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Predicting Ecological Momentary Assessments in an App for Tinnitus by Learning From Each User's Stream With a Contextual Multi-Armed Bandit.
Shahania, Saijal; Unnikrishnan, Vishnu; Pryss, Rüdiger; Kraft, Robin; Schobel, Johannes; Hannemann, Ronny; Schlee, Winny; Spiliopoulou, Myra.
Afiliación
  • Shahania S; Knowledge Management and Discovery Lab, Otto-von-Guericke University Magdeburg, Magdeburg, Germany.
  • Unnikrishnan V; Knowledge Management and Discovery Lab, Otto-von-Guericke University Magdeburg, Magdeburg, Germany.
  • Pryss R; Institute of Clinical Epidemiology and Biometry, University of Würzburg, Würzburg, Germany.
  • Kraft R; Institute of Databases and Information Systems, Ulm University, Ulm, Germany.
  • Schobel J; DigiHealth Institute, Neu-Ulm University of Applied Sciences, Neu-Ulm, Germany.
  • Hannemann R; Sivantos GmbH - WS Audiology, Erlangen, Germany.
  • Schlee W; Department of Psychiatry and Psychotherapy, University of Regensburg, Regensburg, Germany.
  • Spiliopoulou M; Knowledge Management and Discovery Lab, Otto-von-Guericke University Magdeburg, Magdeburg, Germany.
Front Neurosci ; 16: 836834, 2022.
Article en En | MEDLINE | ID: mdl-35478848
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Texto completo: 1 Bases de datos: MEDLINE Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Front Neurosci Año: 2022 Tipo del documento: Article País de afiliación: Alemania
Texto completo
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Bases de datos: MEDLINE Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Front Neurosci Año: 2022 Tipo del documento: Article País de afiliación: Alemania