Hearing4all
Published February 14, 2023 | Version v.1.0
Software Open

Machine learning and feature importance for prediction of hearing help seeking

Creators

  • 1. Department of Psychology, University of Oldenburg and Cluster of Excellence 'Hearing4all', Oldenburg, Germany

Contributors

  • 1. Department of Medical Physics and Acoustics, University of Oldenburg and Cluster of Excellence 'Hearing4all', Oldenburg, Germany and Institut Pasteur, Université Paris Cité, Inserm, Institut de l'Audition, F-75012 Paris, France
  • 2. Department of Psychology, University of Oldenburg and Cluster of Excellence 'Hearing4all', Oldenburg, Germany
  • 3. Department of Medical Physics and Acoustics, University of Oldenburg and Cluster of Excellence 'Hearing4all', Oldenburg, Germany and Research Center Neurosensory Science, University of Oldenburg
  • 4. Department of Psychology, University of Oldenburg and Cluster of Excellence 'Hearing4all', Oldenburg, Germany and Research Center Neurosensory Science, University of Oldenburg

Description

This project contains the data analysis scripts complementing the paper:

Angonese, G., Buhl, M., Kuhlmann, I., Kollmeier, B., & Hildebrandt, A. (2024). Prediction of Hearing Help Seeking to Design a Recommendation Module of an mHealth Hearing App: Intensive Longitudinal Study of Feature Importance Assessment. JMIR Human Factors, 11, e52310. https://doi.org/10.2196/52310

 

The data will be shared upon motivated request.

Files

Psychological_profiling_scripts-v.1.0.zip

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