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Data Infrastructure for Medical Research

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Title: Data Infrastructure for Medical Research
Authors: Heinis, T
Ailamaki, A
Item Type: Journal Article
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.
Issue Date: 8-Nov-2017
Date of Acceptance: 1-Jan-2017
URI: http://hdl.handle.net/10044/1/56781
DOI: https://dx.doi.org/10.1561/1900000050
ISSN: 1931-7883
Publisher: Now Publishers
Start Page: 131
End Page: 238
Journal / Book Title: Foundations and Trends in Databases
Volume: 8
Issue: 3
Copyright Statement: © 2017 T. Heinis and A. Ailamaki
Sponsor/Funder: Engineering & Physical Science Research Council (E
European Research Office
Funder's Grant Number: EP/N023242/1
Keywords: Science & Technology
Computer Science, Software Engineering
Computer Science
Publication Status: Published
Appears in Collections:Computing
Faculty of Engineering