Towards an Intelligence system to support Diseases' Diagnoses and improve Health treatments

E-health is becoming more and more a reality, thanks to the increase of IoT health devices and to the availability of new technologies, algorithms and software, such as Semantics, Machine and Deep Learning. Systems are being developed to support doctors in making diagnoses, starting from data collected from sensors directly connected to the patients. This paper describes the preliminary steps towards the realisation of a platform for specialised doctors, capable of supporting diagnosis, by analysing the patients' symptoms, seen as an input to the system, and to recognise the possible diseases. In particular, we start by analysing semantic technologies as a means to describe sensors' outputs and to define rules that determine the diagnosis. To this end it is necessary to create or identify a support ontology used to describe the patients' symptoms, and then to define rules to identify the correct disease, in order to build a rule based expert system. In particular, this paper focuses on the identification and eventual modifications applied to existing disease ontologies.