RTSANet: learning sequential-attentive hybrid networks for drug information-enhanced medication recommendation.
- DOI
- 10.1080/10255842.2026.2729440
- Published
- 2026 Sep 23
- Container
- Computer methods in biomechanics and biomedical engineering
- Publisher
- Not recorded
- Open access
- unknown
Credibility signals
limited evidence Score 43/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.
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Cite this work
BibTeX
@article{allodium:10.1080/10255842.2026.2729440,
title = {RTSANet: learning sequential-attentive hybrid networks for drug information-enhanced medication recommendation.},
author = {Zhang Y and Wang Z and Du S and Li W and Wang S},
year = {2026},
journal = {Computer methods in biomechanics and biomedical engineering},
doi = {10.1080/10255842.2026.2729440},
url = {https://doi.org/10.1080/10255842.2026.2729440}
}RIS
TY - JOUR TI - RTSANet: learning sequential-attentive hybrid networks for drug information-enhanced medication recommendation. AU - Zhang Y AU - Wang Z AU - Du S AU - Li W AU - Wang S PY - 2026 JO - Computer methods in biomechanics and biomedical engineering DO - 10.1080/10255842.2026.2729440 UR - https://doi.org/10.1080/10255842.2026.2729440 ER -
APA
Y, Z., Z, W., S, D., W, L., & S, W. (2026). RTSANet: learning sequential-attentive hybrid networks for drug information-enhanced medication recommendation.. Computer methods in biomechanics and biomedical engineering. https://doi.org/10.1080/10255842.2026.2729440
Source records
- pubmed · retrieved 2026-09-25T22:56:00.164Z