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Prospective crowdsensing versus retrospective ratings of tinnitus variability and tinnitus–stress associations based on the TrackYourTinnitus mobile platform

, , , , , , , and . International Journal of Data Science and Analytics, (2018)

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Process-Driven Mobile Data Collection., , , and . EMISA Forum, 37 (1): 38-39 (2017)Enhancing mHealth data collection applications with sensing capabilities, , , , , , and . Frontiers in Public Health, (2022)Developing a Gamification-Based mHealth Platform to Support Orofacial Myofunctional Therapy for Children., , , and . CBMS, page 169-172. IEEE, (2023)Expect the gap: A recommender approach to estimate the absenteeism of self-monitoring mHealth app users., , , , and . DSAA, page 1-10. IEEE, (2022)Circadian Conditional Granger Causalities on Ecological Momentary Assessment Data from an mHealth App., , , , , and . CBMS, page 354-359. IEEE, (2021)Towards an Architecture for Collecting a Multidimensional Glioblastoma Dataset., , , , , , , , , and . CBMS, page 904-909. IEEE, (2023)Single versus Combination Treatment in Tinnitus: A Randomized, Multicenter Trial, , , , , , , , , and 40 other author(s). medRxiv, (2024)Preismodelle für Diagnostische Entscheidungsunterstützungssysteme: Marktstrukturanalyse und Entwicklungstendenzen., , , and . INFORMATIK, volume P-366 of LNI, page 1489-1498. Gesellschaft für Informatik, Bonn, (2025)The statistical analysis plan for the unification of treatments and interventions for tinnitus patients randomized clinical trial (UNITI-RCT), , , , , , , , , and 31 other author(s). Trials, 24 (1): 472 (2023)The Effect of Non-Personalised Tips on the Continued Use of Self-Monitoring mHealth Applications, , , , , , , , and . Brain Sciences, 10 (12): 924 (2020)