Published on in Vol 8, No 9 (2020): September

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/20995, first published .
Identifying Key Predictors of Cognitive Dysfunction in Older People Using Supervised Machine Learning Techniques: Observational Study

Identifying Key Predictors of Cognitive Dysfunction in Older People Using Supervised Machine Learning Techniques: Observational Study

Identifying Key Predictors of Cognitive Dysfunction in Older People Using Supervised Machine Learning Techniques: Observational Study

Debbie Rankin   1 , BSc, PhD ;   Michaela Black   1 , BSc, PhD ;   Bronac Flanagan   1 , BSc, MSc, PhD ;   Catherine F Hughes   2 , BSc, PhD ;   Adrian Moore   3 , BSc, MSc, PhD ;   Leane Hoey   2 , BSc, MSc, PhD ;   Jonathan Wallace   4 , BA, MSc ;   Chris Gill   2 , BSc, PhD ;   Paul Carlin   5 , BSc, MPA ;   Anne M Molloy   6 , PhD ;   Conal Cunningham   7 , MD ;   Helene McNulty   2 , BSc, PhD

1 School of Computing, Engineering and Intelligent Systems, Ulster University, Derry~Londonderry, United Kingdom

2 School of Biomedical Sciences, Nutrition Innovation Centre for Food and Health, Ulster University, Coleraine, United Kingdom

3 School of Geography and Environmental Sciences, Ulster University, Coleraine, United Kingdom

4 School of Computing, Ulster University, Jordanstown, United Kingdom

5 School of Health, Wellbeing and Social Care, The Open University, Belfast, United Kingdom

6 School of Medicine, Trinity College Dublin, Dublin, Ireland

7 Mercers Institute for Research on Ageing, St James's Hospital, Dublin, Ireland

Corresponding Author:

  • Debbie Rankin, BSc, PhD
  • School of Computing, Engineering and Intelligent Systems
  • Ulster University
  • Northland Road
  • Derry~Londonderry, BT48 7JL
  • United Kingdom
  • Phone: 44 287167 ext 5841
  • Email: d.rankin1@ulster.ac.uk