Prof. Dr. Winfried Schlee

IPM Institut für Informations- und ProzessmanagementProfessor für Wirtschaftsinformatik

winfried.schlee@ost.ch

Winfried Schlee ist Professor am Institut für Informations- und Prozessmanagement. Er beschäftigt sich schwerpunktmässig mit digitalen Gesundheitsanwendungen - zum Beispiel zur Diagnose und Therapie des chronischen Tinnitus.

Berufliche Praxis

2022 - heute: Professor, Institut für Informations- und Prozessmanagement, OST ST. Gallen
2019 - 2022: Medizinische Einrichtungen des Bezirks Oberpfalz (MedBo) am Bezirksklinikum Regensburg
2013 - 2019 Universitätsklinik Regensburg
2010 - 2013: Universität Ulm
2009 - 2010: Universität Konstanz

Auszeichnungen

2020: Forschungspreis der Stiftung Tinnitus und Hören Charité Berlin
2020: ICPerMed "Best Practice in Personalized Medicine" Recognition Award 2020
2017: Best Paper Award at the 6th IEEE International Conference on Artificial Intelligence and Mobile Services: Pryss, R., Schlee, W., Langguth, B. and Reichert, M., 2017, June. Mobile crowdsensing services for tinnitus assessment and patient feedback. In 2017 IEEE International Conference on AI & Mobile Services (AIMS) (pp. 22-29). IEEE.
2017: 2nd Best Paper Award, International Conference on Biomedical and Health Informatics, Thessaloniki, Greece: Dandage, S., Huber, J., Janki, A., Niemann, U., Pryss, R., Reichert, M., Harrison, S., Vessala, M., Schlee, W., Probst, T. and Spiliopoulou, M., 2017, November. Patient empowerment through summarization of discussion threads on treatments in a patient self-help forum. In International Conference on Biomedical and Health Informatics (pp. 229-233). Springer, Singapore.
2009: Auszeichnung der Doktorarbeit durch die Stiftung Schmieder für Wissenschaft und Forschung, Lurija Institut, Universität Konstanz
2008: Young Investigator Award at the International Conference on Biomagnetism, Sapporo, Japan

Kompetenzfelder

  • Digital Health
  • Tinnitus
  • Ecological Momentary Assessment (EMA)
  • Decision Support Systems (DSS)

Ausbildung

2014 - 2018: Habilitation, Experimentelle Psychiatrie, Universität Regensburg (PD)
2006 - 2009: Promotion, Klinische Psychologie und Neuropsychologie, Universität Konstanz (Dr. rer. nat.)
2000 - 2006: Studium Psychologie, Universität Konstanz (Dipl.-Psych.)

Lehre

  • Digital Health
  • Wissenschaftsmethoden
  • Medizinische Datenbanken
  • Neuropsychology and methods of Neuropsychology
  • Betreuung von studentischen Forschungsarbeiten
  • Betreuung von Bachelor-, Master- und Doktorarbeiten

Mitgliedschaften

  • Tinnitus Research Initiative (TRI)
  • Insititue of Electrical and Electronic Engineers (IEEE)

Winfried Schlee is a professor at the Institute for Information and Process Management. He focuses on digital health applications - for example, for the diagnosis and therapy of chronic tinnitus.

Area of Expertise

  • Digital Health
  • Tinnitus
  • Ecological Momentary Assessment (EMA)
  • Decision Support Systems (DSS)

Education

2014 - 2018: Habilitation, Experimental Psychiatry, University of Regensburg, Germany
2006 - 2009: PhD Doctoral Studies, Clinical Psychology and Neuropsychology, University of Konstanz, Germany
2000 - 2006: Diploma in Psychology, University of Konstanz, Germany

Teaching Experience

  • Digital Health
  • Methods of empirical studies
  • Medical databases
  • Neuropsychology and methods of neuropsychology
  • Advisory for student research projects
  • Advisory for Bachelor, Master and Doctoral theses

Memberships

  • Tinnitus Research Initiative (TRI)
  • Insititue of Electrical and Electronic Engineers (IEEE)

