Predicting Treatment Outcomes in Patients With Psoriatic Arthritis or Axial Spondyloarthritis: An Artificial Intelligence–Driven Approach
XAI provides significant value by enabling explanations of individual patient predictions and their visualizations. This modeling approach may help in the development of a clinical decision support system for patient management.
Authors
- Uta Kiltz (ORCID: https://orcid.org/0000-0001-5668-4497)
- Benjamin Gmeiner (ORCID: https://orcid.org/0000-0002-1517-8528)
- Jan Brandt‐Jürgens
- Michaela Köhm (ORCID: https://orcid.org/0000-0002-3579-5574)
- Asmir Vodenčarević
- David Simón (ORCID: https://orcid.org/0000-0001-8310-7820)
- Daniel Peterlik
- F. Behrens
- Stefan Bär (ORCID: https://orcid.org/0000-0003-4475-4579)
- Peter Kästner (ORCID: https://orcid.org/0000-0002-9530-006X)
- Thomas Glassen
Institutions
- Goethe University Frankfurt (DE)
- Friedrich-Alexander-Universität Erlangen-Nürnberg (DE)
- University of Erfurt (DE)
- Novartis (Germany) (DE)
- Universitätsklinikum Erlangen (DE)
- Rheumazentrum Ruhrgebiet (DE)
- Fraunhofer Institute for Translational Medicine and Pharmacology (DE)
- Public Health Dayton & Montgomery County (US)
- University Hospital Frankfurt (DE)
- Praxis für Hämatologie und Onkologie (DE)
- Charité - Universitätsmedizin Berlin (DE)
- Ruhr University Bochum (DE)
Publication Details
- Journal
- The Journal of Rheumatology
- Published
- 2025-10-15
- DOI
- https://doi.org/10.3899/jrheum.2025-0327
- Citations
- 2
- Primary Topic
- Spondyloarthritis Studies and Treatments
- Type
- article
- Field-Weighted Citation Impact
- 3.34