Paper Info
Title
Graph-based optimization algorithm and software on kidney exchanges.
Abstract
Kidney transplantation is typically the most effective treatment for patients with end-stage renal disease. However, the supply of kidneys is far short of the fast-growing demand. Kidney paired donation (KPD) programs provide an innovative approach for increasing the number of available kidneys. In a KPD program, willing but incompatible donor-candidate pairs may exchange donor organs to achieve mutual benefit. Recently, research on exchanges initiated by altruistic donors (ADs) has attracted great attention because the resultant organ exchange mechanisms offer advantages that increase the effectiveness of KPD programs. Currently, most KPD programs focus on rule-based strategies of prioritizing kidney donation. In this paper, we consider and compare two graph-based organ allocation algorithms to optimize an outcome-based strategy defined by the overall expected utility of kidney exchanges in a KPD program with both incompatible pairs and ADs. We develop an interactive software-based decision support system to model, monitor, and visualize a conceptual KPD program, which aims to assist clinicians in the evaluation of different kidney allocation strategies. Using this system, we demonstrate empirically that an outcome-based strategy for kidney exchanges leads to improvement in both the quantity and quality of kidney transplantation through comprehensive simulation experiments.
Year
DOI
Venue
2012
10.1109/TBME.2012.2195663
IEEE Trans. Biomed. Engineering
Keywords
Field
DocType
kidney transplantation,optimisation,end-stage renal disease,optimal matches,interactive software-based decision support system,knowledge based systems,diseases,graph-based organ allocation algorithms,rule-based strategy,kidney paired donation programs,patient monitoring,conceptual kpd program,kidney exchanges,outcome-based strategy,organ exchange mechanisms,decision support systems,software,altruistic donors,kidney,graph theory,medical computing,interactive systems,graph-based optimization algorithm,patient treatment,expected utility,simulation experiment,decision support system,optimal matching,uncertainty,computational modeling,computer model,graphic user interface,algorithms,resource management,resource manager,rule based,graphical user interfaces
Resource management,Graph,Data mining,Optimal matching,Expected utility hypothesis,Computer science,Decision support system,Knowledge-based systems,Risk analysis (engineering),Electronic engineering,Software,Kidney transplantation
Journal
Volume
Issue
ISSN
59
7
1558-2531
Citations 
PageRank 
References 
7
0.91
2
Authors
6
Name
Order
Citations
PageRank
Yanhua Chen172.60
Yijiang Li270.91
John D Kalbfleisch371.24
Yan Zhou470.91
Alan Leichtman570.91
Peter X-K Song6144.81