Peer-Reviewed Journal Articles and Conference Proceedings

  • SCHLEE, W. (2024). Global age-sex-specific mortality, life expectancy, and population estimates in 204 countries and territories and 811 subnational locations, 1950–2021, and the impact of the COVID-19 pandemic: a comprehensive demographic analysis for the Global Burden of Disease Study 2021. The Lancet.
  • SCHLEE, W. (2024). Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021. The Lancet.
  • SCHLEE, W. (2024). Global fertility in 204 countries and territories, 1950–2021, with forecasts to 2100: a comprehensive demographic analysis for the Global Burden of Disease Study 2021. The Lancet.
  • SCHLEE, W. (2024). Tinnitus: Clinical Insights in Its Pathophysiology-A Perspective. Journal of the Association for Research in Otolaryngology. 10.1007/s10162-024-00939-0
  • BREITMAYER, M., STACH, M., KRAFT, R., ALLGAIER, J., REICHERT, M., PROBST, T., ... PRYSS, R. (2023). Predicting the presence of tinnitus using ecological momentary assessments. Scientific Reports, 13 (1). 10.1038/s41598-023-36172-7
  • SCHLEE, W. (2023). An Opportunity for Constructing the Future of Data Sharing in Otolaryngology. Journal of the Association for Research in Otolaryngology, 24 (4), pp. 397-399. 10.1007/s10162-023-00908-z
  • SCHLEICHER, M., UNNIKRISHNAN, V., PRYSS, R., SCHOBEL, J., SCHLEE, W., SPILIOPOULOU, M. (2023). Prediction meets time series with gaps: User clusters with specific usage behavior patterns. Artificial Intelligence in Medicine, 142, pp. 102575. 10.1016/j.artmed.2023.102575
  • MANTA, O., SARAFIDIS, M., SCHLEE, W., MAZUREK, B., MATSOPOULOS, G. K., KOUTSOURIS, D. D. (2023). Development of Machine-Learning Models for Tinnitus-Related Distress Classification Using Wavelet-Transformed Auditory Evoked Potential Signals and Clinical Data. Journal of Clinical Medicine, 12 (11), pp. 3843. 10.3390/jcm12113843
  • SCHLEE, W. (2023). Predicting Patient-Based Time-Dependent Mobile Health Data. 2023 IEEE 36th International Symposium on Computer-Based Medical Systems (CBMS) (pp. 79-84). IEEE. 10.1109/CBMS58004.2023.00196
  • SCHLEE, W. (2023). Tinnitus Guidelines and Their Evidence Base. Journal of Clinical Medicine, 12 (9), pp. 3087. 10.3390/jcm12093087
  • MAZUREK, B., SCHULZE, H., SCHLEE, W., DOBEL, C. (2023). Tinnitus at the Junction of Traditional Medicine and Modern Technology. Nutrients, 15 (8), pp. 1898. 10.3390/nu15081898
  • UNNIKRISHNAN, V., SCHLEICHER, M., PUGA, C., PRYSS, R., VOGEL, C., SCHLEE, W., SPILIOPOULOU, M. (2023). A Similarity-Guided Framework for Error-Driven Discovery of Patient Neighbourhoods in EMA Data. In Bruno Crémilleux, Sibylle Hess, Siegfried Nijssen (Eds.), Advances in Intelligent Data Analysis XXI (pp. 459-471). Springer Nature Switzerland. 10.1007/978-3-031-30047-9_36
  • PUGA, C., NIEMANN, U., SCHLEE, W., SPILIOPOULOU, M. (2023). A cost-based multi-layer network approach for the discovery of patient phenotypes. International Journal of Data Science and Analytics , pp. 1-21. 10.1007/s41060-023-00431-7
  • HUMER, E., KEIL, T., STUPP, C., SCHLEE, W., WILDNER, M., HEUSCHMANN, P., ... PRYSS, R. (2023). Associations of Country-Specific and Sociodemographic Factors With Self-Reported COVID-19–Related Symptoms: Multivariable Analysis of Data From the CoronaCheck Mobile Health Platform. JMIR Public Health and Surveillance, 9, pp. e40958. 10.2196/40958
