Chronic Disease Progression Prediction: Leveraging Case‐Based Reasoning and Big Data Analytics

2021 ◽  
Author(s):  
Zlatana Nenova ◽  
Jennifer Shang
Keyword(s):  
Big Data ◽  
Chronic Disease ◽  
Disease Progression ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Case Based Reasoning ◽  
Progression Prediction ◽  
Case Based

scholarly journals Prevalence of chronic disease in older adults in multitier eye-care facilities in South India: Electronic medical records-driven big data analytics report

2021 ◽  
Vol 69 (12) ◽  
pp. 3618
Author(s):  
UmeshChandra Behera ◽  
Brooke Salzman ◽  
AnthonyVipin Das ◽  
GumpiliSai Prashanthi ◽  
Parth Lalakia ◽  
...  
Keyword(s):  
Older Adults ◽  
Big Data ◽  
Chronic Disease ◽  
Electronic Medical Records ◽  
Medical Records ◽  
Data Analytics ◽  
South India ◽  
Big Data Analytics ◽  
Eye Care ◽  
Care Facilities

scholarly journals A Web Services, Ontology and Big Data Analysis Technology-Based Cloud Case-Based Reasoning Agent for Energy Conservation of Sustainability Science

2020 ◽  
Vol 10 (4) ◽  
pp. 1387
Author(s):  
Shih-Chin Chen ◽  
Sheng-Yuan Yang
Keyword(s):  
Big Data ◽  
Web Services ◽  
Energy Conservation ◽  
Energy Saving ◽  
Sustainability Science ◽  
Big Data Analytics ◽  
Case Based Reasoning ◽  
Core Technology ◽  
Reasoning Agent ◽  
Case Based

Energy conservation is one of the important topics for sustainability science, while case-based reasoning is one of the most important techniques for sustainable processing. This study aimed to develop a cloud case-based reasoning agent that integrates multiple intelligent technologies and supports, which can help users to quickly, accurately, and effectively obtain useful cloud energy-saving information in a timely manner for sustainability science. The system was successfully built with the support of Web services technology, ontology, and big data analytics. To set up this energy-saving case-based reasoning agent, this study reviewed the relevant technologies for building a web services platform and explored how to widely integrate and support the cloud interaction of the energy-saving data processing agent via the technologies. In addition to presenting relevant R&D technologies and results in detail, this study carefully conducted performance and learning experiments to prove the system’s effectiveness. The results showed that the core technology of the case-based reasoning agent achieved good performance and that the learning effectiveness of the overall system was also great.

Statistical Visualization of Big Data Through Hadoop Streaming in RStudio

2022 ◽  
pp. 758-787
Author(s):  
Chitresh Verma ◽  
Rajiv Pandey
Keyword(s):  
Big Data ◽  
Data Visualization ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Data Streaming ◽  
Data Set ◽  
Graphical Modeling ◽  
Hadoop Mapreduce ◽  
R Packages ◽  
Case Based

Data Visualization enables visual representation of the data set for interpretation of data in a meaningful manner from human perspective. The Statistical visualization calls for various tools, algorithms and techniques that can support and render graphical modeling. This chapter shall explore on the detailed features R and RStudio. The combination of Hadoop and R for the Big Data Analytics and its data visualization shall be demonstrated through appropriate code snippets. The integration perspective of R and Hadoop is explained in detail with the help of a utility called Hadoop streaming jar. The various R packages and their integration with Hadoop operations in the R environment are explained through suitable examples. The process of data streaming is provided using different readers of Hadoop streaming package. A case based statistical project is considered in which the data set is visualized after dual execution using the Hadoop MapReduce and R script.

scholarly journals A conceptual framework for the adoption of big data analytics by e-commerce startups: a case-based approach

2019 ◽  
Vol 17 (2-4) ◽  
pp. 285-318 ◽  
Author(s):  
Abhishek Behl ◽  
Pankaj Dutta ◽  
Stefan Lessmann ◽  
Yogesh K. Dwivedi ◽  
Samarjit Kar
Keyword(s):  
Big Data ◽  
Conceptual Framework ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Case Based

Statistical Visualization of Big Data Through Hadoop Streaming in RStudio

2018 ◽  
pp. 549-577
Author(s):  
Chitresh Verma ◽  
Rajiv Pandey
Keyword(s):  
Big Data ◽  
Data Visualization ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Data Streaming ◽  
Data Set ◽  
Graphical Modeling ◽  
Hadoop Mapreduce ◽  
R Packages ◽  
Case Based

Data Visualization enables visual representation of the data set for interpretation of data in a meaningful manner from human perspective. The Statistical visualization calls for various tools, algorithms and techniques that can support and render graphical modeling. This chapter shall explore on the detailed features R and RStudio. The combination of Hadoop and R for the Big Data Analytics and its data visualization shall be demonstrated through appropriate code snippets. The integration perspective of R and Hadoop is explained in detail with the help of a utility called Hadoop streaming jar. The various R packages and their integration with Hadoop operations in the R environment are explained through suitable examples. The process of data streaming is provided using different readers of Hadoop streaming package. A case based statistical project is considered in which the data set is visualized after dual execution using the Hadoop MapReduce and R script.

Big Data Analytics: The Next Big Thing

2019 ◽  
Vol 54 (5) ◽  
pp. 20
Author(s):  
Dheeraj Kumar Pradhan
Keyword(s):  
Big Data ◽  
Data Analytics ◽  
Big Data Analytics

Strategy in Discovery Mode - Wie Big Data & Analytics strategisches Denken verdrängen kann

2020 ◽  
Vol 49 (5) ◽  
pp. 11-17
Author(s):  
Thomas Wrona ◽  
Pauline Reinecke
Keyword(s):  
Big Data ◽  
Data Analytics ◽  
Big Data Analytics

Big Data & Analytics (BDA) ist zu einer kaum hinterfragten Institution für Effizienz und Wettbewerbsvorteil von Unternehmen geworden. Zu viele prominente Beispiele, wie der Erfolg von Google oder Amazon, scheinen die Bedeutung zu bestätigen, die Daten und Algorithmen zur Erlangung von langfristigen Wettbewerbsvorteilen zukommt. Sowohl die Praxis als auch die Wissenschaft scheinen geradezu euphorisch auf den „Datenzug“ aufzuspringen. Wenn Risiken thematisiert werden, dann handelt es sich meist um ethische Fragen. Dabei wird häufig übersehen, dass die diskutierten Vorteile sich primär aus einer operativen Effizienzperspektive ergeben. Strategische Wirkungen werden allenfalls in Bezug auf Geschäftsmodellinnovationen diskutiert, deren tatsächlicher Innovationsgrad noch zu beurteilen ist. Im Folgenden soll gezeigt werden, dass durch BDA zwar Wettbewerbsvorteile erzeugt werden können, dass aber hiermit auch große strategische Risiken verbunden sind, die derzeit kaum beachtet werden.

A Review on Big Data Analytics Tools in Context with Scalability

2019 ◽  
Vol 7 (2) ◽  
pp. 273-277
Author(s):  
Ajay Kumar Bharti ◽  
Neha Verma ◽  
Deepak Kumar Verma
Keyword(s):  
Big Data ◽  
Data Analytics ◽  
Big Data Analytics
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