Pettersson, W. (2022) kep_solver: a Python package for kidney exchange programme exploration. Journal of Open Source Software, 7(80), 4881. (doi: 10.21105/joss.04881)
![[img]](https://eprints.gla.ac.uk/style/images/fileicons/text.png) |
Text
286248.pdf - Published Version Available under License Creative Commons Attribution. 219kB |
Abstract
Kidney disease is one of the top ten leading causes of death globally (WHO Global Health Estimates, 2019), and unfortunately has no known cure. Instead, late-stage kidney disease is treated with either dialysis or a donated kidney transplant. Of these, a kidney transplant is cheaper, and offers both a better quality of life and a longer life expectancy (Axelrod et al., 2018). Such donor kidneys can come from either living or deceased donors, with living donor transplants resulting in better outcomes for the recipient (Hart et al., 2017; Wolfe et al., 2010). However finding a living donor who is both willing to donate and medically compatible can be difficult. Kidney exchange programmes (KEPs) greatly increase the rate of living donor kidney transplants by alleviating the requirement that a willing donor must be medically compatible with their chosen recipient. Instead, recipients still pair with at least one willing donor, but transplants are organised such a donor donates a kidney to a recipient if and only if their paired recipient receives a kidney. In particular, a donor will often not donate to their paired recipient. The question that arises is then: given a number of recipients, along with their paired donors, which transplants should be selected to go ahead? This is one of the problems that KEPs solve. Commonly, this is solved by first building a compatibility graph: a graph that represents all the donor-and-recipient pairs as well as arcs indicating that there is a potential for a transplant from a donor to a recipient. Then a set of vertex-disjoint cycles are selected through an integer programme according to some pre-determined criteria (e.g. maximising number of transplants, maximising transplants to hard-to-match recipients). These selected cycles correspond to sets of transplants that have been selected to proceed, and will undergo further checks for medical compatibility and transplant procedures.
| Item Type: | Articles |
|---|---|
| Status: | Published |
| Refereed: | Yes |
| Glasgow Author(s) Enlighten ID: | Pettersson, Dr William |
| Authors: | Pettersson, W. |
| College/School: | College of Science and Engineering > School of Computing Science |
| Journal Name: | Journal of Open Source Software |
| Publisher: | Open Journals |
| ISSN: | 2475-9066 |
| ISSN (Online): | 2475-9066 |
| Copyright Holders: | Copyright © 2022 The Author |
| First Published: | First published in Journal of Open Source Software 7(80): 4881 |
| Publisher Policy: | Reproduced under a Creative Commons License |
University Staff: Request a correction | Enlighten Editors: Update this record
Funder and Project Information
Funder and Project Information