  • DEMOEN, S., CHALIMOURDAS, A., TIMMERMANS, A., VAN ROMPAEY, V., VANDERVEKEN, O. M., JACQUEMIN, L., ... MICHIELS, S. (2023). Effectiveness of Telerehabilitation Interventions for Self-management of Tinnitus: Systematic Review. JMIR Publications - Journal of Medical Internet Research, 25, pp. e39076. 10.2196/39076
  • ENGELKE, M., SIMÕES, J., VOGEL, C., SCHOISSWOHL, S., SCHECKLMANN, M., WÖLFLICK, S., ... SCHLEE, W. (2023). Pilot study of a smartphone-based tinnitus therapy using structured counseling and sound therapy: A multiple-baseline design with ecological momentary assessment. PLOS Digital Health, 2 (1), pp. e0000183. 10.1371/journal.pdig.0000183
  • SCHLEE, W. (2023). Randomized controlled trial of a smartphone-based cognitive behavioral therapy for chronic tinnitus. PLOS Digital Health, 2 (9), pp. e0000337. 10.1371/journal.pdig.0000337
  • BEIERLE, F., ALLGAIER, J., STUPP, C., KEIL, T., SCHLEE, W., SCHOBEL, J., ... PRYSS, R. (2023). Self-Assessment of Having COVID-19 With the Corona Check Mhealth App. IEEE Journal of Biomedical and Health Informatics, pp. 1-12. 10.1109/JBHI.2023.3264999
  • DEMOEN, S., JACQUEMIN, L., TIMMERMANS, A., VAN ROMPAEY, V., VANDERVEKEN, O., VERMEERSCH, H., ... MICHIELS, S. (2022). Cost-effectiveness of a smartphone Application for Tinnitus Treatment (the CATT trial): a study protocol of a randomised controlled trial. Trials, 23 (1). 10.1186/s13063-022-06378-7
  • MANTA, O., SARAFIDIS, M., VASILEIOU, N., SCHLEE, W., CONSOULAS, C., KIKIDIS, D., ... KOUTSOURIS, D. D. (2022). Development and Evaluation of Automated Tools for Auditory-Brainstem and Middle-Auditory Evoked Potentials Waves Detection and Annotation. Behavior and Brain Sciences, 12 (12), pp. 1675. 10.3390/brainsci12121675
  • SCHLEE, W. (2022). Free Technical Solutions for Ecological Momentary Assessments - Searching GitHub plus Google. 2022 International Conference on Computational Science and Computational Intelligence (CSCI) (pp. 1778-1781). IEEE. 10.1109/CSCI58124.2022.00315
  • MARCRUM, S. C., ENGELKE, M., GOEDHART, H., LANGGUTH, B., SCHLEE, W., VESALA, M., SIMOES, J. P. (2022). The Influence of Diet on Tinnitus Severity: Results of a Large-Scale, Online Survey. Nutrients, 14 (24), pp. 5356. 10.3390/nu14245356
  • SCHLEE, W. (2022). Low Sleep Satisfaction Is Related to High Disease Burden in Tinnitus. International Journal of Environmental Research and Public Health, 19 (17), pp. 11005. 10.3390/ijerph191711005
  • ALLGAIER, J., SCHLEE, W., PROBST, T., PRYSS, R. (2022). Prediction of Tinnitus Perception Based on Daily Life MHealth Data Using Country Origin and Season. Journal of Clinical Medicine, 11 (15), pp. 4270. 10.3390/jcm11154270
  • SCHLEICHER, M., HAMACHER, S., NAUJOKS, M., GÜNTHER, K., SCHMIDT, T., PRYSS, R., ... SPILIOPOULOU, M. (2022). Prediction of declining engagement to self-monitoring apps on the example of tinnitus mHealth data. 2022 IEEE 35th International Symposium on Computer-Based Medical Systems (CBMS) (pp. 228-233). IEEE. 10.1109/CBMS55023.2022.00047
  • SCHLEE, W. (2022). Utilizing Co-Creative Principles to Develop an E-Learning Platform for Interprofessional Training on Tinnitus: The Erasmus+ Project Tin-TRAC. International Journal of Environmental Research and Public Health, 19 (14), pp. 8323. 10.3390/ijerph19148323
