The Alzheimer's Association International Conference is the conference where all the greatest minds in the field of dementia research come together in one place to present and discuss the latest findings and techniques. For DPUK, AAIC was the opportunity to showcase some of our newest cross-cohort research in the Data Portal, and present our data curation work - an initiative to make cross-cohort studies easier.
Our data curation initiative
The answers to some of the current challenges we face in dementia research will come from making use of the rich health datasets in cohort studies. The aim of our data curation work is to facilitate analyses which use more than one cohort study – we found AAIC researchers excited to learn about our initiative. DPUK's senior researcher and data manager, Dr Sarah Bauermeister, says:
Our data curation initiative C-SURV was met with great interest. Enthusiasm in working with large datasets is growing generally, but combining them with other datasets is still difficult. C-SURV facilitates this with a standardisation procedure.
DPUK’s data curation initiative - C-SURV - consists of four core components: ontology, standardisation, categorisation and harmonisation. The aim is to facilitate cross-cohort analyses, which alongside the updated metadata tools in the Data Portal will make data application and analysis much easier for researchers.
The Data Portal brings together data from 47 cohorts, facilitating analyses which make use of more than one dataset. DPUK researchers presented this cross-cohort analysis study looking at the impact of childhood experiences on later life dementia at AAIC 2019.
Read more about DPUK's data curation work.
Machine learning in dementia research
Machine learning is still a relatively unexplored technique in much dementia research but one in which there’s increasing interest now. At the conference, Sarah, reflected:
Many researchers are not using data machine learning or AI but there is great interest in this area. I was keen to share the potential of using machine learning and AI alongside traditional techniques and found researchers to be excited by the opportunities. - Dr Sarah Bauermeister, senior researcher and data manager