Time Series Geo-Referenced Health Care Analytics for Dementia

This scoping project focuses on cognitive health in ageing, using data from the TUDA study (Trinity, Ulster, Department of Agriculture) linking nutrition, biomarker, lifestyle, health, and geo-referenced data with cognition as people age.


  Project Funders

  • HSCB eHealth Directorate
  • eHealth and Data Analytics Dementia Pathfinder Programme

  Funding Amount

£7451

About the Project

This scoping project focuses on cognitive health in ageing, using data from the TUDA study (Trinity, Ulster, Department of Agriculture) linking nutrition, biomarker, lifestyle, health, and geo-referenced data with cognition as people age.

It is estimated that a 5-year delay in the onset of cognitive dysfunction would reduce population prevalence projections for dementia by 50%, thus having significant implications on health resources and society. Small but effective dietary, lifestyle and health modifications could have major impacts on the quality of life of older people and their families.

The European Commission JRC 2014 report identified multidisciplinary research into nutrition and brain health in older people as a major priority calling for the use of state-of-the-art technologies to provide a better understanding of the interactions between biological and environmental factors on brain health in ageing.

This project brings together experts in nutrition, computing, and GIS technologies to investigate novel solutions for the aggregation and preparation of datasets to produce a rich data source for a future project on effective time series interrogation, pattern analysis, and visualisation, to enable the discovery of patterns and trends that are pertinent to public health analysis.

Projected key outcomes

This scoping project aims to complete the business understanding, data understanding and data preparation phases of the CRISP-DM, to produce a version of the TUDA dataset cleansed, prepared and ready for data analytics to be carried out.

The outcomes will feed into a full project to carry out the modelling, evaluation and deployment phases of the CRISP-DM to enable the discovery of patterns and trends in the TUDA dataset that are pertinent to future health policies aimed to promote better brain health in ageing populations across various socioeconomic status (SES).