  • SCHLEE, W. (2022). Burden of non-communicable diseases among adolescents aged 10–24 years in the EU, 1990–2019: a systematic analysis of the Global Burden of Diseases Study 2019. The Lancet Child & Adolescent Health, 6 (6), pp. 367-383. 10.1016/S2352-4642(22)00073-6
  • SCHLEE, W., NEFF, P., SIMÕES, J., LANGGUTH, B., SCHOISSWOHL, S., STEINBERGER, H., ... PRYSS, R. (2022). Smartphone-Guided Educational Counseling and Self-Help for Chronic Tinnitus. Journal of Clinical Medicine, 11 (7), pp. 1825. 10.3390/jcm11071825
  • SIMONES, J., BULLA, J., PRYSS, R., MARCRUM, S. C., LANGGUTH, B., SCHLEE, W. (2022). Daily Contributors of Tinnitus Loudness and Distress: An Ecological Momentary Assessment Study. Frontiers in Neuroscience, 16 (883665), pp. 1-12. 10.3389/fnins.2022.883665
  • SCHLEE, W. (2022). Global Prevalence and Incidence of Tinnitus. JAMA Neurology, 79 (9), pp. 888. 10.1001/jamaneurol.2022.2189
  • PUGA, C., SCHLEICHER, M., NIEMANN, U., UNNIKRISHNAN, V., BOECKING, B., BRUEGGEMANN, P., ... SPILIOPOULOU, M. (2022). Juxtaposing Medical Centers Using Different Questionnaires Through Score Predictors. Frontiers in Neuroscience, 16 (818686), pp. 1-12. 10.3389/fnins.2022.818686
  • SHAHANIA, S., UNNIKRISHNAN, V., PRYSS, R., KRAFT, R., SCHOBEL, J., HANNEMANN, R., ... SPILIOPOULOU, M. (2022). Predicting Ecological Momentary Assessments in an App for Tinnitus by Learning From Each User's Stream With a Contextual Multi-Armed Bandit. Frontiers in Neuroscience, 16 (836834), pp. 1-17. 10.3389/fnins.2022.836834
  • BROMIS, K., SARAFIDIS, M., MANTA, O., KOURIS, I., VELLIDOU, E., SCHLEE, W., KOUTSOURIS, D. (2022). Predicting the optimal therapeutic intervention for tinnitus patients using random forest regression: A preliminary study of UNITI's decision support system model. 2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC) (pp. 2655-2658). IEEE. 10.1109/EMBC48229.2022.9871331
  • SCHLEICHER, M., PRYSS, R., SCHLEE, W., SPILIOPOULOU, M. (2022). When Can I Expect the mHealth User to Return? Prediction Meets Time Series with Gaps. In Martin Michalowski, Syed Sibte Raza Abidi, Samina Abidi (Eds.), Artificial Intelligence in Medicine (pp. 310-320). Cham: Springer International Publishing Switzerland. 10.1007/978-3-031-09342-5_30
  • PRAKASH, S., SCHLEE, W., UNNIKRISHNAN, V., PRYSS, R., KRAFT, R., SCHOBEL, J., ... SPILIOPOULOU, M. (2021). Interactive System for Similarity-Based Inspection and Assessment of the Well-Being of mHealth Users. Entropy, 23 (12), pp. 1695. 10.3390/e23121695
  • ALLGAIER, J., SCHLEE, W., LANGGUTH, B., PROBST, T., PRYSS, R. (2021). Predicting the gender of individuals with tinnitus based on daily life data of the TrackYourTinnitus mHealth platform. Scientific Reports, 11 (1). 10.1038/s41598-021-96731-8
  • SCHLEE, W., SIMÕES, J., PRYSS, R. (2021). Auricular Acupressure Combined with Self-Help Intervention for Treating Chronic Tinnitus: A Longitudinal Observational Study. Journal of Clinical Medicine, 10 (18), pp. 4201. 10.3390/jcm10184201
  • BEIERLE, F., SCHOBEL, J., VOGEL, C., ALLGAIER, J., MULANSKY, L., HAUG, F., ... PRYSS, R. (2021). Corona Health—A Study- and Sensor-Based Mobile App Platform Exploring Aspects of the COVID-19 Pandemic. International Journal of Environmental Research and Public Health, 18 (14), pp. 7395. 10.3390/ijerph18147395
