<div class="csl-bib-body">
<div class="csl-entry">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 <i>Tagungsband Langbeiträge ASIM SST 2024, 27. Symposium Simulationstechnik, München</i> (pp. 43–50). ARGESIM Publisher Vienna. https://doi.org/10.11128/arep.47.a4725</div>
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dc.identifier.uri
http://hdl.handle.net/20.500.12708/204634
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dc.description.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
dc.language.iso
en
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dc.relation.ispartofseries
Tagungsbände Symposium Simulationstechnik (SST)
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dc.subject
Rheumatoid Arthritis
en
dc.subject
Recommendation Modeling
en
dc.subject
Health Applications
en
dc.title
Recommendation Modeling for Health Self-Management Applications for People with Rheumatoid Arthritis
en
dc.type
Inproceedings
en
dc.type
Konferenzbeitrag
de
dc.contributor.affiliation
Karolinska Institutet, Sweden
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dc.contributor.affiliation
Medical University of Vienna, Austria
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dc.contributor.affiliation
Copenhagen Living Lab (Copenhagen, DK)
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dc.relation.isbn
978-3-903347-65-6
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dc.relation.doi
10.11128/arep.47
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dc.description.startpage
43
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dc.description.endpage
50
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dc.type.category
Full-Paper Contribution
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tuw.booktitle
Tagungsband Langbeiträge ASIM SST 2024, 27. Symposium Simulationstechnik, München
