Big data and kidney transplantation: Basic concepts and initial experiences

David J. Taber; Amit Mathur; Titte R. Srinivas

doi:10.1007/978-3-319-62142-5_13

Big data and kidney transplantation: Basic concepts and initial experiences

David J. Taber, Amit Mathur, Titte R. Srinivas

Surgery

Research output: Chapter in Book/Report/Conference proceeding › Chapter

Abstract

We live in a data-rich world that is ever expanding, and the field of medicine has become particularly enriched with data from the electronic health record (EHR) and from sensors such as EKG monitors, glucometers, and pacemakers. Big Data is a term that is now frequently encountered in both the lay press and the technical literature and is best defined by the extreme volume, variety, or velocity of data. Large relational databases alone do not equate to Big Data (Table 13.2 and see discussion that follows). The magnitude of the data explosion that we live in consciously or unconsciously is underscored, which is outlined throughout this chapter. As a specific example this ever-growing field can have, we will use our recent inquiry into predicting kidney transplant outcomes using a big data approach and discuss the applicability of big data techniques in clinical transplantation.

Original language	English (US)
Title of host publication	Technological Advances in Organ Transplantation
Publisher	Springer International Publishing
Pages	297-313
Number of pages	17
ISBN (Electronic)	9783319621425
ISBN (Print)	9783319621418
DOIs	https://doi.org/10.1007/978-3-319-62142-5_13
State	Published - May 23 2018

ASJC Scopus subject areas

Medicine(all)
Health Professions(all)
Engineering(all)
Biochemistry, Genetics and Molecular Biology(all)

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10.1007/978-3-319-62142-5_13

Cite this

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Big data and kidney transplantation: Basic concepts and initial experiences

Abstract

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