The challenges for IT industries to analyse such an enormous amount of data and turn all this into actionable medical sights will grow significantly, which triggers the demand for Big Data technologies, in order to improve the overall efficiency and quality of care delivery.

In the Digital Health theme, GATE research explores the following research challenges:

  • Semantic technologies. Use of validated and semantic sources for data interpretation according to human standards, analysis for human needs and interpretation.
  • Large-scale data analysis and training of supervised/unsupervised models. Complex data analytics, knowledge extraction and representation (transformation and alignment of unstructured data with fact repositories, interpretation of data against semantic sources) to cluster different sociodemographic groups and discover hidden patterns which can be used to develop better and personalized drugs.
  • Digital twin with human-data interaction. Supporting human engagement and combining advanced descriptive and prescriptive analytical methods to advise the diagnosis, monitoring and treatment of patients.
  • Probabilistic and dynamic models enabling analytics on a  vast amount of data to support preventive medicine and early discovery of potential diseases in patients.
  • Image analysis and multimodal data analysis. Use of multi-modal data for complex data analytics across data sources and interpretation of complex data types.

Our pilot project in the field of Digital Health is related to the use of artificial intelligence as a tool for the diagnosis and treatment of cognitive diseases with a focus on Alzheimer’s disease.

The main goal of the project is to develop methods, algorithms and tools that support risk prediction, diagnosis and treatment of cognitive diseases and in particular Alzheimer’s disease. The expected results from a research point of view are related to finding new classifications of patients with Alzheimer’s disease, developing models for predicting a cognitive decline, identifying structural variants of DNA in patients with Alzheimer’s disease, defining the necessary sample sizes in the planning of RNA research, development of optimal methods for finding genes that could be associated with Alzheimer’s disease, as well as methods for filling in missing data. Practitioners are expected to develop tools to facilitate the diagnosis, monitoring and treatment of patients with Alzheimer’s disease or people predisposed to it.
The developed methods, algorithms and tools can subsequently be integrated into an omix analytical model.

The project is implemented through successful cooperation with leading universities at the international level such as Yale, Oxford, Stanford and Chalmers, as well as with the support of medical professionals in Bulgaria.



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 the 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.