Big data technology in health and biomedical research: A literature review

Big data and hadoop technologies are used for biomedical and health-care informatics research purpose. Huge information advances are progressively utilized for biomedical and medicinal services informatics research. A lot of natural and clinical information have been produced and gathered at a remarkable speed and scale. For instance, the new era of sequencing innovations empowers the expert cessing of billions of DNA grouping information every day, and the use of electronic health records (EHRs) is reporting a lot of patient information. The expense of securing and examining biomedical information is relied upon to diminish drastically with the assistance of innovation overhauls, for example, the rise of new sequencing machines, the improvement of novel equipment and programming for parallel processing, and the broad extension of EHRs. Huge information applications show new chances to find new learning and make novel techniques to enhance the nature of human services. The utilization of enormous information in social insurance is a quickly developing field, with numerous new disclosures and procedures distributed in the most recent five years. In this paper we present different areas of biomedical fields like bioinformatics, clinical informatics, imaging informatics, and general health care informatics. In particular, in bioinformatics, high-throughput tests encourage the exploration of new expansive affiliation investigations of ailments, and with clinical informatics, the clinical field profits by the boundless measure of gathered patient information for settling on savvy choices. Imaging informatics is presently all the more quickly incorporated with cloud stages to share therapeutic picture information and work processes, and general wellbeing informatics influences huge information methods for foreseeing and observing irresistible illness flare-ups, for example, Ebola. In this paper, we survey the late advance and leaps forward of enormous information applications in these human services areas and compress the difficulties, holes, and chances to enhance and progress huge information applications in social insurance. © 2016 SERSC.