  • JAMALUDEEN, N., UNNIKRISHNAN, V., PRYSS, R., SCHOBEL, J., SCHLEE, W., SPILIOPOULOU, M. (2021). Circadian Conditional Granger Causalities on Ecological Momentary Assessment Data from an mHealth App. 2021 IEEE 34th International Symposium on Computer-Based Medical Systems (CBMS) (pp. 354-359). IEEE. 10.1109/CBMS52027.2021.00110
  • UNNIKRISHNAN, V., SHAH, Y., SCHLEICHER, M., FERNÁNDEZ-VIADERO, C., STRANDZHEVA, M., VELIKOVA, D., ... SPILIOPOULOU, M. (2021). Love thy Neighbours: A Framework for Error-Driven Discovery of Useful Neighbourhoods for One-Step Forecasts on EMA data. 2021 IEEE 34th International Symposium on Computer-Based Medical Systems (CBMS) (pp. 295-300). IEEE. 10.1109/CBMS52027.2021.00080
  • HOLFELDER, M., MULANSKY, L., SCHLEE, W., BAUMEISTER, H., SCHOBEL, J., GREGER, H., ... PRYSS, R. (2021). Medical Device Regulation Efforts for mHealth Apps during the COVID-19 Pandemic—An Experience Report of Corona Check and Corona Health. Multidisciplinary Scientific Journal, 4 (2), pp. 206-222. 10.3390/j4020017
  • VOGEL, C., PRYSS, R., SCHOBEL, J., SCHLEE, W., BEIERLE, F. (2021). Developing Apps for Researching the COVID-19 Pandemic with the TrackYourHealth Platform. 2021 IEEE/ACM 8th International Conference on Mobile Software Engineering and Systems (MobileSoft) (pp. 65-68). IEEE. 10.1109/MobileSoft52590.2021.00015
  • ALLGAIER, J., NEFF, P., SCHLEE, W., SCHOISSWOHL, S., PRYSS, R. (2021). Deep Learning End-to-End Approach for the Prediction of Tinnitus based on EEG Data. 2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC) (pp. 816-819). IEEE. 10.1109/EMBC46164.2021.9629964
  • PUGA, C., NIEMANN, U., UNNIKRISHNAN, V., SCHLEICHER, M., SCHLEE, W., SPILIOPOULOU, M. (2021). Discovery of Patient Phenotypes through Multi-layer Network Analysis on the Example of Tinnitus. 2021 IEEE 8th International Conference on Data Science and Advanced Analytics (DSAA) (pp. 1-10). IEEE. 10.1109/DSAA53316.2021.9564158
  • BUDIMIR, S., KUSKA, M., SPILIOPOULOU, M., SCHLEE, W., PRYSS, R., ANDERSSON, G., ... PROBST, T. (2021). Reasons for Discontinuing Active Participation on the Internet Forum Tinnitus Talk: Mixed Methods Citizen Science Study. JMIR Formative Research, 5 (4), pp. e21444. 10.2196/21444
  • VOGEL, C., SCHOBEL, J., SCHLEE, W., ENGELKE, M., PRYSS, R. (2021). UNITI Mobile—EMI-Apps for a Large-Scale European Study on Tinnitus. 2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC) (pp. 2358-2362). IEEE. 10.1109/EMBC46164.2021.9630482
  • SARAFIDIS, M., MANTA, O., KOURIS, I., SCHLEE, W., KIKIDIS, D., VELLIDOU, E., KOUTSOURIS, D. (2021). Why a Clinical Decision Support System is needed for Tinnitus? 2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC) (pp. 2075-2078). 10.1109/EMBC46164.2021.9630137
  • UNNIKRISHNAN, V., SCHLEICHER, M., SHAH, Y., JAMALUDEEN, N., PRYSS, R., SCHOBEL, J., ... SPILIOPOULOU, M. (2020). The Effect of Non-Personalised Tips on the Continued Use of Self-Monitoring mHealth Applications. Behavior and Brain Sciences, 10 (12), pp. 924. 10.3390/brainsci10120924
  • SCHLEICHER, M., UNNIKRISHNAN, V., NEFF, P., SIMÕES, J., PROBST, T., PRYSS, R., ... SPILIOPOULOU, M. (2020). Understanding adherence to the recording of ecological momentary assessments in the example of tinnitus monitoring. Scientific Reports, 10 (1). 10.1038/s41598-020-79527-0
