Record link: 
http://hdl.handle.net/20.500.12708/204634
-
Title: 
Recommendation Modeling for Health Self-Management Applications for People with Rheumatoid Arthritis
en
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
-
Publisher DOI: 
10.11128/arep.47.a4725
-
Publication Type: 
Inproceedings - Full-Paper Contribution
en
Language: 
English
-
Authors: 
Schwab, Nadine 
Zauner, Günther 
Urach, Christoph 
Studenic, Paul 
Radner, Helga 
Nakhost-Lotfi, Nasim 
Stamm, Tanja 
Hammer-Jakobsen, Thomas 
Dam, Andreas 
Popper, Nikolas 
-
Organisational Unit: 
E194-04 - Forschungsbereich Data Science 
E105-06 - Forschungsbereich Computational Statistics 
-
Published in: 
Tagungsband Langbeiträge ASIM SST 2024, 27. Symposium Simulationstechnik, München 
-
ISBN: 
978-3-903347-65-6
-
DOI of the book: 
10.11128/arep.47
-
Date (published): 
2024
-
Event name: 
27. Symposium Simulationstechnik (2024) 
de
Event date: 
4-Sep-2024 - 6-Sep-2024
-
Event place: 
München, Germany
-
Number of Pages: 
8
-
Publisher: 
ARGESIM Publisher Vienna, Vienna
-
Keywords: 
Rheumatoid Arthritis; Recommendation Modeling; Health Applications
en
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.
en
Research Areas: 
Modeling and Simulation: 100%
-
Science Branch: 
1020 - Informatik: 90%
5020 - Wirtschaftswissenschaften: 10%
-
Appears in Collections:
Conference Paper

Show full item record

Page view(s)

176
checked on Nov 25, 2024

Google ScholarTM

Check