SEFA: Semantic Embedding-Based Feature Augmentation of Biomedical Language-Model Embeddings Improves Interpretable Metabolomic Prediction of Lung Cancer.
- DOI
- 10.3390/biomedicines14081856
- Published
- 2026 Aug 18
- Container
- Biomedicines
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.3390/biomedicines14081856,
title = {SEFA: Semantic Embedding-Based Feature Augmentation of Biomedical Language-Model Embeddings Improves Interpretable Metabolomic Prediction of Lung Cancer.},
author = {Wu J and Haince JF and Bux RA and Huang G and Tappia PS and Ramjiawan B and Vaida M},
year = {2026},
journal = {Biomedicines},
doi = {10.3390/biomedicines14081856},
url = {https://doi.org/10.3390/biomedicines14081856}
}RIS
TY - JOUR TI - SEFA: Semantic Embedding-Based Feature Augmentation of Biomedical Language-Model Embeddings Improves Interpretable Metabolomic Prediction of Lung Cancer. AU - Wu J AU - Haince JF AU - Bux RA AU - Huang G AU - Tappia PS AU - Ramjiawan B AU - Vaida M PY - 2026 JO - Biomedicines DO - 10.3390/biomedicines14081856 UR - https://doi.org/10.3390/biomedicines14081856 ER -
APA
J, W., JF, H., RA, B., G, H., PS, T., B, R., & M, V. (2026). SEFA: Semantic Embedding-Based Feature Augmentation of Biomedical Language-Model Embeddings Improves Interpretable Metabolomic Prediction of Lung Cancer.. Biomedicines. https://doi.org/10.3390/biomedicines14081856
Source records
- pubmed · retrieved 2026-09-26T22:16:07.399Z