Decision Support System for Renal Transplantation

In: Proceedings of the 2018 IISE Annual Conference. Edited by K. Barker, D. Berry, C. Rainwater. Orlando: IISE; 2018: 431-436.

Posted: 23 Dec 2018 Last revised: 28 Aug 2019

See all articles by Muhammad Ehsan Khan

Muhammad Ehsan Khan

Binghamton University

Avishek Choudhury

West Virginia University - Industrial and Management Systems Engineering; West Virginia University

Daehan Won

Binghamton University

Amy Friedman

LiveOnNY

Date Written: May 22, 2018

Abstract

The burgeoning need for kidney transplantation mandates immediate attention. Mismatch of deceased donor-recipient kidney leads to post-transplant death. To ensure ideal kidney donor-recipient match and minimize post-transplant deaths, the paper develops a prediction model that identifies factors that determine the probability of success of renal transplantation, that is, if the kidney procured from the deceased donor can be transplanted or discarded. The paper conducts a study enveloping data for 584 imported kidneys collected from 12 transplant centers associated with an organ procurement organization located in New York City, NY. The predicting model yielding best performance measures can be beneficial to the healthcare industry. Transplant centers and organ procurement organizations can take advantage of the prediction model to efficiently predict the outcome of kidney transplantation. Consequently, it will reduce the mortality rate caused by mismatching of donor-recipient kidney transplantation during the surgery.

Keywords: Organ transplantation, Kidney transplantation, deceased kidney donor, Gradient Boosting Classifier, Random Forest

Suggested Citation

Khan, Muhammad Ehsan and Choudhury, Avishek and Won, Daehan and Friedman, Amy, Decision Support System for Renal Transplantation (May 22, 2018). In: Proceedings of the 2018 IISE Annual Conference. Edited by K. Barker, D. Berry, C. Rainwater. Orlando: IISE; 2018: 431-436., Available at SSRN: https://ssrn.com/abstract=3297572

Muhammad Ehsan Khan

Binghamton University ( email )

PO Box 6001
Binghamton, NY 13902-6000
United States

Avishek Choudhury (Contact Author)

West Virginia University - Industrial and Management Systems Engineering ( email )

West Virginia University ( email )

1347 Evansdale Dr
Morgantown, WV WV 26506
United States

Daehan Won

Binghamton University

PO Box 6001
Binghamton, NY 13902-6000
United States

Amy Friedman

LiveOnNY

460 W 34th St
New York, NY 10001
United States

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