Record link: 
http://hdl.handle.net/20.500.12708/204634
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Title: 
Recommendation Modeling for Health Self-Management Applications for People with Rheumatoid Arthritis
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Citation: 
Schwab, N., Zauner, G., Urach, C., Studenic, P., Radner, H., Nakhost-Lotfi, N., Stamm, T., Hammer-Jakobsen, T., Dam, A., & Popper, N. (2024). Recommendation Modeling for Health Self-Management Applications for People with Rheumatoid Arthritis. In Tagungsband Langbeiträge ASIM SST 2024, 27. Symposium Simulationstechnik, München (pp. 43–50). ARGESIM Publisher Vienna. https://doi.org/10.11128/arep.47.a4725
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Publisher DOI: 
10.11128/arep.47.a4725
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Publication Type: 
Inproceedings - Full-Paper Contribution
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Language: 
English
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Authors: 
Schwab, Nadine 
Zauner, Günther 
Urach, Christoph 
Studenic, Paul 
Radner, Helga 
Nakhost-Lotfi, Nasim 
Stamm, Tanja 
Hammer-Jakobsen, Thomas 
Dam, Andreas 
Popper, Nikolas 
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Organisational Unit: 
E194-04 - Forschungsbereich Data Science 
E105-06 - Forschungsbereich Computational Statistics 
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Published in: 
Tagungsband Langbeiträge ASIM SST 2024, 27. Symposium Simulationstechnik, München 
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ISBN: 
978-3-903347-65-6
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DOI of the book: 
10.11128/arep.47
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Date (published): 
2024
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Event name: 
27. Symposium Simulationstechnik (2024) 
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Event date: 
4-Sep-2024 - 6-Sep-2024
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Event place: 
München, Germany
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Number of Pages: 
8
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Publisher: 
ARGESIM Publisher Vienna, Vienna
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Keywords: 
Rheumatoid Arthritis; Recommendation Modeling; Health Applications
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Abstract: 
For the containment of chronic diseases, mHealth tools, for example mobile apps, provide great opportunities to track the disease progression and to give useful recommendations. In this project, possible data-driven enhancements for an already existing mobile app for patients with Rheumatoid Arthritis are discussed, developed and implemented. This happens in an ongoing feedback-cycle, including app developers, medical experts, patients and data scientists. The new features improve the app experience and are currently being evaluated in an observational study.
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Research Areas: 
Modeling and Simulation: 100%
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Science Branch: 
1020 - Informatik: 90%
5020 - Wirtschaftswissenschaften: 10%
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Appears in Collections:
Conference Paper

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