MINHO Ageing Data Lake: From data to evidence generation

In our Digital Era, it is crucial the establishment of innovative strategies that work to bolster health promotion, studies and/or programs designed to reduce the loss of independence in the older years, and the full utilization of already existing data, in a concerted effort to characterize individual/population health, anticipate health events, and evaluate public health interventions, public policies and others. Proper quality of life can be aided using available digital technologies and capabilities, be it via direct or indirect use and application. Regarding the former, digital literacy goes “hand in hand” with health and health literacy and promotion, while, for the latter, the use of digital databases for the aggregation, retrieval, and/or analysis of information and/or data is a must.

The Project aims to: (i) create primary or secondary digital repositories (from ageing-related data collected from population-based studies conducted by the Team, public data and established collaborations); and (ii) improve and consolidate digital tools that aggregate into a developing digital platform that permits data to be structured and to facilitate its analysis and the promotion of clinical studies to all stakeholders. The strategies employed will allow to: (i) contribute to understanding the pathophysiological mechanisms involved in ageing-related processes and its determinants; (ii) monitor throughout life, or in particular physiological or pathological contexts, with the aid of digital tools (e.g. sensors); (iii) provide crucial practical clues to digital literacy and on how to reach individuals in the community; (iv) allow self-empowerment on maintaining life quality.

Funding Agency

PT2020; European Health Data & Evidence Network

Project Reference

“Digitalizar a investigação clínica” (04/SAICT/2020); “EDHEN – Clinical Research Data Partners European” (3rd Open Call EDHEN)

Project Members

Main Project Outcomes

S. Queirós, “Right ventricular segmentation in multi-view cardiac MRI using a unified U-net model”, in E. Puyol Antón et al. (eds) Statistical Atlases and Computational Models of the Heart. Multi-Disease, Multi-View, and Multi-Center Right Ventricular Segmentation in Cardiac MRI Challenge. STACOM 2021. Lecture Notes in Computer Science, vol 13131, pp. 287-295, Springer, Cham, 2022.

“Best Paper Award in the M&Ms-2 Challenge”, by M&Ms2 Challenge organizers and the Medical Image Computing and Computer Assisted Intervention (MICCAI) Society.

Main Project Outcomes

Ongoing project