Please use this identifier to cite or link to this item: https://hdl.handle.net/10216/74016
Author(s): Francisco Reinaldo
Carlos Fernandes
Md. Anishur Rahman
Andreia Malucelli
Rui Camacho
Title: Assessing the eligibility of kidney transplant donors
Issue Date: 2009
Abstract: Organ transplantation is a highly complex decision processthat requires expert decisions. The major problem in a transplantationprocedure is the possibility of the receiver's immune system attack anddestroy the transplanted tissue. It is therefore of capital importance tond a donor with the highest possible compatibility with the receiver, andthus reduce rejection. Finding a good donor is not a straightforward taskbecause a complex network of relations exists between the immunologicaland the clinical variables that inuence the receiver's acceptance of thetransplanted organ. Currently the process of analyzing these variablesinvolves a careful study by the clinical transplant team. The number andcomplexity of the relations between variables make the manual processvery slow. In this paper we propose and compare two Machine Learningalgorithms that might help the transplant team in improving and speedingup their decisions. We achieve that objective by analyzing past real casesand constructing models as set of rules. Such models are accurate andunderstandable by experts.
Subject: Ciência de computadores, Ciências Médicas, Ciências da computação e da informação
Computer science, Medical sciences, Computer and information sciences
Scientific areas: Ciências exactas e naturais::Ciências da computação e da informação
Natural sciences::Computer and information sciences
URI: https://repositorio-aberto.up.pt/handle/10216/74016
Source: Machine Learning and Data Mining in Pattern Recognition
Document Type: Artigo em Livro de Atas de Conferência Internacional
Rights: openAccess
License: https://creativecommons.org/licenses/by-nc/4.0/
Appears in Collections:FEUP - Artigo em Livro de Atas de Conferência Internacional

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