Annals

Special Issue: Data Science, Learning, and Applications to Biomedical and Health Sciences

Edited by

Nabil R. Adams (Rutgers University)

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Special Issue: Data Science, Learning, and Applications to Biomedical and Health Sciences

Published: January 2017

Volume 1387

Published since 1824, Annals of the New York Academy of Sciences is the Academy’s premier scientific publication.

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The 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. Papers in this special issue discuss some of these challenges and potential solutions, as well as initiatives that are already underway to take advantage of Big Data.