iHELP: Personalised Health Monitoring and Decision Support Based on Artificial Intelligence and Holistic Health Records

George Manias, Harm Op Den Akker, Ainhoa Azqueta, Diego Burgos, Nikola Dino Capocchiano, Borja Llobell Crespo, Athanasios Dalianis, Andrea Damiani, Krasimir Filipov, Giorgos Giotis, Maritini Kalogerini, Rostislav Kostadinov (+18 others)
2021 2021 IEEE Symposium on Computers and Communications (ISCC)  
Scientific and clinical research have advanced the ability of healthcare professionals to more precisely define diseases and classify patients into different groups based on their likelihood of responding to a given treatment, and on their future risks. However, a significant gap remains between the delivery of stratified healthcare and personalization. The latter implies solutions that seek to treat each citizen as a truly unique individual, as opposed to a member of a group with whom they
more » ... e common risks or health-related characteristics. Personalisation also implies an approach that takes into account personal characteristics and conditions of individuals. This paper investigates how these desirable attributes can be developed and introduces a holistic environment, the iHELP, that incorporates big data management and Artificial Intelligence (AI) approaches to enable the realization of datadriven pathways where awareness, care and decision support is provided based on person-centric early risk prediction, prevention and intervention measures.
doi:10.1109/iscc53001.2021.9631475 fatcat:nifyvy4dczcd5i7rfh6suazdc4