Published on in Vol 5, No 1 (2022): Jan-Mar

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/28333, first published .
Predicting Working Memory in Healthy Older Adults Using Real-Life Language and Social Context Information: A Machine Learning Approach

Predicting Working Memory in Healthy Older Adults Using Real-Life Language and Social Context Information: A Machine Learning Approach

Predicting Working Memory in Healthy Older Adults Using Real-Life Language and Social Context Information: A Machine Learning Approach

Andrea Ferrario   1, 2 , PhD ;   Minxia Luo   3, 4 , PhD ;   Angelina J Polsinelli   5 , PhD ;   Suzanne A Moseley   6 , PhD ;   Matthias R Mehl   7 , Prof Dr ;   Kristina Yordanova   8 , Dr ;   Mike Martin   3, 4 , Prof Dr ;   Burcu Demiray   3, 4 , PhD

1 Chair of Technology Marketing, ETH Zurich, Zurich, Switzerland

2 Mobiliar Lab for Analytics, ETH Zurich, Zurich, Switzerland

3 Department of Psychology, University of Zurich, Zurich, Switzerland

4 University Research Priority Program Dynamics of Healthy Aging, University of Zurich, Zurich, Switzerland

5 Department of Neurology, Indiana University School of Medicine, Indianapolis, IN, United States

6 Department of Psychology, Minnesota Epilepsy Group, St Paul, MN, United States

7 Department of Psychology, University of Arizona, Tucson, AZ, United States

8 Institute of Computer Science, University of Rostock, Rostock, Germany

Corresponding Author:

  • Andrea Ferrario, PhD
  • Chair of Technology Marketing
  • ETH Zurich
  • Weinbergstrasse 56/58
  • Zurich, 8092
  • Switzerland
  • Phone: 41 799282484
  • Email: aferrario@ethz.ch