piwik-script

English Intern
Lehrstuhl für klinische Epidemiologie und Biometrie

Michael Stach

M.Sc. Michael Stach

Am Schwarzenberg 15, Haus A15

Kurzer Lebenslauf

seit 2023

 Wissenschaftlicher Mitarbeiter am Institut für Klinische Epidemiologie und Biometrie, Universität Würzburg
2017-2022

Wissenschaftlicher Mitarbeiter am Institut für Datenbanken und Informationssysteme, Universität Ulm

2014-2016

Studium M.Sc. Medieninformatik, Schwerpunkt Verteilte Systeme & Informationssysteme, Universität Ulm
2010-2014

Studium B.Sc. Medieninformatik, Universität Ulm

 

Wissenschaftliche Schwerpunkte

Digital Health, Daily Life Research, Mobile Computing, Information Systems

Projekte

Ausgewählte Publikationen der letzten Jahre

2023[ to top ]
  • 1.
    Breitmayer M, Stach M, Kraft R, Allgaier J, Reichert M, Schlee W, et al. Predicting the presence of tinnitus using ecological momentary assessments. Scientific Reports [Internet]. 2023;13(1):8989. Available from: https://doi.org/10.1038/s41598-023-36172-7
  • 1.
    Beierle F, Allgaier J, Stupp C, Keil T, Schlee W, Schobel J, et al. Self-Assessment of Having COVID-19 With the Corona Check Mhealth App. IEEE J Biomed Health Inform. 2023;Pp.
2022[ to top ]
  • 1.
    Stach M, Reichert M, Prasser F, Baumeister H, Schlee W, Heuschmann P, et al. Free Technical Solutions for Ecological Momentary Assessments - Searching GitHub plus Google. In: 2022 International Conference on Computational Science and Computational Intelligence (CSCI). 2022. pp. 1778-81.
  • 1.
    Stach M, Pflüger F, Reichert M, Pryss R. LAMP: a monitoring framework for mHealth application research. Procedia Computer Science [Internet]. 2022;198:203-10. Available from: https://www.sciencedirect.com/science/article/pii/S1877050921024686
2021[ to top ]
  • 1.
    Beierle F, Schobel J, Vogel C, Allgaier J, Mulansky L, Haug F, et al. 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. 2021;18(14):7395.
2020[ to top ]
  • 1.
    Stach M, Vogel C, Gablonski TC, Andreas S, Probst T, Reichert M, et al. Technical Challenges of a Mobile Application Supporting Intersession Processes in Psychotherapy. Procedia Computer Science [Internet]. 2020;175:261-8. Available from: https://www.sciencedirect.com/science/article/pii/S187705092031718X
  • 1.
    Stach M, Kraft R, Probst T, Messner EM, Terhorst Y, Baumeister H, et al. Mobile Health App Database - A Repository for Quality Ratings of mHealth Apps. In: 2020 IEEE 33rd International Symposium on Computer-Based Medical Systems (CBMS). 2020. pp. 427-32.
  • 1.
    Mehdi M, Stach M, Riha C, Neff P, Dode A, Pryss R, et al. Smartphone and Mobile Health Apps for Tinnitus: Systematic Identification, Analysis, and Assessment. JMIR Mhealth Uhealth [Internet]. 2020;8(8):e21767. Available from: http://mhealth.jmir.org/2020/8/e21767/https://doi.org/10.2196/21767http://www.ncbi.nlm.nih.gov/pubmed/32808939
  • 1.
    Kraft R, Stach M, Reichert M, Schlee W, Probst T, Langguth B, et al. Comprehensive insights into the TrackYourTinnitus database. Procedia Computer Science [Internet]. 2020;175:28-35. Available from: https://www.sciencedirect.com/science/article/pii/S1877050920316872
  • 1.
    Kraft R, Schlee W, Stach M, Reichert M, Langguth B, Baumeister H, et al. Combining Mobile Crowdsensing and Ecological Momentary Assessments in the Healthcare Domain. Frontiers in Neuroscience [Internet]. 2020;14. Available from: https://www.frontiersin.org/articles/10.3389/fnins.2020.00164