Predictive AI Models for the Personalized Medicine

Abstract

Innovative information systems which enable personalized medicine are presented. The designed decision support systems are expected to infer with an excellent level of accuracy the outcome of a therapeutic intervention through the analysis of biometric, genetic and environmental data. They are also capable to motivate their predictions according to a dynamic knowledge base, which is kept updated with new analysed cases. These systems can be used by researchers to identify useful correlations between biometric, genetic and environmental data with potential risks and benefits of certain therapeutic choices. They can also be used by the patients to choose the most appropriate therapeutic intervention according to their needs and expectations. In other words the presented decision support tools can realize the vision of the predictive, preventive, personalized and participatory (P4) medicine pursued by the systemic medicine.