  It is proposed to investigate the onset of a disease D, based on several risk
factors., with a specific interest in Alzheimer occurrence. For that purpose,
two classes of techniques are available, whose properties are quite different
in terms of interpretation, which is the focus of this paper: classical
statistics based on probabilistic models and artificial intelligence (mainly
neural networks) based on optimization algorithms. Both methods are good at
prediction, with a preference for neural networks when the dimension of the
potential predictors is high. But the advantage of the classical statistics is
cognitive : the role of each factor is generally summarized in the value of a
coefficient which is highly positive for a harmful factor, close to 0 for an
irrelevant one, and highly negative for a beneficial one.
