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

Engagement with and Adherence to Digital Health Interventions, Law of Attrition (493) Machine Learning (1465)

Published on in Vol 22, No 10 (2020): October

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/17738, first published .
Developing a Process for the Analysis of User Journeys and the Prediction of Dropout in Digital Health Interventions: Machine Learning Approach

Developing a Process for the Analysis of User Journeys and the Prediction of Dropout in Digital Health Interventions: Machine Learning Approach

Developing a Process for the Analysis of User Journeys and the Prediction of Dropout in Digital Health Interventions: Machine Learning Approach

Authors of this article:

Vincent Bremer1 Author Orcid Image ;   Philip I Chow2 Author Orcid Image ;   Burkhardt Funk1 Author Orcid Image ;   Frances P Thorndike2 Author Orcid Image ;   Lee M Ritterband2 Author Orcid Image
Article Authors Cited by (16) Tweetations (5) Metrics

Vincent Bremer   1 * , MA ;   Philip I Chow   2 * , PhD ;   Burkhardt Funk   1 * , PhD ;   Frances P Thorndike   2 * , PhD ;   Lee M Ritterband   2 * , PhD

1 Institute of Information Systems, Leuphana University Lüneburg, Lüneburg, Germany

2 Center for Behavioral Health & Technology, University of Virginia School of Medicine, Charlottesville, VA, United States

*all authors contributed equally

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