ALAMEDA: Artificial Intelligence for the treatment of brain disorders


Providing personalized care and better treatments to patients suffering from major brain disorders by reducing treatment costs through the use of artificial intelligence: this is the ambitious goal of the ALAMEDA project (, funded by the European Commission under the HORIZON 2020 program1.

The three-year project started on January 2021st 31 and will end on December 2023st XNUMX.


The ALAMEDA project aims to provide personalized care and better treatments to patients suffering from major brain disorders such as Parkinson's disease, multiple sclerosis and stroke. This, with the aim of ensuring that medical interventions in the health sector are effective for the patient, but not only for them.

What we want to achieve is also the possibility of being able to "foresee" any worsening in the patient's clinical situation, so as to be able to intervene promptly to slow down the course of the disease.

Again, thanks to targeted and personalized treatments, ALAMEDA aims to lighten the burden of European health systems. To date, in the EU, the treatment of brain disorders represents one of the highest costs in the entire health system. Being able to intervene effectively is certainly an advantage.

The tools used

Among the main tools used are artificial intelligence and the management of Big Data as "predictive" tools, this is because timeliness, referring to brain diseases, is fundamental.

In fact, in most cases, when clinical symptoms occur in patients with Parkinson's disease or multiple sclerosis, the outcomes are essentially irreversible. So detecting symptoms early can make a difference in treating those with brain disorders.

Unfortunately, there is no cure for this type of disease, but slowing down its evolution means guaranteeing patients who are affected by it a better quality of life for a longer period of time.

Today the possibility of "predicting" and anticipating the treatment of brain disorder is made possible by the advances made in the field of technology that allow us to work towards paths that until a few years ago it was unthinkable to be able to beat. This is of great benefit to both patients and the healthcare system, which will be less burdened in the long run from an economic point of view.

In the case of neurological disease research, technological advances are proving particularly effective in this regard. By working on the "new" methods of Big Data Analytics e Machine Learning it is in fact able to provide clinically relevant information that can effectively implement medical recommendations, thus promoting greater efficiency and an equally greater effectiveness of treatments in a field in which experts foresee a growing shortage of specialists in the coming years. 

The problem of the shortage of health personnel is indeed global and deserves to be considered with due attention. According to the World Health Organization, by 2030 the EU will have a deficit of about 4,1 million skilled health professionals (midwives, nurses and doctors).

In terms of the overall economic and social impact, there is also another consideration: given that most neurological disorders increase with age, their burden is expected to increase in countries with aging populations, such as for example in Italy and in many European countries.

In this context, the Artificial Intelligence tools used in the health sector can give life to an important turning point, guaranteeing better management of diseases and lower treatment costs.

Future scenarios

The advanced data analysis systems will be distributed in order to continuously monitor the state of health of patients and their overall cognitive capacity and evaluate all the aspects considered fundamental for the diagnosis of brain disorders: fatigue, psychosocial state, anxiety. and depression, quality of life, and satisfaction with technology and Tele-healthcare.

Thanks to the use of Artificial Intelligence, the management of some cases will be facilitated and made more efficient even in the presence of heterogeneous and incomplete data. With this project, doctors will be able to design personalized monitoring plans with the aim of improving patient outcomes.

In addition, this will allow clinicians to have advanced tools for timely prediction of relapses to identify the most appropriate treatment, ensuring effective care for these patients over time.

Monitoring of motor function and sleep characteristics, an essential part of the ALAMEDA project, has the potential to predict the course of the disease, in particular the prediction of relapses or any worsening. All of this will be essential to improve the effectiveness of drugs and rehabilitation treatments, resulting in better care and quality of life for people with brain disorders. 

Overall, ALAMEDA will therefore bring benefits to healthcare professionals and operators, expanding the current landscape of diagnostic and monitoring tools available for clinical and healthcare practice. A project that, without a shadow of a doubt, is ambitious and because of its importance it involves eight countries (Greece, England, Italy, Romania, Norway, Luxembourg, Spain and Cyprus) for a total of 15 organizations actively on the front line. ALAMEDA, coordinated by the ICCS - Institute of Communication and Information Systems (Greece), also sees the precious collaboration of some Italian partners: EY - Advisory SPA; IMF - Foundation of the Italian Multiple Sclerosis Association; Pluribus One Srl, which within the project deals with a delicate and inherent aspect of ALAMEDA's IT security: the design of the platform to guarantee the protection and privacy of data that will be hosted, processed and shared with the scientific community.

Not an easy task that deserves a few words of in-depth analysis, given the fact that in recent years cyber attacks against European health facilities have shown a growing and worrying trend.

The protection of the ALAMEDA platform from cyber attacks and unauthorized access will start from the creation of a "Threat Model", through standard and widely used threat modeling methodologies (for example STRIDE2 or PASTA3). This will lead to the identification of specific instances and categories of potential attacks and threats to be addressed. But above all it will lead to identifying the countermeasures in terms of active protection mechanisms (security requirements to be included in the platform itself) and passive (use and implementation of proprietary software solutions of the Sardinian company such as anti-malware, firewall, web application firewall, for detect and block threats).

Another aspect related to the security of the data used and hosted by ALAMEDA concerns the full transparency (both towards recipients within the consortium and towards external stakeholders) on the measures adopted to guarantee the collection and processing of data using high standards of security and protection of privacy. .

All with the aim of making ALAMEDA not only compliant with the GDPR but also a reference case for closely related future initiatives, concerning data security in the health sector, and also favoring the exploitation and sustainability of the results achieved by the project.

Maris Matteucci, Matteo Mauri

1grant agreement No 101017558, total budget 6 million Euros.