Brain disease models using multivariate causality.
People are not all equal when it comes to conditions such as mental illness, since there are a number of factors which are directly or indirectly related to the symptoms and disease progression. Therefore, it is crucial that we create a model which takes all of those factors into account. Now this is possible due to the availability of large scale data and the power of multivariate approaches for explaining individual differences. During this study, we hypothesized that these data could be summarized into a few components that are age and gender dependent, based on the few components, we could develop causal brain health models.