  • MEHDI, M., DODE, A., PRYSS, R., SCHLEE, W., REICHERT, M., HAUCK, F. J. (2020). Contemporary Review of Smartphone Apps for Tinnitus Management and Treatment. Behavior and Brain Sciences, 10 (11), pp. 867. 10.3390/brainsci10110867
  • SCHLEE, W., HØLLELAND, S., BULLA, J., SIMÕES, J., NEFF, P., SCHOISSWOHL, S., ... LANGGUTH, B. (2020). The Effect of Environmental Stressors on Tinnitus: A Prospective Longitudinal Study on the Impact of the COVID-19 Pandemic. Journal of Clinical Medicine, 9 (9), pp. 2756. 10.3390/jcm9092756
  • KRAFT, R., BIRK, F., REICHERT, M., DESHPANDE, A., SCHLEE, W., LANGGUTH, B., ... PRYSS, R. (2020). Efficient Processing of Geospatial mHealth Data Using a Scalable Crowdsensing Platform. Sensors, 20 (12), pp. 3456. 10.3390/s20123456
  • BEIERLE, F., TRAN, V. T., ALLEMAND, M., NEFF, P., SCHLEE, W., PROBST, T., ... PRYSS, R. (2020). What data are smartphone users willing to share with researchers? Journal of Ambient Intelligence and Humanized Computing , 11 (6), pp. 2277-2289. 10.1007/s12652-019-01355-6
  • SCHOBEL, J., PROBST, T., REICHERT, M., SCHLEE, W., SCHICKLER, M., KESTLER, H. A., PRYSS, R. (2020). Measuring Mental Effort for Creating Mobile Data Collection Applications. International Journal of Environmental Research and Public Health, 17 (5), pp. 1649. 10.3390/ijerph17051649
  • MEHDI, M., RIHA, C., NEFF, P., DODE, A., PRYSS, R., SCHLEE, W., ... HAUCK, F. J. (2020). Smartphone Apps in the Context of Tinnitus: Systematic Review. Sensors, 20 (6), pp. 1725. 10.3390/s20061725
  • PRYSS, R., SCHLEE, W., HOPPENSTEDT, B., REICHERT, M., SPILIOPOULOU, M., LANGGUTH, B., ... PROBST, T. (2020). 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. JMIR Publications - Journal of Medical Internet Research, 22 (6), pp. e15547. 10.2196/15547
  • KRAFT, R., SCHLEE, W., STACH, M., REICHERT, M., LANGGUTH, B., BAUMEISTER, H., ... PRYSS, R. (2020). Combining Mobile Crowdsensing and Ecological Momentary Assessments in the Healthcare Domain. Frontiers in Neuroscience, 14 (164), pp. 1-14. 10.3389/fnins.2020.00164
  • KRAFT, R., STACH, M., REICHERT, M., SCHLEE, W., PROBST, T., LANGGUTH, B., ... PRYSS, R. (2020). Comprehensive insights into the TrackYourTinnitus database. The 17th International Conference on Mobile Systems and Pervasive Computing (MobiSPC) (pp. 28-35). Procedia Computer Science. 10.1016/j.procs.2020.07.008
  • O'ROURKE, T., PRYSS, R., SCHLEE, W., PROBST, T. (2020). Development of a Multidimensional App-Quality Assessment Tool for Health-Related Apps (AQUA). Digital Psychology, 1 (2), pp. 13-23. 10.24989/dp.v1i2.1816
  • UNNIKRISHNAN, V., SHAH, Y., SCHLEICHER, M., STRANDZHEVA, M., DIMITROV, P., VELIKOVA, D., ... SPILIOPOULOU, M. (2020). Predicting the Health Condition of mHealth App Users with Large Differences in the Number of Recorded Observations - Where to Learn from? In Annalisa Appice, Grigorios Tsoumakas, Yannis Manolopoulos, Stan Matwin (Eds.), Discovery Science (pp. 659-673). Cham: Springer International Publishing Switzerland. 10.1007/978-3-030-61527-7_43
  • MEHDI, M., STACH, M., RIHA, C., NEFF, P., DODE, A., PRYSS, R., ... HAUCK, F. J. (2020). Smartphone and Mobile Health Apps for Tinnitus: Systematic Identification, Analysis, and Assessment. JMIR mHealth and uHealth, 8 (8), pp. e21767. 10.2196/21767
