A reproducible symptom-based computational phenotyping framework for longitudinal fibromyalgia analysis using real-world registry data: a cross-cohort validation study
- DOI
- 10.1186/s12911-026-03740-6
- Published
- 2026-08-05
- Container
- BMC Medical Informatics and Decision Making
- Publisher
- Springer Science and Business Media LLC
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1186/s12911-026-03740-6,
title = {A reproducible symptom-based computational phenotyping framework for longitudinal fibromyalgia analysis using real-world registry data: a cross-cohort validation study},
author = {Nazario Felix-Gonzalez and Jose-Maria Gomez-Arguelles and Ceferino Maestu-Unturbe},
year = {2026},
journal = {BMC Medical Informatics and Decision Making},
doi = {10.1186/s12911-026-03740-6},
url = {https://doi.org/10.1186/s12911-026-03740-6}
}RIS
TY - JOUR TI - A reproducible symptom-based computational phenotyping framework for longitudinal fibromyalgia analysis using real-world registry data: a cross-cohort validation study AU - Nazario Felix-Gonzalez AU - Jose-Maria Gomez-Arguelles AU - Ceferino Maestu-Unturbe PY - 2026 JO - BMC Medical Informatics and Decision Making DO - 10.1186/s12911-026-03740-6 UR - https://doi.org/10.1186/s12911-026-03740-6 ER -
APA
Felix-Gonzalez, N., Gomez-Arguelles, J., & Maestu-Unturbe, C. (2026). A reproducible symptom-based computational phenotyping framework for longitudinal fibromyalgia analysis using real-world registry data: a cross-cohort validation study. BMC Medical Informatics and Decision Making. https://doi.org/10.1186/s12911-026-03740-6
Source records
- crossref · retrieved 2026-11-04T23:00:31.880Z