Mapping longitudinal studies to risk factors in an ontology for dementia

Mark Roantree, Jim O' Donoghue*, Noel O' Kelly, Maria Pierce, Kate Irving, Martin Van Boxtel, Sebastian Köhler

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review


A common activity carried out by healthcare professionals is to test various hypotheses on longitudinal study data in an effort to develop new and more reliable algorithms that might determine the possibility of developing certain illnesses. The INnovative, Midlife INtervention for Dementia Deterrence project provides input from a number of European dementia experts to identify the most accurate model of inter-related risk factors which can yield a personalized dementia-risk quotient and profile. This model is then validated against the large population-based prospective Maastricht Aging Study dataset. As part of this overall goal, the research presented in this article demonstrates how we can automate the process of mapping modifiable risk factors against large sections of the aging study and thus use information technology to provide more powerful query interfaces.

Original languageEnglish
Pages (from-to)414-426
Number of pages13
JournalHealth Informatics Journal
Issue number2
Publication statusPublished - Jun 2016


  • dementia
  • modifiable risk factors
  • ontology
  • word matching

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