“BioEngineering for Precision Medicine”
Chronic diseases, otherwise known as noncommunicable diseases (NCDs), represent the major global health problem of the 21st century. NCDs kill 41 million people each year, equivalent to 71% of all deaths globally, and threaten progress towards the 2030 Agenda for Sustainable Development, which includes a target of reducing premature deaths from NCDs by one-third by 2030. The major chronic diseases listed by World Health Organization (WHO) are cardiovascular diseases, cancer, chronic respiratory diseases, diabetes mellitus (DM) and neurodegenerative disorders.
Monitoring and maintaining normal values for key health metrics play a primary role in reducing chronic disease risk. As such, powerful mechanisms based on prevention to combat the chronic disease crisis are currently present and continue to evolve. However, a new healthcare delivery model is needed to implement these mechanisms effectively.
Our research in this area aims to make possible the precision medicine of the future by bringing the computation closer to the edge, and proposing an optimal computing architecture that leverages the limits of Cloud-computing. As a consequence, our edge computing architecture will bring the precision medicine to a broader population.
Our work focuses on the following research lines:
- To develop real-time prediction techniques for chronic symptomatic diseases in an ambulatory environment. We design and validate wearable monitoring approaches, we develop signal and data processing techniques, and we implement learning-based prediction algorithms for
- Migraine (in collaboration with Hospital Universitario de la Princesa)
- Neuropathic pain in cancer (in collaboration with Hospital HM Sanchinarro)
- To develop computer aided diagnosis tools based on advanced machine learning techniques for
- Stroke (in collaboration with Hospital Universitario de la Princesa)
- Aphasia and other dementias (in collaboration with University of Extremadura – , and Hospital Clinico San Carlos)
- To design computing framework for the automatic analysis of heterogeneous data sources and knowledge extraction from genomics and other “omics” for
- Rare tumors (in collaboration with Hospital HM Sanchinarro, CIMA , and CNIO).
- To perform computing techniques for advanced personalization of therapies in chronic diseases like
- Botulinum toxin in chronic migraine (in collaboration with Hospital Universitario de la Princesa, and Hospital Clinico Universitario de Valladolid)
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