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 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.