AI-empowered m-health systems for Personalised Services and Digital Phenotyping

Health services personalization and early risk prediction represent the main research challenges in m-health systems, which can be achieved through the use of AI algorithms and tools applied to physiological and behavioural data collected by wearables and IoT devices in real-world settings. In this paper we present a summary of the results we obtained in our research activities in this area and future works, with particular attention to AI-empowered m-health systems as support for personalised rehabilitation services and malnutrition risk assessment, mobile sensing data analysis for disease detection and the identification of new health and behavioural markers that can support remote patient monitoring and the clinical practice