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首页> 外文期刊>International journal of medical informatics >Electre Tri-g, a multiple criteria decision aiding sorting model applied to assisted reproduction
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Electre Tri-g, a multiple criteria decision aiding sorting model applied to assisted reproduction

机译:Electre Tri-g,一种用于辅助复制的多标准决策辅助分类模型

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摘要

Objective: The aim of this paper is to apply an informatics tool for dealing with a medical decision aiding problem to help infertile couples to become parents, when using assisted reproduction. Methods: A multiple criteria decision aiding method for sorting or ordinal classification problems, called Electre Tri-C, was chosen in order to assign each couple to an embryo-transfer category. The set of categories puts in evidence a way for increasing the single pregnancy rate, while minimizing multiple pregnancies. The decision aiding sorting model was co-constructed through an interaction process between the decision aiding analysts and the medical experts. Results: According to the sample used in this study, the Electre Tri-C method provides a unique category in 86% of the cases and it achieves a sorting accuracy of 61%. Retrospectively, the medical experts do agree that some of their judgments concerning the number of embryos to transfer back to the uterus of the woman could be different according to these results. The current ART methodology achieves a single pregnancy rate of 47% and a twin pregnancy rate of 14%. Thus, this informatics tools may play an important role for supporting ART medical decisions, aiming to increase the single pregnancy rate, while minimizing multiple pregnancies. Limitations: Building the set of criteria comprises a part of arbitrariness and imperfect knowledge, which require time and expertise to be reu0001ned. Among them, three criteria are modeled by means of a holistic classification procedure by the medical experts.
机译:目的:本文的目的是应用信息学工具来处理医学决策辅助问题,以帮助不育夫妇在使用辅助生殖时成为父母。方法:选择一种用于分类或顺序分类问题的多准则决策辅助方法,称为Electre Tri-C,以将每对夫妇分配到胚胎移植类别。这组类别为增加单胎妊娠率,同时最大程度地减少多胎妊娠提供了证据。决策辅助分类模型是通过决策辅助分析人员和医学专家之间的交互过程共同构建的。结果:根据本研究中使用的样本,Electre Tri-C方法在86%的案例中提供了独特的类别,并且实现了61%的分类精度。追溯地,医学专家确实同意,根据这些结果,他们对转移回女性子宫的胚胎数量的某些判断可能会有所不同。当前的抗逆转录病毒治疗方法单胎妊娠率为47%,双胎妊娠率为14%。因此,这种信息学工具可能在支持抗逆转录病毒疗法医疗决策中发挥重要作用,旨在提高单胎妊娠率,同时最大程度地减少多胎妊娠。局限性:建立标准集包括任意性和不完善的知识,这需要时间和专业知识来重新认识。其中,三个标准是由医学专家通过整体分类程序建模的。

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