  • MEHDI, M., DIEMER, F., HENNIG, L., DODE, A., PRYSS, R., SCHLEE, W., ... HAUCK, F. (2020). TinnituSense: a Mobile Electroencephalography (EEG) Smartphone App for Tinnitus Research. MobiQuitous '20: Computing, Networking and Services (pp. 252-261). ACM Press. 10.1145/3448891.3448933
  • PRYSS, R., PROBST, T., SCHLEE, W., SCHOBEL, J., LANGGUTH, B., NEFF, P., ... REICHERT, M. (2019). Prospective crowdsensing versus retrospective ratings of tinnitus variability and tinnitus–stress associations based on the TrackYourTinnitus mobile platform. International Journal of Data Science and Analytics , 8 (4), pp. 327-338. 10.1007/s41060-018-0111-4
  • HOPPENSTEDT, B., REICHERT, M., KAMMERER, K., PROBST, T., SCHLEE, W., SPILIOPOULOU, M., PRYSS, R. (2019). Dimensionality Reduction and Subspace Clustering in Mixed Reality for Condition Monitoring of High-Dimensional Production Data. Sensors, 19 (18), pp. 3903. 10.3390/s19183903
  • PRYSS, R., SCHLEE, W., REICHERT, M., KURTHEN, I., GIROUD, N., JAGODA, L., ... PROBST, T. (2019). Ecological Momentary Assessment based Differences between Android and iOS Users of the TrackYourHearing mHealth Crowdsensing Platform. 2019 41st Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC) (pp. 3951-3955). 10.1109/EMBC.2019.8857854
  • PRYSS, R., JOHN, D., REICHERT, M., HOPPENSTEDT, B., SCHMID, L., SCHLEE, W., ... PROBST, T. (2019). Machine Learning Findings on Geospatial Data of Users from the TrackYourStress mHealth Crowdsensing Platform. 2019 IEEE 20th International Conference on Information Reuse and Integration for Data Science (IRI) (pp. 350-355). 10.1109/IRI.2019.00061
  • KRAFT, R., BIRK, F., REICHERT, M., DESHPANDE, A., SCHLEE, W., LANGGUTH, B., ... PRYSS, R. (2019). Design and Implementation of a Scalable Crowdsensing Platform for Geospatial Data of Tinnitus Patients. 2019 IEEE 32nd International Symposium on Computer-Based Medical Systems (CBMS) (pp. 294-299). IEEE. 10.1109/CBMS.2019.00068
  • MEHDI, M., SCHWAGER, D., PRYSS, R., SCHLEE, W., REICHERT, M., HAUCK, F. J. (2019). Towards Automated Smart Mobile Crowdsensing for Tinnitus Research. 2019 IEEE 32nd International Symposium on Computer-Based Medical Systems (CBMS) (pp. 75-80). IEEE. 10.1109/CBMS.2019.00026
  • HOPPENSTEDT, B., PROBST, T., REICHERT, M., SCHLEE, W., KAMMERER, K., SPILIOPOULOU, M., ... PRYSS, R. (2019). Applicability of Immersive Analytics in Mixed Reality: Usability Study. IEEE Xplore, 7, pp. 71921-71932. 10.1109/ACCESS.2019.2919162
  • PRYSS, R., JOHN, D., SCHLEE, W., SCHLOTZ, W., SCHOBEL, J., KRAFT, R., ... PROBST, T. (2019). Exploring the Time Trend of Stress Levels While Using the Crowdsensing Mobile Health Platform, TrackYourStress, and the Influence of Perceived Stress Reactivity: Ecological Momentary Assessment Pilot Study. JMIR mHealth and uHealth, 7 (10), pp. e13978. 10.2196/13978
  • MICHIELS, S., HARRISON, S., VESALA, M., SCHLEE, W. (2019). The Presence of Physical Symptoms in Patients With Tinnitus: International Web-Based Survey. Interactive Journal of Medical Research, 8 (3), pp. e14519. 10.2196/14519
  • SIMOES, J. P., NEFF, P., SCHOISSWOHL, S., BULLA, J., SCHECKLMANN, M., HARRISON, S., ... SCHLEE, W. (2019). Towards Personalized Tinnitus Treatment: An Exploratory Study Based on Internet Crowdsensing. Frontiers in Public Health, 7, pp. 157. 10.3389/fpubh.2019.00157

