GATE aims to contribute via Innovations, Big Data analytics, algorithms, AI, ML, DL and Digital Transformation to Long-life healthy living through all its phases: Prevention, Diagnosis, Treatment and Home Care.

We started from TM’s most complex and significant part, namely, studying the human brain and related diseases, called Translational Neuroscience [TN], which expands the understanding of brain structure, function and disease and translates this knowledge into clinical applications and novel therapies for nervous system disorders. TN deals with Neurodevelopmental and Neurodegenerative disorders.

Neurodevelopmental disorders are disorders such as epilepsy, autism spectrum disorders (ASD), learning disabilities, and certain neuromuscular disorders. TN research is focused on elucidating the cause of neurodevelopmental disorders, whether genetic, environmental, or a combination, and tactics for prevention and Treatment if possible.

Neurodegenerative disorders result from neuronal loss of function over time, leading to cell death. For example, Alzheimer’s disease, Parkinson’s disease, etc. TN research focuses on investigating the mechanisms for these disorders and the means of drug delivery.

Methods, Data, Temporal Structures and Models

Our methodology includes medical imaging, Data structures, AI models, and analytical & therapeutic techniques like Electrophysiology, Neuroimaging, Gene therapy and Stem cells, Vital signs and Behaviour, Brain networks, Dynamic models, etc. We plan to use computational models, multiscale complex processes, and the dynamics of complex networks. Our concept is to place the models at the centre. Thus, the dynamical models, AI and learning techniques, and network dynamics could bind all the different modalities and scales into a powerful R&D tool. The expected results are entirely personalised and, at the same time, give a complete picture of the specific patient’s position in the neurological disease spectrum as a whole.

Targeted R&D directions

Direction 1. Alzheimer’s disease. Alzheimer’s disease continues to be an active direction in GATE’s R&D plans. To establish scientific research continuation, we plan to enrich the toolbox of necessary conditions for early disease diagnosis and expand it to similar diseases and other dementia types.

Direction 2. Remote sensing real-time patient monitoring and alerting for hazardous events. The goal is to build a real-time system, using remote optical sensors, which follows and protects the patient by alerting for Life signs disruption or lethal syndromes detection like SUDEP, SIDS, Central Apnea, etc.

Direction 3. Multi-stable autonomous neuro-dynamics. The goal is to build a novel modelling framework of autonomous systems using physiologically motivated nonlinear multi-stable models with physiologically informed parameter choice.

Direction 4. Virtual Patient. Brain-like computing architectures for clinical diagnostic and surveillance purposes. The system can address clinical problems related to system deficits, behavioural issues and other pathological conditions, effectively providing a “virtual patient” simulation platform for testing new corrective or control approaches.

Direction 5. Drug response prediction. We are not planning to approach the problem on a molecular and genetic level (micro-scale) like in precision medicine studies but on the level of large-scale measurements, models and network dynamics.

Synergy and Collaboration

Digital Health is not a stand-alone GATE’s direction. The synergy between Digital Health and the rest of the GATE’s strategic application themes is shown in:

  1. a) the building blocks of reinforced, autonomous learning used for real-time personalisation, monitoring of public places for real-time surveillance use, detecting and alerting for different types of behaviour, etc.;
  2. b) the overlap of the surrounding methodologies and application areas, namely: Big Data, AI, System’s Analysis, Innovative algorithms, Informatics, Mathematics, Graph Theory, Life Sciences, Physical Sciences, Computer Vision, Data Science, ML, Medical Imaging, Biomarkers, Connectivity Patterns, etc.

The development of GATE’s projects for Digital Health is carried out in cooperation with leading world universities, hospitals, scientific and public organizations.



Opportunities and Prospects in Digital Health” session, GATE Big Data and Artificial Intelligence Forum, December 10th, 2020

The goal of the “Opportunities and Prospects in Digital Health” session of the GATE Big Data and Artificial Intelligence Forum was to discuss various elements of the process of utilizing, analyzing and gaining insight from Big Data in the Digital Health domain. The emphasis was on collaboration between different stakeholders — biomedical researchers, hospitals and medical doctors, data scientists, biostatisticians and bioinformaticians, pharmaceutical companies, etc. Consequently, the panellists were representatives of different fields within the Digital Health domain.

The keynote speaker of the session was Prof. Dr Milan Petkovic, Vice president of BDVA and the Data Science department head at Philips. Having a unique insight as part of the industry, academia and the ecosystem, his presentation underlined the current state and the perspectives in the Digital Health domain. He emphasized the trends in healthcare that are the main driver for innovation; the new reality in digitalization and telemedicine; the technical changes, such as the growth of health data; also the collaboration between different entities by utilizing not only analytical methods but also specific domain knowledge. In addition, Prof. Petkovic showed several specific use cases, including AI-enabled solutions and described several EU initiatives in the field.

The session moderator Dr Dean Palejev, Digital Health Research Lead at GATE, presented some of the institute’s main projects in the domain. These include developing AI and ML-based methods for analyzing Next Generation Sequencing data and are implemented in collaboration with researchers from the US and Sweden.  The development of NGS over the past decade made this type of data one of the richest sources of genomic data and, together with the advancements in the Big Data, AI and ML analytical methodology opened vast research possibilities in the field.

The vice-chair of the Board of Digital Health and Innovations Cluster Bulgaria, Dr Rosen Dimitrov presented his organization and its members representing various companies and organizations in the field. He emphasized their vision for creating a data-driven ecosystem in the Digital Health domain in the country. He also described the services provided by his organization including access to information, mentoring and support and importantly, providing a platform for collaboration between different types of stakeholders in the Digital Health ecosystem.

The next panellist was Dr Fredrik Johansson, Assistant Professor at the Chalmers University of Technology who outlined some advanced initiatives at his university. One such example is the Chalmers AI Research Centre (CHAIR) that also includes external collaborators from the industry and the public sector and Dr Johansson described in more detail their collaboration with Sahlgrenska University Hospital. He also mentioned his work on predicting the cognitive decline of Alzheimer’s patients, part of which is a collaboration with GATE.

As a medical practitioner Dr Todor Kunchev, a neurologist at University hospital Sofiamed shared his thoughts on the opportunities of digitalization of dementia management prompted by the increased number of cases due to increased life expectancy. He presented an example of such a system, the CogniTwin project on which he is partnering with GATE. The project was designed to create a digital twin model for the exploration of behavioural changes in patients with proven cognitive disorders and its implementation utilizes modern Big Data and AI technologies.

At the end of the session, the panellists discussed the important recent advancements in the field from their point of view, as well as their predictions for the next few years. As expected it became apparent that different technologies and trends are important for the different participants in the ecosystem, and that the synergy of rapidly developed technologies is the leading force of innovation in the Digital Health domain.