Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
10351677 | Computers in Biology and Medicine | 2013 | 9 Pages |
Abstract
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.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Science Applications
Authors
G. Corani, C. Magli, A. Giusti, L. Gianaroli, L.M. Gambardella,