Journal
COMPUTERS IN BIOLOGY AND MEDICINE
Volume 43, Issue 11, Pages 1783-1792Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.compbiomed.2013.07.035
Keywords
In vitro fertilization (IVF); Bayesian networks; EM algorithm; MAP estimation; Classification
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Funding
- CTI (Commission for Technology and Innovation) [9707.1 PFSL-LS]
- Swiss NSF [200020-132252]
- Hasler foundation [10030]
- Swiss National Science Foundation (SNF) [200020_132252] Funding Source: Swiss National Science Foundation (SNF)
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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.
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