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Editorial: Smart Mobile Data Collection in the Context of Neuroscience, , , , , and . Frontiers in Neuroscience, (2021)Combining Mobile Crowdsensing and Ecological Momentary Assessments in the Healthcare Domain, , , , , , , , and . Frontiers in Neuroscience, (2020)Towards the Interpretation of Sound Measurements from Smartphones Collected with Mobile Crowdsensing in the Healthcare Domain: An Experiment with Android Devices., , and . Sensors, 22 (1): 170 (2022)Dealing With Inaccurate Sensor Data in the Context of Mobile Crowdsensing and mHealth., , , and . IEEE J. Biomed. Health Informatics, 26 (11): 5439-5449 (2022)Towards Mobile-Based Preprocessing Pipeline for Electroencephalography (EEG) Analyses: The Case of Tinnitus, , , , , , , and . Wireless Mobile Communication and Healthcare, page 67-86. Springer International Publishing, (2021)Ambalytics: A Scalable and Distributed System Architecture Concept for Bibliometric Network Analyses, , , and . Future Internet, 13 (8): 203 (2021)Quality of life during the COVID-19 pandemic–Results of the CORONA HEALTH App study, , , , , and . Journal of Health Monitoring, 6 (Suppl 6): 2-21 (2021)How does the model make predictions? A systematic literature review on the explainability power of machine learning in healthcare., , , and . Artif. Intell. Medicine, (September 2023)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, 8 (4): 327--338 (Nov 1, 2019)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)