PhenoSS: phenotype semantic similarity-based approach for rare disease prediction and patient clustering
- DOI
- 10.1093/jamia/ocag131
- Published
- 2026-07-31
- Container
- Journal of the American Medical Informatics Association
- Publisher
- Oxford University Press (OUP)
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1093/jamia/ocag131,
title = {PhenoSS: phenotype semantic similarity-based approach for rare disease prediction and patient clustering},
author = {Shihan Chen and Quan M Nguyen and Yu Hu and Cong Liu and Chunhua Weng and Kai Wang},
year = {2026},
journal = {Journal of the American Medical Informatics Association},
doi = {10.1093/jamia/ocag131},
url = {https://doi.org/10.1093/jamia/ocag131}
}RIS
TY - JOUR TI - PhenoSS: phenotype semantic similarity-based approach for rare disease prediction and patient clustering AU - Shihan Chen AU - Quan M Nguyen AU - Yu Hu AU - Cong Liu AU - Chunhua Weng AU - Kai Wang PY - 2026 JO - Journal of the American Medical Informatics Association DO - 10.1093/jamia/ocag131 UR - https://doi.org/10.1093/jamia/ocag131 ER -
APA
Chen, S., Nguyen, Q. M., Hu, Y., Liu, C., Weng, C., & Wang, K. (2026). PhenoSS: phenotype semantic similarity-based approach for rare disease prediction and patient clustering. Journal of the American Medical Informatics Association. https://doi.org/10.1093/jamia/ocag131
Source records
- crossref · retrieved 2026-11-10T09:31:25.471Z