiments facilitate the research of new genome-wide association studies of diseases, and with clinical informatics, the clinical field benefits from the vast amount of collected patient data for making intelligent decisions. Imaging informatics is now more rapidly integrated with cloud platforms to share medical image data and workflows, and public health informatics leverages big data techniques for predicting and monitoring infectious disease outbreaks, such as Ebola. In this paper, we review the recent progress and breakthroughs of big data applications in these health-care domains and summarize the challenges, gaps, and opportunities to improve and advance big data applications in health care.

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“…Marcin Mazurek proposed a model titled to combine both RDBMS and NoSQL technologies in an analytical system [2].…”

Section: Literature Reviewmentioning

confidence: 99%

Withdrawn

2020

IJITEE

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Data mining models of education system is limited to relatively small scope of researches and analysis. In the information age, it is the vital issue to retrieve and processing available data in real time. The education system based on relational database has lack capabilities of processing real time data for its large volume and unstructured format. On the other side, NoSQL repositories have strong architecture, it can process big data efficiently in real time by using appropriate model. NoSQL is a non-relational database management system, which stand for "Not Only SQL" or "Not SQL", it can store a wide variety of data, including document, key-value, columnar and graph formats. Relational Database Management System uses SQL syntax to store, retrieve and mining necessary data. Instead, NoSQL database system circumscribe a wide range of database technologies that can store structured, semi-structured, unstructured and polymorphic data. In this paper, we proposed an improved model for data mining by NoSQL repositories and transformation of data from unstructured form to structured form using NoSQL technologies. Double view of big data collected in the database use data mining technology to retrieve required data. Appropriate process of query a database allows to effective retrieval of imported data for analytical systems. Data can be available for analysis instantly after submitted by users. The proposed model can be suitable for any institutes or organizations, which have a large amount of data.

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Applying NoSQL Databases for Operationalizing Clinical Data Mining Models

Cited by 18 publications

References 2 publications

Emergence of Big Data Research in Operations Management, Information Systems, and Healthcare: Past Contributions and Future Roadmap

Emergence of Big Data Research in Operations Management, Information Systems, and Healthcare: Past Contributions and Future Roadmap

Big Data Application in Biomedical Research and Health Care: A Literature Review

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