A Bayesian network model for predicting the outcome of in vitro fertilization
Giorgio Corani, M. Cristina Magli, Alessandro Giusti, Luca Gianaroli, Luca Maria Gambardella · 2012
We present a Bayesian network model for predicting the outcome of in-vitro fertilization (IVF). The problem is characterized by a peculiar missingness process, and we propose a simple but effective averaging approach which improves parameter estimates compared to the traditional MAP estimation. The model can provide relevant insights to IVF experts. 1