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ALAMEDA: Early Diagnosis and Treatment of Stroke Diseases through Smart Technological Interventions

In recent years, new opportunities for improved and personalized health care, as well as prevention, have emerged, thanks to the progress made in the design of innovative health risk management systems and the development of relevant effective intervention tools. According to the World Health Organization[1], the digital transformation in the health sector is an urgent need and challenge, due to the global problem of lack of healthcare workforce. It is typical that this shortage will reach about 4,1 million qualified health professionals (midwives, nurses and doctors) by 2030 in the European Union.

In the field of research on brain diseases, technological developments have proven to be particularly effective. Large Scale Data Analysis methods and Machine Learning Algorithms are able to provide clinically useful information, which, in combination with physicians' recommendations, can contribute to effective treatments. This is especially important because neurological disorders are increasingly associated with disability-adjusted life-years (DALYs) - this is 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 made in understanding the value of certain measures and treatment programs, Proper rehabilitation impact assessment in patients with PMSS remains an extremely important challenge, so as to improve the capacity of the health system and enable the development of new personalized treatment options.

"The ALAMEDA Consortium consists of technicians and medical experts who work together to review and radically change the way patients with PMSS are treated, with the ultimate goal of improving their quality of life ", stated Dr. Konstantinos Demestihas, coordinator of ALAMEDA and Research and Development Project Manager at the Research University Institute of Communication and Computer Systems (EPISEV).

The application of digital technologies in specific issues of health care and chronic diseases has the potential to create rich diagnostic data. In this data, methods of artificial intelligence and big data management are applied with the aim of extracting useful information, which can support intelligent personalized guidance in the field of healthcare, taking into account existing practices and medical protocols. In the coming years, continuous research is expected to bring about unprecedented developments in the field of health, through tools for risk prediction and improved understanding of the diseases under study.

The use of artificial intelligence methods (Big Data Analysis, Engineering and In-Depth Learning) as predictive tools is especially important for brain diseases, as, in many cases, until all clinical symptoms are present and specialists can make a definitive diagnosis, the results are virtually irreversible. In this light, better tools are needed to detect the 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 the data, detect abnormalities in "expected" patterns and link similar patients / diseases / drugs based on their common features. In the field of health, deep learning is expected to play a key role, paving the way for radical changes in Clinical Decision Support Systems (CDSSs), diagnosis and treatment choices. These changes are further enhanced by recent advances in the digitization of medical records, including medical reports, image data, or sensors.

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 do just that!


• Project acronym: ALAMEDA

• Start date: 01 January 2021

• Duration: 36 months

• Budget: € 6.000.000

• Coordinator: University Research Institute of Communication and Computer Systems (Greece)

The ALAMEDA consortium consists of 15 partners in 8 different European countries: Research University Institute of Communication and Computer Systems (EPISEV), National and Kapodistrian University of Athens (EKPA), National Center for Research and Technological Development (EKETA) Private Capital 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) by NORWAY, Unisystems Luxemburg Sarl from LUXEMBOURG, Wise Angle Consulting SL from SPAIN, Catalink Limited and University of Nicosia from CYPRUS.

DENIAL OF RESPONSIBILITY: This press release expresses solely the views of the authors and The European Union is not responsible for any use which 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.

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