Books and Research Monographs

Chapters in Edited Books

  • SCHLEE, W., LANGGUTH, B., PRYSS, R., ALLGAIER, J., MULANSKY, L., VOGEL, C., ... KIKIDIS, D. (2021). Using Big Data to Develop a Clinical Decision Support System for Tinnitus Treatment (1 ed.). In Grant D. Searchfield, Jinsheng Zhang (Eds.), The Behavioral Neuroscience of Tinnitus (pp. 175-189). Cham: Springer International Publishing Switzerland. 10.1007/7854_2021_229
  • SCHLEE, W., KRAFT, R., SCHOBEL, J., LANGGUTH, B., PROBST, T., NEFF, P., ... PRYSS, R. (2019). Momentary Assessment of Tinnitus—How Smart Mobile Applications Advance Our Understanding of Tinnitus (1 ed.). In Harald Baumeister, Christian Montag (Eds.), Digital Phenotyping and Mobile Sensing (pp. 209-220). Cham: Springer International Publishing Switzerland. 10.1007/978-3-030-31620-4_13
  • PRYSS, R., KRAFT, R., BAUMEISTER, H., WINKLER, J., PROBST, T., REICHERT, M., ... SCHLEE, W. (2019). Using Chatbots to Support Medical and Psychological Treatment Procedures: Challenges, Opportunities, Technologies, Reference Architecture (1 ed.). In Harald Baumeister, Christian Montag (Eds.), Digital Phenotyping and Mobile Sensing (pp. 249-260). Cham: Springer International Publishing Switzerland. 10.1007/978-3-030-31620-4_16

Professional Journals and Newspaper

  • DODE, A., MEHDI, M., PRYSS, R., SCHLEE, W., PROBST, T., REICHERT, M., ... WINTER, M. (2021). Using a visual analog scale (VAS) to measure tinnitus-related distress and loudness: Investigating correlations using the Mini-TQ results of participants from the TrackYourTinnitus platform. Elsevier, pp. 171-190. London. 10.1016/bs.pbr.2020.08.008
  • SCHLEE, W. (2017). What Does Tinnitus Have to Do with Hearing Loss? Frontiers for Young Minds.

Presentations

  • SCHLEICHER, M., PRYSS, R., SCHOBEL, J., SCHLEE, W., SPILIOPOULOU, M. (2022). Expect the gap: A recommender approach to estimate the absenteeism of self-monitoring mHealth app users. 2022 IEEE 9th International Conference on Data Science and Advanced Analytics (DSAA) (pp. 1-10). IEEE. 10.1109/DSAA54385.2022.10032390
  • SCHLEE, W. (2022). UNITI - erste Daten einer Multicenter-Studie. 23. Tinnitussymposium Charité.
  • SCHLEE, W. (2022). Variation d'un moment á l'autre d'un accoupène détecté par smartphone. 12ème colloque AFREPA.
  • SCHLEE, W. (2022). emporal dynamics of the subjective tinnitus perception. Novembro Laranja, Campanha Nacional de Alerta Ao Zumbido, Misofonia e Hiperacusio.
  • SCHLEE, W. (2021). Moment-to-moment variability of tinnitus measured with a smartphone. 12ème colloque AFREPA.
  • SCHLEE, W. (2021). Temporal dynamics of the subjective tinnitus perception. Weizha international sobre zumbido e hippersensibilidades auditivas.
  • SCHLEE, W. (2021). Zeitliche Dynamik der Tinnituswahrnehmung. 22. Tinnitussymposium Charité.
  • SCHLEE, W. (2019). Gender-based differences in chronic tinnitus. Tinnitus Research Initiative International Conference, Taiwan.