Optimizing word embeddings for small datasets: a case study on patient portal messages from breast cancer patients
- DOI
- 10.1038/s41598-024-66319-z
- Published
- 2024-07-12
- Container
- Scientific Reports
- Publisher
- Springer Science and Business Media LLC
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1038/s41598-024-66319-z,
title = {Optimizing word embeddings for small datasets: a case study on patient portal messages from breast cancer patients},
author = {Qingyuan Song and Congning Ni and Jeremy L. Warner and Qingxia Chen and Lijun Song and S. Trent Rosenbloom and Bradley A. Malin and Zhijun Yin},
year = {2024},
journal = {Scientific Reports},
doi = {10.1038/s41598-024-66319-z},
url = {https://doi.org/10.1038/s41598-024-66319-z}
}RIS
TY - JOUR TI - Optimizing word embeddings for small datasets: a case study on patient portal messages from breast cancer patients AU - Qingyuan Song AU - Congning Ni AU - Jeremy L. Warner AU - Qingxia Chen AU - Lijun Song AU - S. Trent Rosenbloom AU - Bradley A. Malin AU - Zhijun Yin PY - 2024 JO - Scientific Reports DO - 10.1038/s41598-024-66319-z UR - https://doi.org/10.1038/s41598-024-66319-z ER -
APA
Song, Q., Ni, C., Warner, J. L., Chen, Q., Song, L., Rosenbloom, S. T., Malin, B. A., & Yin, Z. (2024). Optimizing word embeddings for small datasets: a case study on patient portal messages from breast cancer patients. Scientific Reports. https://doi.org/10.1038/s41598-024-66319-z
Source records
- crossref · retrieved 2026-11-08T23:08:59.821Z