Disease Phenotypes in Refractory Musculoskeletal Pain Syndromes Identified by Unsupervised Machine Learning
Our model identified and visualized clinically relevant chronic musculoskeletal pain subtypes and predicted their response to multimodal treatment. Such digital personas and avatars may play a future role in the design of personalized therapeutic modalities and clinical trials.
Authors
- Marc R. Suter (ORCID: https://orcid.org/0000-0002-4653-0512)
- Thomas Hügle (ORCID: https://orcid.org/0000-0002-3276-9581)
- Tiffany Prétat (ORCID: https://orcid.org/0009-0009-8076-1769)
- Christopher A. Lovejoy (ORCID: https://orcid.org/0000-0003-0919-1264)
- Pedro Ming Azevedo (ORCID: https://orcid.org/0000-0003-3321-266X)
Institutions
- University of Lausanne (CH)
Publication Details
- Journal
- ACR Open Rheumatology
- Published
- 2024-08-29
- DOI
- https://doi.org/10.1002/acr2.11699
- Citations
- 8
- Primary Topic
- Fibromyalgia and Chronic Fatigue Syndrome Research
- Type
- article
- Field-Weighted Citation Impact
- 3.08