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

New Methods (944) Patient-Reported Outcome Measures (PROMs) (288) Machine Learning (1463) Ecological Momentary Assessment (EMA) (309) mHealth for Data Collection and Research (954) mHealth for Symptom and Disease Monitoring, Chronic Disease Management (1397) Hearing Impairment and Hearing Loss (67)

Published on in Vol 22, No 6 (2020): June

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/15547, first published .
Applying Machine Learning to Daily-Life Data From the TrackYourTinnitus Mobile Health Crowdsensing Platform to Predict the Mobile Operating System Used With High Accuracy: Longitudinal Observational Study

Applying Machine Learning to Daily-Life Data From the TrackYourTinnitus Mobile Health Crowdsensing Platform to Predict the Mobile Operating System Used With High Accuracy: Longitudinal Observational Study

Applying Machine Learning to Daily-Life Data From the TrackYourTinnitus Mobile Health Crowdsensing Platform to Predict the Mobile Operating System Used With High Accuracy: Longitudinal Observational Study

Authors of this article:

Rüdiger Pryss1 Author Orcid Image ;   Winfried Schlee2 Author Orcid Image ;   Burkhard Hoppenstedt3 Author Orcid Image ;   Manfred Reichert3 Author Orcid Image ;   Myra Spiliopoulou4 Author Orcid Image ;   Berthold Langguth2 Author Orcid Image ;   Marius Breitmayer3 Author Orcid Image ;   Thomas Probst5 Author Orcid Image
Article Authors Cited by (15) Tweetations (5) Metrics

Rüdiger Pryss   1 , PhD, Prof Dr ;   Winfried Schlee   2 , PhD ;   Burkhard Hoppenstedt   3 , MSc ;   Manfred Reichert   3 , PhD, Prof Dr ;   Myra Spiliopoulou   4 , PhD, Prof Dr ;   Berthold Langguth   2 , PhD, Prof Dr ;   Marius Breitmayer   3 , MSc ;   Thomas Probst   5 , PhD, Prof Dr

1 Institute of Clinical Epidemiology and Biometry, University of Würzburg, Würzburg, Germany

2 Department of Psychiatry and Psychotherapy, University of Regensburg, Regensburg, Germany

3 Institute of Databases and Information Systems, Ulm University, Ulm, Germany

4 Faculty of Computer Science, Otto von Guericke University of Magdeburg, Magdeburg, Germany

5 Department for Psychotherapy and Biopsychosocial Health, Danube University Krems, Krems, Austria

Corresponding Author:

  • Rüdiger Pryss, PhD, Prof Dr
  • Institute of Clinical Epidemiology and Biometry
  • University of Würzburg
  • Josef-Schneider-Str 2
  • Würzburg, 97080
  • Germany
  • Phone: 49 931-20146471
  • Fax: 49 931-201647310
  • Email: ruediger.pryss@uni-wuerzburg.de