Disease evolution prognosis based on multi-source signals and image analysis

A methodology to approach the automatic monitoring and prognosis of diseases evolution is proposed. We define a multilevel system architecture capable to process multi-source biomedical data according to a coarse-to-fine paradigm. An application regarding neuro-signals and image categorization is also considered as a case study. The proposed methodology even preliminary has shown to be a possible approach to prognosis activity, mainly if suitably integrated into a hybrid system for medical decision support.