Big data is among the most significant modern trends in informatics due to its potential applications and recent emergence. Everything on the Internet is deeply interconnected, and tools that can gather and analyze enormous amounts of information have recently emerged. The discovery of numerous trends, previously an occupation that could only be delegated to humans, can now be automated. The idea has applications in a broad variety of spheres, including healthcare.
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Most commonly used sources of information analyzed via big data mining are social networks, as they provide vast amounts of information presented in a readable form. According to Andreu-Perez, Poon, Merrifield, Wong, and Yang (2015), analysis of text posts and messages on sites such as Twitter can discover correlations with the overall mental state of the population and potentially locate anomalies. Other trends, such as increased occurrences of asthma, can also be predicted. Gathering data from electronic health records for research purposes, are also possible, and the range of possibilities is extensive.
Big data analysis is among the most influential modern trends in informatics and it has applications in virtually every sphere of human life. Its uses in medicine offer unprecedented opportunities to analyze social health and predict health trends through scanning social network posts. Big data enables new approaches for studies, where researchers have access to vast amounts of unbiased data as well as the tools to identify common factors. Ultimately, technology has the potential to revolutionize healthcare, although concerns such as privacy have to be addressed first.
Andreu-Perez, J., Poon, C. C., Merrifield, R. D., Wong, S. T., & Yang, G. Z. (2015). Big data for health. IEEE Journal of Biomedical and Health Informatics, 19(4), 1193-1208.