학술논문
iHELP: Personalised Health Monitoring and Decision Support Based on Artificial Intelligence and Holistic Health Records
Document Type
Conference
Author
Manias, George; Op Den Akker, Harm; Azqueta, Ainhoa; Burgos, Diego; Capocchiano, Nikola Dino; Crespo, Borja Llobell; Dalianis, Athanasios; Damiani, Andrea; Filipov, Krasimir; Giotis, Giorgos; Kalogerini, Maritini; Kostadinov, Rostislav; Kranas, Pavlos; Kyriazis, Dimosthenis; Lophatananon, Artitaya; Malwade, Shwetambara; Marinos, George; Melillo, Fabio; Mas, Vicent Moncho; Muir, Kenneth; Nieroda, Marzena; De Nigro, Antonio; Pandolfo, Claudia; Patino-Martinez, Marta; Picioroaga, Florin; Pnevmatikakis, Aristodemos; Syed-Abdul, Shabbir; Tomson, Tanja; Vicheva, Dilyana; Wajid, Usman
Source
2021 IEEE Symposium on Computers and Communications (ISCC) Computers and Communications (ISCC), 2021 IEEE Symposium on. :1-8 Sep, 2021
Subject
Language
ISSN
2642-7389
Abstract
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 share 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 data-driven pathways where awareness, care and decision support is provided based on person-centric early risk prediction, prevention and intervention measures.