Decision Algorithm for Heuristic Donor-Recipient Matching
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Date
2017-06-01
Authors
Namatevs, Ivars
Aleksejeva, Ludmila
ORCID
Advisor
Referee
Mark
Journal Title
Journal ISSN
Volume Title
Publisher
Institute of Automation and Computer Science, Brno University of Technology
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Abstract
This paper introduces the application of artificial intelligence paradigm towards precision medicine in renal transplantation. The match of the optimal donor-recipient pair in kidney transplantation in Latvian Transplant Centre (LTC) has been constrained by the lack of prediction models and algorithms. Consequently, LTC seeks for practical intelligent computing solution to assist the clinical setting decision-makers during their search for the optimal donor-recipient match. Therefore, by optimizing both the donor and recipient profiles, prioritizing importance of the features, and based on greedy algorithm approach, advanced decision algorithm has been created. The strength of proposed algorithm lies in identification of suitable donors for a specific recipient based on evaluation of criteria by points principle. Experimental study demonstrates that the decision algorithm for heuristic donor-recipient matching integrated in machine learning approach improves the ability of optimal allocation of renal in LTC. It is an important step towards personalized medicine in clinical settings.
Description
Citation
Mendel. 2017 vol. 23, č. 1, s. 33-40. ISSN 1803-3814
https://mendel-journal.org/index.php/mendel/article/view/49
https://mendel-journal.org/index.php/mendel/article/view/49
Document type
Peer-reviewed
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Language of document
en