An Exploration of Optimizing Kidney Exchanges with Graph Machine Learning-Reference-Cited by-同舟云学术

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An Exploration of Optimizing Kidney Exchanges with Graph Machine Learning

Published:2024-05-07 Issue: Volume: Page:114-119
ISSN:
Container-title:2024 IEEE Conference on Cognitive and Computational Aspects of Situation Management (CogSIMA)
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Author:

Nau Calvin¹,Sankaran Prashant²,Sudit Moises²,Khazaelpour Payam¹,McConky Katie¹,Velasquez Alvaro³,Kayler Liise⁴

Affiliation:

1. Rochester Institute of Technology,Department of Industrial & Systems Engineering,Rochester,New York,USA

2. University of Buffalo SUNY,Department of Industrial & Systems Engineering,Buffalo,New York,USA

3. Defense Advanced Research Projects Agency,Neuro-Symbolic AI Department,Arlington,Virginia,USA

4. University of Buffalo SUNY,Department of Surgery,Buffalo,New York,USA

Funder

Defense Advanced Research Projects Agency

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10553377/10553681/10553716.pdf?arnumber=10553716

Reference22 articles.

1. Optimizing Kidney Exchange with Transplant Chains: Theory and Reality;Dickerson

2. Clearing algorithms for barter exchange markets

3. New insights on integer-programming models for the kidney exchange problem

4. Branch-and-cut-and-price for the cardinality-constrained multi-cycle problem in kidney exchange

5. The Need for (Long) Chains in Kidney Exchange;Ashlagi,2012

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