Big Data and Kidney Transplantation: Basic Concepts and Initial Experiences

  • David J. Taber
  • Amit K. Mathur
  • Titte R. SrinivasEmail author


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.



Area Under the Curve-Receiver Operating Characteristic Curve


BK Virus


Body Mass Index


Blood Pressure


Confidence Interval




Delayed Graft Function


Estimated Glomerular Filtration Rate


Electronic Health Record


Graft Loss




International Classification of Diseases


Kidney Donor Risk Index




Myocardial Infarction


Natural Language Processing


Odds Ratio


Polymerase Chain Reaction


Systolic Blood Pressure


Scientific Registry of Transplant Recipients

Tx Database

Transplant Database


United Network for Organ Sharing


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Copyright information

© Springer International Publishing AG, part of Springer Nature 2017

Authors and Affiliations

  • David J. Taber
    • 1
  • Amit K. Mathur
    • 2
  • Titte R. Srinivas
    • 3
    Email author
  1. 1.Medical University of South Carolina, Division of Transplant SurgeryCharlestonUSA
  2. 2.Mayo Clinic, Division of Transplant SurgeryScottsdaleUSA
  3. 3.Transplant Nephrology, Intermountain Medical Center, Transplant ServicesMurrayUK

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