Authors:
Vadim Peretokin
1
;
Ioannis Basdekis
2
;
Ioannis Kouris
3
;
Jonatan Maggesi
4
;
Mario Sicuranza
5
;
Qiqi Su
6
;
Alberto Acebes
7
;
Anca Bucur
1
;
Vinod Jaswanth Roy Mukkala
4
;
Konstantin Pozdniakov
6
;
Christos Kloukinas
6
;
Dimitrios D. Koutsouris
3
;
Elefteria Iliadou
8
;
Ioannis Leontsinis
9
;
Luigi Gallo
5
;
Giuseppe De Pietro
5
and
George Spanoudakis
2
Affiliations:
1
Philips Research, Eindhoven, The Netherlands
;
2
SPHYNX Technology Solutions AG, Zug, CH, Switzerland
;
3
Biomedical Engineering Laboratory, School of Electrical and Computer Engineering, National Technical University of Athens, Athens, Greece
;
4
Computer Science Department, Università degli Studi di Milano, Milan, Italy
;
5
Institute for High-Performance Computing and Networking, National Research Council of Italy, ICAR - CNR, Naples, Italy
;
6
Department of Computer Science, City, University of London, London, U.K.
;
7
Atos Research and Innovation. Madrid, Spain 81st Otolaryngology University Department, National and Kapodistrian University of Athens, Athens, Greece 91st Cardiology Clinic, Medical school, National and Kapodistrian University of Athens, Athens Greece
;
8
1st Otolaryngology University Department, National and Kapodistrian University of Athens, Athens, Greece
;
9
1st Cardiology Clinic, Medical school, National and Kapodistrian University of Athens, Athens Greece
Keyword(s):
Cloud, AI, Semantic Interoperability, HL7 FHIR, Healthcare, GDPR, Evidence-based, Ageing, Hearing Loss, Cardiovascular Disease, Balance Disorder.
Abstract:
This paper describes a cloud-based platform that offers evidence-based, personalised interventions powered by Artificial Intelligence to help support efficient remote monitoring and clinician-driven guidance to people over 65 who suffer or are at risk of hearing loss, cardiovascular diseases, cognitive impairments, balance disorders, and mental health issues. This platform has been developed within the SMART-BEAR integrated project to power its large-scale clinical pilots and comprises a standards-based data harmonisation and management layer, a security component, a Big Data Analytics system, a Clinical Decision Support tool, and a dashboard component for efficient data collection across the pilot sites.