In recent years, new opportunities for improved and personalized healthcare and prevention have emerged, thanks to the progress made in the design of innovative health risk prediction systems and in the development of relevant effective intervention tools. According to the World Health Organization[1], digital transformation in the health sector is an urgent need and challenge, due to the global problem of the shortage of the healthcare workforce. It is noteworthy that this shortage will reach about 4.1 million skilled health professionals (midwives, nurses and doctors) by 2030 in the European Union.
In the field of brain disease research, technological advances have proven to be particularly effective. Big Data Analytics and Machine Learning Algorithms are able to provide clinically actionable information, which, combined with physician recommendations, can contribute to effective treatments. This is particularly important because neurological disorders are increasingly burdened with disability-adjusted life-years (DALYs – the number of years lost due to ill health, disability or premature death), ranking third after cancer and cardiovascular disease.[2]
Although continuous progress has been observed in understanding the value of certain measures and treatment programs, appropriate evaluation of the impact of rehabilitation in patients with PMSS remains an extremely important challenge, in order to improve health system capacity and enable the development of new personalized treatment options.
“The ALAMEDA Consortium consists of technical and medical experts who collaborate to review and radically change the ways of treating patients with PMSS, with the ultimate goal of improving their quality of life,” said Dr. Konstantinos Demestichas, ALAMEDA coordinator and Research and Development Project Manager at the Research University Institute of Communication and Computer Systems (RICCS).
The application of digital technologies to specific healthcare and chronic disease topics has the potential to generate rich diagnostic data. Artificial intelligence and big data management methods are applied to this data to extract useful information that can support intelligent personalized healthcare guidance, taking into account existing practices and medical protocols. In the coming years, ongoing research is expected to bring unprecedented developments in the health sector, through risk prediction tools and improved understanding of the diseases under study.
The use of artificial intelligence methods (Big Data Analytics, Machine Learning and Deep Learning) as predictive tools is particularly important for brain diseases, as, in many cases, by the time all clinical symptoms are manifested and specialists can make a definitive diagnosis, the results are essentially irreversible. In this light, better tools are needed to detect early signs of a brain disease. With the advancement of the field of machine intelligence, very powerful algorithms have been developed that detect hidden patterns in data, identify anomalies in “expected” patterns and connect similar patients/diseases/drugs based on their common characteristics. In the healthcare sector, deep learning is expected to play a key role, paving the way for radical changes in Clinical Decision Support Systems (CDSSs), diagnosis formulation and treatment selection. These changes are further enhanced by recent progress in the digitization of medical records, including medical reports, image or sensor data.
We have no choice but to pursue this further progress in order to improve the quality of life of patients and their caregivers, and ALAMEDA is ready to make just that happen!
PROJECT DETAILS
• Project acronym: ALAMEDA
• Start date: January 01, 2021
• Duration: 36 months
• Budget: €6,000,000
• Coordinator: Research University Institute of Communications and Computer Systems (Greece)
The ALAMEDA consortium consists of 15 partners in 8 different European countries: University Research Institute of Communication and Computer Systems (URICS), National and Kapodistrian University of Athens (NKUA), National Center for Research and Technological Development (CERTH) and Digital Technologies and Innovation Projects Private Equity Company (Enora Innovation – ENO) from GREECE, Wellics Ltd from UNITED KINGDOM, EY Advisory SPA, Fondazione Italiana Sclerosi Multipla Onlus (FISM) and Pluribus One Srl from ITALY, Universitatea Polithnica Din Bucuresti and Spitalul Universitar De Urgenta Bucuresti from ROMANIA, Norges Teknisk-Naturvitenskapelige Universitet (NTNU) from NORWAY, Unisystems Luxemburg Sarl from LUXEMBOURG, Wise Angle Consulting SL from SPAIN, Catalink Limited and University of Nicosia from CYPRUS.
DISCLAIMER: This press release reflects the views only of the authors, and the European Union is not responsible for any use that may be made of the information contained therein.
[1] World Health Organization (2016), Global strategy on human resources for health: workforce 2030, Geneva.
[2] Deuschl G, et al, The burden of neurological diseases in Europe: an analysis for the Global Burden of Disease Study 2017, Lancet Public Health 2020; 5: e551–67.
