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This methodology uses graph machine learning and allows for the integration of additional patient-donor attributes and collaboration between the optimization ...
Abstract—The Kidney Exchange Problem (KEP) determines organ exchange chains and cycles amongst a pool of patient-donor pairs (PDP) and non-directed donors ...
We briefly review the standard mathematical model for kidney exchange and techniques from the AI community used to clear real kidney exchanges, and then give ...
Abstract. Kidney exchanges are organized markets where patients swap willing but incompatible donors. In the last decade, kid- ney exchanges grew from small ...
We generate random kidney exchange graphs based on directed Erd˝os-Rényi graphs ... machine learning, pages 282–293. Springer, 2006 ... as sub-optimal changes to ...
Sep 23, 2023 · In Section 2 we describe kidney exchange programs and explain how to model them using a kidney exchange graph. ... Optimizing kidney exchange ...
May 3, 2018 · This approach employs a learning strategy for optimal solution searching. ... Graph-Based Optimization Algorithm and Software on Kidney Exchanges.
A new learning-based two-stage approach for approximately solving the Kidney-Exchange Problem is introduced, outputting approximate solutions on average 1.1 ...
May 18, 2024 · This paper introduces a new learning-based approach for approximately solving the Kidney-Exchange Problem (KEP), an NP-hard problem on ...
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A. E. Roth, T. Sonmez, and M. U. Unver. Efficient kidney exchange: Coincidence of wants in a market with compatibility-based preferences. American Economic ...