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Home / Journals / Science Journal of Public Health / EHealth and Big Data in Medicine
EHealth and Big Data in Medicine
Lead Guest Editor:
Professor Jivka Borislavova Vinarova
Healthcare and social sciences department, New Bulgarian University, Sofia, Bulgaria
Guest Editors
Iliya Ivanov Pendzhurov
Healthcare and Social Sciences Department, New Bulgarian University
Sofia, Bulgaria
Introduction
The term Big data ( Great Information arrays) for first time to mentions in 1997 in report "Application-Controlled Demand Paging for Out-of-Core Visualization", read 8th Conference on visualization organized by IEEE (www.ieee.org / about / ieee_history.html). On conference USENIX is shown presentation "Big Data and the Next Wave of Infra Stress", but the generation of idea started in 1975, when Japanese ministry of Posts and Telecommunications begins to explore quantitatively the Information flow in Japan - Information Flow Census (idea for this measurement is offered in 1969). This happened 15 years before the World Wide Web was created!

Big Data in Health combines all the electronic health data, which is so large and complicated that they are almost impossible to cultivate with traditional or common tools and methods for managing them. Circulating Big Data in healthcare is striking not only because of its volume, but also because of the type`s diversity and changing and managing rate. The main are:

1. clinical data for decision support by the CIS with different specialization (diagnostic, prognostic, with elements of artificial intelligence, management, nursing, etc.), mainly standardized data from electronic patient records (EPRs)
2. registered data from monitoring sensors and recording Devices
3. expert generated specific indicators; written notes and medical prescriptions
4. sound recordings and visual images
5. specialized research
6. drug data
7. emergency data
8. any administrative-passport data
9. Insurance and health insurance
10. Social media publications, including Twitter feeds, blogs, status updates on Facebook and other platforms and web pages
11. data from non-conventional medicine - traditional practices, experience and user results; non-professional health and medical initiatives
12. Regulatory and statutory health documents from the fields of social medicine, public health, medical science, health market, politics and culture.
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