Development and internal validation of an interpretable machine learning model using routine laboratory data for systemic sclerosis-associated pulmonary arterial hypertension.
- DOI
- 10.1007/s00296-026-06255-5
- Published
- 2026 Jul 16
- Container
- Rheumatology international
- Publisher
- Not recorded
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1007/s00296-026-06255-5,
title = {Development and internal validation of an interpretable machine learning model using routine laboratory data for systemic sclerosis-associated pulmonary arterial hypertension.},
author = {Zhang Y and Feng S and Zhang Y and Luo J},
year = {2026},
journal = {Rheumatology international},
doi = {10.1007/s00296-026-06255-5},
url = {https://doi.org/10.1007/s00296-026-06255-5}
}RIS
TY - JOUR TI - Development and internal validation of an interpretable machine learning model using routine laboratory data for systemic sclerosis-associated pulmonary arterial hypertension. AU - Zhang Y AU - Feng S AU - Zhang Y AU - Luo J PY - 2026 JO - Rheumatology international DO - 10.1007/s00296-026-06255-5 UR - https://doi.org/10.1007/s00296-026-06255-5 ER -
APA
Y, Z., S, F., Y, Z., & J, L. (2026). Development and internal validation of an interpretable machine learning model using routine laboratory data for systemic sclerosis-associated pulmonary arterial hypertension.. Rheumatology international. https://doi.org/10.1007/s00296-026-06255-5
Source records
- pubmed · retrieved 2026-09-26T03:44:32.238Z