Clinical decisions are more promising and evidence-based, hence, big data analytics to
assist clinical decision-making has been expressed for a variety of clinical fields. Due to the …

A systematic literature review of papers on big data in healthcare published between 2010
and 2015 was conducted. This paper reviews the definition, process, and use of big data in …

Objective. The aim of this study was to provide a definition of big data in healthcare.
Methods. A systematic search of PubMed literature published until May 9, 2014, was …

Introduction Machine learning capability holds promise to inform disease models, the
discovery and development of novel disease modifying therapeutics and prevention …

Background Diabetes mellitus is a common and complicated chronic lifelong disease.
Hence, it is of high clinical significance to find the most relevant clinical indexes and to …

As global policy makers prioritize big data policy, it is important to try to outline expected
outcomes vis-à-vis health sector objectives. We identify initiatives aimed at promoting the …

Reference intervals are commonly used as a decision-making tool. In this review, we
provide an overview on “big data” and reference intervals, describing the rationale, current …

Digital imaging and medical reporting have acquired an essential role in healthcare, but the
main challenge is the storage of a high volume of patient data. Although newer technologies …

Big data technologies are nowadays providing health care with powerful instruments to
gather and analyze large volumes of heterogeneous data collected for different purposes …

Big data has been a hot topic in health care and biomedical research in recent years.
Medical and health field has entered a big data era [1]. China is a large country with a …