This paper is in the following e-collection/theme issue:

New Methods (944) Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1641) Depression and Mood Disorders; Suicide Prevention (1363) Diagnostic Tools in Mental Health (242)

Published on in Vol 21, No 6 (2019): June

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/12554, first published .
Early Detection of Depression: Social Network Analysis and Random Forest Techniques

Early Detection of Depression: Social Network Analysis and Random Forest Techniques

Early Detection of Depression: Social Network Analysis and Random Forest Techniques

Authors of this article:

Fidel Cacheda1, 2 Author Orcid Image ;   Diego Fernandez1, 2 Author Orcid Image ;   Francisco J Novoa1, 2 Author Orcid Image ;   Victor Carneiro1, 2 Author Orcid Image
Article Authors Cited by (126) Tweetations (95) Metrics

Fidel Cacheda   1, 2 , PhD ;   Diego Fernandez   1, 2 , PhD ;   Francisco J Novoa   1, 2 , PhD ;   Victor Carneiro   1, 2 , PhD

1 Department of Computer Science, Faculty of Computer Science, University of A Coruna, A Coruna, Spain

2 Center for Information and Communications Technology Research, University of A Coruna, A Coruna, Spain

Corresponding Author:

  • Diego Fernandez, PhD
  • Department of Computer Science
  • Faculty of Computer Science
  • University of A Coruna
  • Campus de Elvina
  • A Coruna, 15071
  • Spain
  • Phone: 34 881011213
  • Email: diego.fernandez@udc.es