Big Data and Health Care: Challenges and Opportunities for Coordinated Policy Development in the EU

2015 ◽  
Vol 1 (4) ◽  
pp. 285-300 ◽  
Author(s):  
Sebastian Salas-Vega ◽  
Adria Haimann ◽  
Elias Mossialos
Keyword(s):  
Health Care ◽  
Big Data ◽  
Policy Development ◽  
Challenges And Opportunities ◽  
The Eu

The European Union’s Policy towards its Eastern Neighbours: The Crisis in Ukraine

2018 ◽  
Author(s):  
Tatsiana Shaban
Keyword(s):  
Crisis Management ◽  
Policy Development ◽  
Interesting Case ◽  
European Neighbourhood Policy ◽  
Significant Progress ◽  
Challenges And Opportunities ◽  
External Governance ◽  
Institutional Challenges ◽  
The Relationship ◽  
The Eu

The European Union’s neighbourhood is complex and still far from being stable. In Ukraine, significant progress has occurred in many areas of transition; however, much work remains to be done, especially in the field of regional development and governance where many legacies of the Soviet model remain. At the crossroads between East and West, Ukraine presents an interesting case of policy development as an expression of European Union (EU) external governance. This paper asks the question: why was the relationship between the EU and Ukraine fairly unsuccessful at promoting stability in the region and in Ukraine? What was missing in the European Neighbourhood Policy (ENP) in Ukraine that rendered the EU unable to prevent a conflict on the ground? By identifying security, territorial, and institutional challenges and opportunities the EU has faced in Ukraine, this paper underlines the most important factors accounting for the performance of its external governance and crisis management in Ukraine.   Full text available at: https://doi.org/10.22215/rera.v12i2.1310

scholarly journals The European Union’s Policy towards its Eastern Neighbours: The Crisis in Ukraine

2018 ◽  
Vol 12 (2) ◽  
Author(s):  
Tatsiana Shaban
Keyword(s):  
Crisis Management ◽  
Policy Development ◽  
Interesting Case ◽  
European Neighbourhood Policy ◽  
Significant Progress ◽  
Challenges And Opportunities ◽  
External Governance ◽  
Institutional Challenges ◽  
The Relationship ◽  
The Eu

The European Union’s neighbourhood is complex and still far from being stable. In Ukraine, significant progress has occurred in many areas of transition; however, much work remains to be done, especially in the field of regional development and governance where many legacies of the Soviet model remain. At the crossroads between East and West, Ukraine presents an interesting case of policy development as an expression of European Union (EU) external governance. This paper asks the question: why was the relationship between the EU and Ukraine fairly unsuccessful at promoting stability in the region and in Ukraine? What was missing in the European Neighbourhood Policy (ENP) in Ukraine that rendered the EU unable to prevent a conflict on the ground? By identifying security, territorial, and institutional challenges and opportunities the EU has faced in Ukraine, this paper underlines the most important factors accounting for the performance of its external governance and crisis management in Ukraine.

scholarly journals BIG DATA ANALYSIS IN HEALTH CARE DOMAIN: A SYSTEMATIC REVIEW

2020 ◽  
Vol 5 (2) ◽  
pp. 1-8
Author(s):  
Abhishek Bajpai ◽  
Dr. Sanjiv Sharma
Keyword(s):  
Health Care ◽  
Big Data ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Large Data ◽  
Large Data Sets ◽  
Data Sets ◽  
Healthcare Data ◽  
Challenges And Opportunities ◽  
Business Profit

As the Volume of the data produced is increasing day by day in our society, the exploration of big data in healthcare is increasing at an unprecedented rate. Now days, Big data is very popular buzzword concept in the various areas. This paper provide an effort is made to established that even the healthcare industries are stepping into big data pool to take all advantages from its various advanced tools and technologies. This paper provides the review of various research disciplines made in health care realm using big data approaches and methodologies. Big data methodologies can be used for the healthcare data analytics (which consist 4 V’s) which provide the better decision to accelerate the business profit and customer affection, acquire a better understanding of market behaviours and trends and to provide E-Health services using Digital imaging and communication in Medicine (DICOM).Big data Techniques like Map Reduce, Machine learning can be applied to develop system for early diagnosis of disease, i.e. analysis of the chronic disease like- heart disease, diabetes and stroke. The analysis on the data is performed using big data analytics framework Hadoop. Hadoop framework is used to process large data sets Further the paper present the various Big data tools , challenges and opportunities and various hurdles followed by the conclusion.                                      

scholarly journals Challenges and Opportunities of Big Data in Health Care: A Systematic Review

2016 ◽  
Vol 4 (4) ◽  
pp. e38 ◽  
Author(s):  
Clemens Scott Kruse ◽  
Rishi Goswamy ◽  
Yesha Raval ◽  
Sarah Marawi
Keyword(s):  
Systematic Review ◽  
Health Care ◽  
Big Data ◽  
Challenges And Opportunities

scholarly journals Study on Big Data Challenges and Opportunities

2018 ◽  
pp. 424-429
Author(s):  
Meet Hire ◽  
Mayur Gavande ◽  
Krupit Chovatiya ◽  
Aditya Tekale ◽  
Mr. Pritesh Patel ◽  
...  
Keyword(s):  
Health Care ◽  
Big Data ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Data Governance ◽  
Early Detection Of Disease ◽  
Managerial Skills ◽  
Age Related ◽  
Challenges And Opportunities ◽  
Business Sectors

Big data analytics offers promise in many business sectors, and health care is looking at big data to provide answers to many age-related issues, particularly dementia and chronic disease management. The purpose of this review was to summarize the challenges faced by big data analytics and the opportunities that big data opens in health care. The top challenges were issues of data structure, security, data standardization, storage and transfers, and managerial skills such as data governance. The top opportunities revealed were quality improvement, population management and health, early detection of disease, data quality, structure, and accessibility, improved decision making, and cost reduction.

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