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Data Infrastructure for Medical Research
Author(s): Thomas Heinis;Anastasia Ailamaki
Source: Journal:Foundations and Trends® in Databases ISSN Print:1931-7883, ISSN Online:1931-7891 Publisher:Now Publishers Volume 8 Number 3, Pages: 111(131-238) DOI: 10.1561/1900000050
Abstract:
While we are witnessing rapid growth in data across the sciences and
in many applications, this growth is particularly remarkable in the
medical domain, be it because of higher resolution instruments and
diagnostic tools (e.g. MRI), new sources of structured data like activity
trackers, the wide-spread use of electronic health records and many
others. The sheer volume of the data is not, however, the only challenge
to be faced when using medical data for research. Other crucial challenges
include data heterogeneity, data quality, data privacy and so
on. In this article, we review solutions addressing these challenges by
discussing the current state of the art in the areas of data integration,
data cleaning, data privacy, scalable data access and processing in the
context of medical data. The techniques and tools we present will give
practitioners — computer scientists and medical researchers alike —
a starting point to understand the challenges and solutions and ultimately
to analyse medical data and gain better and quicker insights.
T. Heinis
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