A Bayesian network model for predicting pregnancy after in vitro fertilization

被引：31

作者：

Corani, G. ^{[1
]}

Magli, C. ^{[2
]}

Giusti, A. ^{[1
]}

Gianaroli, L. ^{[2
]}

Garnbardella, L. M. ^{[1
]}

机构：

[1] Ist Dalle Molle Studi Intelligenza Artificiale ID, Manno, Switzerland

[2] Int Inst Reprod Med IIRM, Lugano, Switzerland

来源：

COMPUTERS IN BIOLOGY AND MEDICINE | 2013年 / 43卷 / 11期

基金：

瑞士国家科学基金会;

关键词：

In vitro fertilization (IVF); Bayesian networks; EM algorithm; MAP estimation; Classification; SINGLE EMBRYO-TRANSFER; MORPHOLOGY; SELECTION; BENEFITS; OUTCOMES; OOCYTE; ZYGOTE; RISKS; SCORE;

D O I：

10.1016/j.compbiomed.2013.07.035

中图分类号：

Q [生物科学];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

We present a Bayesian network model for predicting the outcome of in vitro fertilization (IVF). The problem is characterized by a particular missingness process; we propose a simple but effective averaging approach which improves parameter estimates compared to the traditional MAP estimation. We present results with generated data and the analysis of a real data set. Moreover, we assess by means of a simulation study the effectiveness of the model in supporting the selection of the embryos to be transferred. (C) 2013 Elsevier Ltd. All rights reserved.

引用

页码：1783 / 1792

页数：10

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