Integrating genetic, epigenetic, and clinical signatures via machine learning for robust prediction of leflunomide response in rheumatoid arthritis: a multi-center validation study.
- DOI
- 10.3389/fimmu.2026.1804485
- Published
- 2026
- Container
- Frontiers in immunology
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.3389/fimmu.2026.1804485,
title = {Integrating genetic, epigenetic, and clinical signatures via machine learning for robust prediction of leflunomide response in rheumatoid arthritis: a multi-center validation study.},
author = {Chen M and Liu H and Jin L and Feng X and Dai B and Wang F and Wang Q and Chen Y and Yi M and Jia B and Dong K and Zhang J and Fan Z and Li J and Zhao F and Jia Y and Wang J and Liu M and Xu J and Fu L},
year = {2026},
journal = {Frontiers in immunology},
doi = {10.3389/fimmu.2026.1804485},
url = {https://doi.org/10.3389/fimmu.2026.1804485}
}RIS
TY - JOUR TI - Integrating genetic, epigenetic, and clinical signatures via machine learning for robust prediction of leflunomide response in rheumatoid arthritis: a multi-center validation study. AU - Chen M AU - Liu H AU - Jin L AU - Feng X AU - Dai B AU - Wang F AU - Wang Q AU - Chen Y AU - Yi M AU - Jia B AU - Dong K AU - Zhang J AU - Fan Z AU - Li J AU - Zhao F AU - Jia Y AU - Wang J AU - Liu M AU - Xu J AU - Fu L PY - 2026 JO - Frontiers in immunology DO - 10.3389/fimmu.2026.1804485 UR - https://doi.org/10.3389/fimmu.2026.1804485 ER -
APA
M, C., H, L., L, J., X, F., B, D., F, W., Q, W., Y, C., M, Y., B, J., K, D., J, Z., Z, F., J, L., F, Z., Y, J., J, W., M, L., J, X., & L, F. (2026). Integrating genetic, epigenetic, and clinical signatures via machine learning for robust prediction of leflunomide response in rheumatoid arthritis: a multi-center validation study.. Frontiers in immunology. https://doi.org/10.3389/fimmu.2026.1804485
Source records
- pubmed · retrieved 2026-09-27T01:12:00.903Z