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Big Data Applications In Health Care And Education

B. K. Tripathy
Published 2018 · Business

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Technology plays a major role in all spheres of life and higher education and health care are no exceptions. The use of big data in higher education and health care are relatively new. The dynamics of higher education is passing through a phase of rapid changes. Also, the amount of data available in this field and proper analytics can reap the benefits and highlight on future techniques to be followed in handling the complex situations arisen from pressure exerted by accrediting agencies, governments and other stake holders. Higher education is becoming more and more complex with several institutes entering into the market with more and more diversified approaches. This makes the functionalities of all institutes of higher education to revise their approaches frequently to cope up with this pressure. The educational institutes have to ensure that the quality of learning programmes is at par with that of their counterparts at the national and global level. Analysis of vast data sources generated in this connection being more often not available for analysis is a major concern. The analysis of these volumes of data plays a major role in understanding and ensuring that institutions are aware of the changes occurring everywhere and they are taking care of their social responsibilities. Due to digitization of medical records in an attempt to make them available for research and development over the past ten to fifteen years, there is a huge amount of data, which besides being voluminous are complex, diverse and temporal which is collected by healthcare stockholders. An analysis of these data could collectively help the healthcare industry to find out problems related to variability in healthcare quality and escalating healthcare expenditure. In this chapter we shall make a critical analysis of these aspects of higher education and healthcare with respect to big data analysis and make some recommendations in this direction.
This paper references
Mass spectrometry-based metabolomics.
K. Dettmer (2007)
Reliable medical recommendation systems with patient privacy
T. R. Hoens (2010)
Concept definition for Big Data architecture in the education system
P. Michalík (2014)
The Evolution of Big Data and Learning Analytics in American Higher Education
Anthony G. Picciano (2012)
Healthcare information systems: data mining methods in the creation of a clinical recommender system
L. Duan (2011)
Big Data and analytics in higher education: Opportunities and challenges
B. Daniel (2015)
Influenza and Other Respiratory Viruses Involved in Severe Acute Respiratory Disease in Northern Italy during the Pandemic and Postpandemic Period (2009–2011)
E. Pariani (2014)
Data Mining Applications in Higher Education and Academic Intelligence Management
V. Bresfelean (2008)
Introduction to the special section on twitter and microblogging services
Irwin King (2013)
Big Data X-Learning Resources Integration and Processing in Cloud Environments
Kong Xiang-sheng (2014)
Metabolomics in diabetes.
A. Zhang (2014)
U-Air: when urban air quality inference meets big data
Yu Zheng (2013)
Inferring air pollution by sniffing social media
Shike Mei (2014)
Significance of Big Data and Analytics in Higher Education
B. Tulasi (2013)
A Data Mining view on Class Room Teaching Language
Umesh Kumar Pandey (2011)
Growing pains for metabolomics: the newest 'omic science is producing results--and more data than researchers know what to do with
B. Daviss (2005)
Principles for the post-GWAS functional characterization of cancer risk loci
M. Freedman (2011)
Data Changes Everything: Delivering on the Promise of Learning Analytics in Higher Education.
Ellen D. Wagner (2012)
N-smarts: networked suite of mobile atmospheric real-time sensors
R. Honicky (2008)
Mining Educational Data to Reduce Dropout Rates of Engineering Students
S. Pal (2012)
Predicting student performance: an application of data mining methods with an educational Web-based system
B. Minaei-Bidgoli (2003)
Twitter Improves Influenza Forecasting
M. J. Paul (2014)
The Use of Twitter to Track Levels of Disease Activity and Public Concern in the U.S. during the Influenza A H1N1 Pandemic
A. Signorini (2011)
What is Big Data? A Consensual Definition and a Review of Key Research Topics
A. Mauro (2015)
A Classification Model to Analyze the Spread and Emerging Trends of the Zika Virus in Twitter
Balakrushna Tripathy (2017)
Using Big Data to Predict Student Dropouts: Technology Affordances for Research.
David Niemi (2012)
Big Data for Development: From Information- to Knowledge Societies
M. Hilbert (2013)
Metabolomics in toxicology: preclinical and clinical applications.
D. Robertson (2011)
Educational Data Mining: A Review of the State of the Art
C. Romero (2010)
Applications of Big Data in Education
Faisal Kalota (2015)
Significance and Challenges of Big Data Research
X. Jin (2015)
Technology Enhanced Analytics (TEA) in Higher Education.
Ben K. Daniel (2013)
Growing pains for metabolomics
B. Daviss (2005)
Application of Big Data in Education Data Mining and Learning Analytics-A Literature Review
Katrina Sin (2015)
Managing, Analysing, and Integrating Big Data in Medical Bioinformatics: Open Problems and Future Perspectives
I. Merelli (2014)
Promises and Challenges of Big Data Computing in Health Sciences
T. Huang (2015)
Data Mining and Its Applications in Higher Education
Jing Luan (2002)
Health Recommender Systems: Concepts, Requirements, Technical Basics and Challenges
Martin Wiesner (2014)
Data Mining: A prediction for performance improvement using classification
B. K. Bhardwaj (2012)
Indoor air pollution in developing countries.
B. Chen (1990)
Metabolomic Characterization of Human Rectal Adenocarcinoma with Intact Tissue Magnetic Resonance Spectroscopy
K. Jordan (2009)
An Empirical Study of the Applications of Data Mining Techniques in Higher Education
V. Kumar (2011)

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