American Journal of Engineering Research (AJER) 2016 American Journal of Engineering Research (AJER) e-ISSN: 2320-0847 p-ISSN : 2320-0936 Volume-5, Issue-12, pp-364-370 www.ajer.org Research Paper Open Access
Big Data Technologies in Health and Biomedical Enes Celik1, Muhammet Atalay2 1
(Department of Computer Programming, Kirklareli University, Turkey) 2 (Department of Quantitative Methods, Kirklareli University, Turkey)
ABSTRACT: In the last decade in order to analyze everything we do means to use the technology, we collect data in very large increases in the amount of many new developments in this field. At the intersection point of these trends we call "big Data", in order to be more efficient and productive, and helped to each sector. Biomedical technology in medical diagnosis and treatment can be used for the purpose of article, material, equipment, software, program, intelligent systems and equipment production is an interdisciplinary viewing technology. Biomedical Technology, as is the case in many developed and developing countries should be supported in Turkey priority science and technology are seen as one of the branches and various plans and programs. The rapid development of the right technology and there is a need for industry-academia relationship. In the health sector in other subgroups, is diagnostic kits. Hospitals, clinics, universities, laboratories and personally for many diagnostic kit used sensors comprise a wide market. Keywords: Big Data, Health, Biomedical, Bioinformation
I. INTRODUCTION Based on large data into or to the health sector, but to capture the full value of before must undergo fundamental changes in the industry. In the field of health is an ongoing process large data revolution. The process which began with the increase in the source of information over the past decade, pharmaceutical companies, research, collects and the patient data in digital medical data, some States developed.The US federal Government and other public institutions, the scope of public insurance programs and other information to clinical trials in patients, including health information. In parallel, taking advantage of the latest technological developments from a variety of sources, information derivation and analysis facilitated. Information for a single patient, many hospitals, and laboratories and from doctor's offices can come. Along with financial concerns and other factors have increased demands for large data. Showing a steady increase over the last 20 years medical expenses in the United States by 2014 GDP is approximately 600 billion dollars with 17.6%. Turkey also is approximately 5.4 per cent GDP in 2014 and 95 billion Turkish Lira (TL). The use of more physicians to give up too many users will be free to share the results of treatment, and treatment has reduced the volume of.Within the framework of the new plans, when the desired results in treatment cost less than provided. Taxpayers can also enter agreements with pharmaceutical companies, pharmaceutical companies, the result of the treatment process and giving feedback to the patient's health can be improved and taken off the cost of the drug in this new environment, to compile data from large health care stakeholders can exchange information. The increase in health care costs in large data can be effective in clinical trend when exceptional. Physicians can use traditional jurisdiction receiving treatment decision. But in the last few years evidence based, systematic review of the clinical data and a move toward treatment when decision based on the best available information one chooses. Individual data in large data collected algorithms often has provided strong evidence. In the health sector in the marketing and the use of large data partially such as banking sector remained in the back. Large data may produce positive results, the first movements in the field. These developments are promising, but the important question is: in the health sector is all data capture and use the potential of large or are there barriers that will prevent you’re checked out.
II. LITERATURE REVIEW Over the course of a year, 14 old driver, 20,000 km, cognitive and physical health status after a certain time period tracked, reflex and slowed with the passing of slowdown into the nervous system events to determine. Here the reasons for falling asleep on the analysis of the drivers.In this study, slowing habits of drivers almost every driver with correlation between 0.74 similar deceleration habits. Don't fall asleep or slowdown here in terms of a number of important health habits can be identified. Here is the solution as the
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