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Ann. N. Y. Acad. Sci. · Jan 2017
Data science, learning, and applications to biomedical and health sciences.
- Nabil R Adam, Robert Wieder, and Debopriya Ghosh.
- Rutgers University Institute for Data Science, Learning, and Applications, Newark, New Jersey.
- Ann. N. Y. Acad. Sci. 2017 Jan 1; 1387 (1): 5-11.
AbstractThe last decade has seen an unprecedented increase in the volume and variety of electronic data related to research and development, health records, and patient self-tracking, collectively referred to as Big Data. Properly harnessed, Big Data can provide insights and drive discovery that will accelerate biomedical advances, improve patient outcomes, and reduce costs. However, the considerable potential of Big Data remains unrealized owing to obstacles including a limited ability to standardize and consolidate data and challenges in sharing data, among a variety of sources, providers, and facilities. Here, we discuss some of these challenges and potential solutions, as well as initiatives that are already underway to take advantage of Big Data.© 2017 New York Academy of Sciences.
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