Volume and Value of Big Healthcare Data.

TitleVolume and Value of Big Healthcare Data.
Publication TypeJournal Article
Year of Publication2016
AuthorsDinov, Ivo D.
JournalJ Med Stat Inform
Date Published2016

Modern scientific inquiries require significant data-driven evidence and trans-disciplinary expertise to extract valuable information and gain actionable knowledge about natural processes. Effective evidence-based decisions require collection, processing and interpretation of vast amounts of complex data. The Moore's and Kryder's laws of exponential increase of computational power and information storage, respectively, dictate the need rapid trans-disciplinary advances, technological innovation and effective mechanisms for managing and interrogating Big Healthcare Data. In this article, we review important aspects of Big Data analytics and discuss important questions like: What are the challenges and opportunities associated with this biomedical, social, and healthcare data avalanche? Are there innovative statistical computing strategies to represent, model, analyze and interpret Big heterogeneous data? We present the foundation of a new compressive big data analytics (CBDA) framework for representation, modeling and inference of large, complex and heterogeneous datasets. Finally, we consider specific directions likely to impact the process of extracting information from Big healthcare data, translating that information to knowledge, and deriving appropriate actions.

Alternate JournalJ Med Stat Inform
PubMed ID26998309
PubMed Central IDPMC4795481
Grant ListP20 NR015331 / NR / NINR NIH HHS / United States
P30 DK089503 / DK / NIDDK NIH HHS / United States
P50 NS091856 / NS / NINDS NIH HHS / United States
U54 EB020406 / EB / NIBIB NIH HHS / United States