Biomedical Data Science

Biomedical Data Science

Data Science and Big Data at ISGlobal
Photo: Gerd Altmann / Pixabay

Over time, valuable information on drug biological activity and clinical data from patients accumulates in corporate and public archives. Such data sets, as a whole, may be sufficient to provide new therapeutic leads and the new data analytics technologies are now mature to accelerate drug discovery and development.

In parallel, with the advent of digital health, phones, tablets and wearables are becoming an integral part of our life, monitoring our daily intake, pulse, pressure, sleep, and all the way from our breathing to our behavioural patterns. The COVID-19 pandemic has made the world aware of the potential of telecommunication, reshaping the way we think about health and human relationships.

The Biomedical Data Science Team at ISGlobal seeks to develop and translate data analytics methods imported from other disciplines such as physics, computer vision and machine learning. We have an interventional approach to research as we focus on methods that aim to both explain and predict biomedical phenomena delivering social impact.

While the application of artificial neural networks to study large datasets is becoming an established classification and prediction tool, often this technology lacks interpretability required for biomedical applications and clinical implementation. Our lab focuses on the development of analytical tools that provide interpretable results (Explainable Artificial Intelligence), providing new insights into biological drivers of disease and the discovery of new biomarkers that will allow the early diagnosis of conditions leading to effective interventions and improved health outcomes.

Primary Research Areas

  1. Medical and microscopy image analysis and classification to support clinical-decision in neurodegeneration, ageing and cancer.
  2. Heterogeneous data integration and Electronic Medical Records (EHR) informatics for the automated risk assessment of population health outcomes.
  3. Explainable Artificial Intelligence (AI) applications in the biomedical field. Finding new biomarkers for the early detection and management of non-communicable diseases.

The Biomedical Data Science group is part of the ISGlobal Severo Ochoa (SO) programme which supports interdisciplinary science to improve the understanding of complex health problems. Our team contributes to ISGlobal programs with advanced analytics and machine learning, as well as engage in external partnerships and collaborations.

Topics of Collaboration with other ISGlobal Teams

  • Characterizing the social and health impact of COVID-19.
  • The Human Signature: Exposome, omic and socio-demographic data integration to predict and intervene health-outcomes.
  • Immunology: Understanding drivers of vaccine-induced immune response across infectious diseases.

Our Team

Head of the group

ISGlobal Team